智能交通信号灯毕业设计外文翻译
基于PLC的交通灯控制系统设计外文翻译
毕业设计（外文翻译）英文题目 PLC-based design of traffic lights中文题目基于PLC的交通灯设计系（院）自动化系专业电气工程与自动化学生姓名学号 2009022388指导教师职称讲师二〇一三年六月PLC-based design of traffic lights Abstract: One kind of traffic light control system using programmable logic controller (PLC), via software control traffic lights run automatically. In the system, the original line is the program instead of the relay, programmable logic controller (PLC) system hardware and software resources to be fair use. Normal operation and emergency transport for a detailed description and from the East and West emergencies can be mutually linked. Traffic signal systems and two seven-segment digital display in the countdown order; also discussed in detail the wiring of the hardware and PLC ladder. Traffic lights at the crossroads of the remote monitoring system design configuration software MCGS, real-time monitoring of traffic lights, greatly improving the reliability of data transmission. At the same time, we can configure the traffic lights to change the status of photographs.Keywords: switching power,supply protection, circuit system design1. IntroductionWith the social development and progress, traffic flow becomes increasingly important. On the one hand, too many crossroads, more and more vehicles, which are causing serious traffic congestion. On the other hand, in the limited time it is necessary to maintain the vehicle and pedestrian fast and safe. Therefore, one kind of traffic light control system design, can be used to display time countdown, with computer controlled real-time data. In addition, the configuration technology for real-time images that reflect the traffic lights, understand the historical crossroads of work to get traffic lights visualization. The system consists of host computer and a low computer. MCGS configuration is installed in the host computer is lower by the PLC control system.Normal traffic signal timing diagram shown in Figure 1. But there are some urgent matters, for example. There are a number of ambulances to transport patients to the hospital or to deal with a number of fire engines and fire. Fire engines and ambulances rushed to take precedence over other traffic scene. According to urban traffic control system, under normal circumstances, two control methods and urgency traffic control factors into account. This process can show 14 segment encoder. U.S. traffic lights instant record of the monitoring process.Emergency control signals to control traffic emergency switch. If there is no emergency lights all work, but when an emergency open. In this case, the car is urgent priority pass. Once the emergency vehicle passes, emergency switch off immediately. The green light in the same direction of the vehicle quickly flashes three times, followed by the normal operation. If you were from the north-south and east-west two emergency vehicles, traffic control systems can respond quickly came early, and then another.2. Traffic Control System DesignA. Hardware designCP1H series PLC as controller, display the procedure should stop when the time series of abnormal system operation, the time will not be displayed. When the emergency procedures are completed time series, countdown display program should be reset. At 220 V AC system is used to control traffic lights, 24 V DC control segment encoder, Figure 2 shows the scheme Eastern time display. CP1H series programmable logic controller (PLC) is a simple controller, which consists of 24 inputs and sixteen outputs. Because the output to twenty In this system, an I / Omodule must be extended. Circuit is shown in Figure 2.B. Control Program DesignSix timers and two special normal open pulse is used in this system, the green light flashes for all north-south and east-timer and a special pulse; eight kinds ofinterlocking internal relay is used to implement the urgency and transmit pulse two directions to PLC, shown in the figure. Two SDEC instructions are used to display the countdown display the corresponding light. As an important part of the countdown display program, east and west of the green light reflected in the view 4 in these programs downloaded to the programmable logic controller (PLC), all the traffic lights running accuracy, urgency, and things can be interlocked from north to south strictly, all the lights can be set back to the urgency of passing state. Therefore, these control program is correct, simple.C. Monitoring SystemComputer system has two main functions: an output signal acquisition and display real-time status of the programmable logic controller (PLC) to control traffic lights, traffic lights. Another notification robot status and history of the state real-time curve by examining the history and alarm window.This monitoring system design and configuration software MCGS configuration is easy. The serial communication is implemented as follows.Data inspection methods: double endedSerial Communications Number: COM0 endedThe minimum sampling period: 200 msProgrammable Logic Controller (PLC) The parameters are defined as follows: The minimum sampling period of the basic properties: 200 msThree read / write channel: X0, X1, X2Six read-only access (read U.S. traffic lights): Q0-Q5All channels must be connected to a variable defined in a real-time database access visits and other parameters to their default values. After a successful relationship, PLC and computer control system is able to change the color of the analog signal lights in the picture on the PC being collected data through the serial port.. In contrast, by changing the parameters of the host, the corresponding value is written to the PLC internal relay control, intersection traffic lights can be implemented. Experimental results show that the system is usually good enough and animation. Online monitoring system of traffic lights in Figure 5:3. ConclusionExperimental results show that the system is usually configured with enough good photos. This system simplifies the programmable logic controller (PLC) and the communication between the host computer using industrial configuration software development time is greatly reduced. In particular, more suitable for complex controlsystems. We can control the traffic lights by the PLC and MCGS configuration, replace the original relay control, improve the system's lifetime. At the same time, this method can be applied to control the motor and fluid levels. Remote control and configuration combined with the simulation, can be applied to similar control zone. 4. References[1] Whitworth, Duller, Jones D I. Aerial video inspection of overhead power lines [J].PowerEngineering Journal,2001,15:25-32.[2] Jan Axelson, Lakeview Research-Serial port complete [D]. USA:1999:91-135.基于PLC的交通灯控制系统设计摘要一种交通灯控制系统采用可编程序控制器(PLC), 通过软件控制交通灯自动运行。
交通工程专业毕业论文及外文文献-智能交通灯系统设计
毕业论文中文题目：智能交通灯系统设计外文题目：DESIGN OF INTELLIGENT TRAFFIC LIGHT S YSTEM附录A外文文献中文译文附录B外文文献毕业设计（论文）共75 页（其中：外文文献及译文23 页）图纸共1 张完成日期2016 年6 月答辩日期2016 年6 月摘要随着科学技术的发展，交通运输工具发展也愈来愈快，交通堵塞，交通事故频发，严重影响到人们的正常生活。
因此，一个功能完整，运行系统稳定，符合交通正常运行并且人性化的交通灯系统可以为我们的生活带来安全的保障，同时也有利于提高人们出行的便捷。
本文综合叙述了光电传感技术，交通灯的发展现状，在交通灯的基本功能即单片机控制红黄绿灯显示通行或禁行，数码管显示倒计时时间，黄闪等功能基础上，增加了紧急处理按键，应用光电传感器实现车流量检测智能调整时间以及闯红灯报警功能。
本文共分为六大部分，交通灯基本知识的介绍，光电开关技术的介绍，智能交通灯总体设计，硬件电路设计，软件设计以及智能交通灯设计的总结。
通过增加车流量检测及闯红灯报警等功能，体现了现代交通灯的智能功能，可以根据检测到的车流量自动调节下一周期绿灯的时间，从而减轻通行压力。
关键词：智能交通灯；车流量检测；光电开关AbstractWith the development of science technology, the development of transportbecomes fast.Traffic jam, frequent traffic accidents have the serious influence onhuman's normal life.A fully functional, stable operation system, conform to the normal operation of traffic and humanized traffic light system can bring us life security, as well as improve the convenience of travel.This article comprehensively describes thephotoelectric sensor technology , the development and status quo of traffic lights,besides the basic function ofthe chip microcomputer control traffic light shows the people pass or stop, digital tube displays the countdown time, yellow flashing, and other functions, I increase the emergency handling keys, adjusting time with the application of photoelectric sensors for detecting traffic and red light alarm functions. This article is divided into six parts, the introduction of basic knowledge about traffic lights ,the Photoelectric switch technology,the intelligent traffic light overall design, the hardware circuit design, the software design, as well as the summary and prospect of intelligent traffic light design.By increasing traffic detection and,red light alarm, and other functions,which embodies the modern intelligent function of traffic lights, traffic can be detected according to automatically adjust the next cycle of green light time, so as to alleviate traffic pressure.Key words:Intelligent traffic lights; Traffic detection; Photoelectric switch目录1 绪论 (1)1.1 研究目的 (1)1.2 研究意义 (1)1.3 交通灯发展历史 (2)1.4 交通灯分类及控制方式 (2)1.4.1 交通灯分类 (2)1.4.2 交通灯控制 (4)1.5 智能交通灯的研究现状 (4)1.6 预期实现功能 (5)1.7 主要内容安排 (7)2 光电传感技术 (8)2.1 光电开关特点 (8)2.2 光电开关分类 (8)2.2.1 按结构分类 (8)2.2.2 按检测方式分类 (8)2.3 光电开关的工作原理 (10)2.4 光电传感器技术应用 (11)2.5 光电开关使用注意事项 (11)3 总体设计方案选择 (12)3.1 控制模块方案选择 (12)3.2 显示模块方案选择 (13)3.3 输入模块方案选择 (14)3.4 传感器模块方案选择 (14)4 硬件系统设计 (17)4.1STC89C51 单片机介绍 (17)4.2 单片机最小系统 (20)4.2.1 时钟电路 (20)4.2.2 复位电路 (21)4.3 显示模块 (22)4.3.1 发光二极管 (22)4.3.2 数码管 (23)4.4 按键模块 (24)4.5 光电开关模块 (25)4.6 蜂鸣器模块 (25)5 软件设计 (27)5.1 主程序设计 (27)5.2 子程序设计 (28)5.2.1 显示子程序设计 (28)5.2.2 外部中断子程序设计 (29)5.2.3 定时中断子程序设计 (29)6 系统仿真 (31)6.1 仿真软件介绍 (31)6.2 仿真结果及分析 (31)7 总结 (38)致谢 (39)参考文献 (40)附录 A 译文 (41)附录 B 外文文献 (51)附录 C 硬件电路图 (64)附录 D 程序代码 (65)辽宁工程技术大学毕业设计（论文）1 绪论本章重点介绍智能交通灯的研究目的、研究意义、以及交通灯的发展过程、交通灯分类及控制方式、智能交通灯的研究现状和预期实现功能。
智能交通系统中英文对照外文翻译文献
智能交通系统中英文对照外文翻译文献(文档含英文原文和中文翻译)原文:Traffic Assignment Forecast Model Research in ITS IntroductionThe intelligent transportation system (ITS) develops rapidly along with the city sustainable development, the digital city construction and the development of transportation. One of the main functions of the ITS is to improve transportation environment and alleviate the transportation jam, the most effective method to gain the aim is to forecast the traffic volume of the local network and the important nodes exactly with GIS function of path analysis and correlation mathematic methods, and this will lead a better planning of the traffic network. Traffic assignment forecast is an important phase of traffic volume forecast. It will assign the forecasted traffic to every way in the traffic sector. If the traffic volume of certain road is too big, which would bring on traffic jam, planners must consider the adoption of new roads or improving existing roads to alleviate the traffic congestion situation. This study attempts to present an improved traffic assignment forecast model, MPCC, based on analyzing the advantages and disadvantages of classic traffic assignment forecast models, and test the validity of the improved model in practice.1 Analysis of classic models1.1 Shortcut traffic assignmentShortcut traffic assignment is a static traffic assignment method. In this method, the traffic load impact in the vehicles’ travel is not considered, and the traffic impedance (travel time) is a constant. The traffic volume of every origination-destination couple will be assigned to the shortcut between the origination and destination, while the traffic volume of other roads in this sector is null. This assignment method has the advantage of simple calculation; however, uneven distribution of the traffic volume is its obvious shortcoming. Using this assignment method, the assignment traffic volume will be concentrated on the shortcut, which isobviously not realistic. However, shortcut traffic assignment is the basis of all theother traffic assignment methods.1.2 Multi-ways probability assignmentIn reality, travelers always want to choose the shortcut to the destination, whichis called the shortcut factor; however, as the complexity of the traffic network, thepath chosen may not necessarily be the shortcut, which is called the random factor.Although every traveler hopes to follow the shortcut, there are some whose choice isnot the shortcut in fact. The shorter the path is, the greater the probability of beingchosen is; the longer the path is, the smaller the probability of being chosen is.Therefore, the multi-ways probability assignment model is guided by the LOGIT model:∑---=n j ii i F F p 1)exp()exp(θθ (1)Where i p is the probability of the path section i; i F is the travel time of thepath section i; θ is the transport decision parameter, which is calculated by the followprinciple: firstly, calculate the i p with different θ (from 0 to 1), then find the θwhich makes i p the most proximate to the actual i p .The shortcut factor and the random factor is considered in multi-ways probabilityassignment, therefore, the assignment result is more reasonable, but the relationshipbetween traffic impedance and traffic load and road capacity is not considered in thismethod, which leads to the assignment result is imprecise in more crowded trafficnetwork. We attempt to improve the accuracy through integrating the several elements above in one model-MPCC.2 Multi-ways probability and capacity constraint model2.1 Rational path aggregateIn order to make the improved model more reasonable in the application, theconcept of rational path aggregate has been proposed. The rational path aggregate,which is the foundation of MPCC model, constrains the calculation scope. Rationalpath aggregate refers to the aggregate of paths between starts and ends of the trafficsector, defined by inner nodes ascertained by the following rules: the distancebetween the next inner node and the start can not be shorter than the distance betweenthe current one and the start; at the same time, the distance between the next innernode and the end can not be longer than the distance between the current one and theend. The multi-ways probability assignment model will be only used in the rationalpath aggregate to assign the forecast traffic volume, and this will greatly enhance theapplicability of this model.2.2 Model assumption1) Traffic impedance is not a constant. It is decided by the vehicle characteristicand the current traffic situation.2) The traffic impedance which travelers estimate is random and imprecise.3) Every traveler chooses the path from respective rational path aggregate.Based on the assumptions above, we can use the MPCC model to assign thetraffic volume in the sector of origination-destination couples.2.3 Calculation of path traffic impedanceActually, travelers have different understanding to path traffic impedance, butgenerally, the travel cost, which is mainly made up of forecast travel time, travellength and forecast travel outlay, is considered the traffic impedance. Eq. (2) displaysthis relationship. a a a a F L T C γβα++= (2)Where a C is the traffic impedance of the path section a; a T is the forecast traveltime of the path section a; a L is the travel length of the path section a; a F is theforecast travel outlay of the path section a; α, β, γ are the weight value of that threeelements which impact the traffic impedance. For a certain path section, there aredifferent α, β and γ value for different vehicles. We can get the weighted average of α,β and γ of each path section from the statistic percent of each type of vehicle in thepath section.2.4 Chosen probability in MPCCActually, travelers always want to follow the best path (broad sense shortcut), butbecause of the impact of random factor, travelers just can choose the path which is ofthe smallest traffic impedance they estimate by themselves. It is the key point ofMPCC. According to the random utility theory of economics, if traffic impedance is considered as the negativeutility, the chosen probability rs p of origination-destinationpoints couple (r, s) should follow LOGIT model:∑---=n j jrs rs bC bC p 1)exp()exp( (3) where rs p is the chosen probability of the pathsection (r, s);rs C is the traffic impedance of the path sect-ion (r, s); j C is the trafficimpedance of each path section in the forecast traffic sector; b reflects the travelers’cognition to the traffic impedance of paths in the traffic sector, which has reverseratio to its deviation. If b → ∞ , the deviation of understanding extent of trafficimpedance approaches to 0. In this case, all the travelers will follow the path whichis of the smallest traffic impedance, which equals to the assignment results withShortcut Traffic Assignment. Contrarily, if b → 0, travelers ’ understanding error approaches infinity. In this case, the paths travelers choose are scattered. There is anobjection that b is of dimension in Eq.(3). Because the deviation of b should beknown before, it is difficult to determine the value of b. Therefore, Eq.(3) is improvedas follows:∑---=n j OD j OD rsrs C bC C bC p 1)exp()exp(，∑-=n j j OD C n C 11（4） Where OD C is the average of the traffic impedance of all the as-signed paths; bwhich is of no dimension, just has relationship to the rational path aggregate, ratherthan the traffic impedance. According to actual observation, the range of b which is anexperience value is generally between 3.00 to 4.00. For the more crowded cityinternal roads, b is normally between 3.00 and 3.50.2.5 Flow of MPCCMPCC model combines the idea of multi-ways probability assignment anditerative capacity constraint traffic assignment.Firstly, we can get the geometric information of the road network and OD trafficvolume from related data. Then we determine the rational path aggregate with themethod which is explained in Section 2.1.Secondly, we can calculate the traffic impedance of each path section with Eq.(2),Fig.1 Flowchart of MPCC which is expatiated in Section 2.3.Thirdly, on the foundation of the traffic impedance of each path section, we cancalculate the respective forecast traffic volume of every path section with improvedLOGIT model (Eq.(4)) in Section 2.4, which is the key point of MPCC.Fourthly, through the calculation processabove, we can get the chosen probability andforecast traffic volume of each path section, but itis not the end. We must recalculate the trafficimpedance again in the new traffic volumesituation. As is shown in Fig.1, because of theconsideration of the relationship between trafficimpedance and traffic load, the traffic impedanceand forecast assignment traffic volume of everypath will be continually amended. Using therelationship model between average speed andtraffic volume, we can calculate the travel timeand the traffic impedance of certain path sect-ionunder different traffic volume situation. For theroads with different technical levels, therelationship models between average speeds totraffic volume are as follows: 1) Highway: 1082.049.179AN V = (5) 2) Level 1 Roads: 11433.084.155AN V = (6) 3) Level 2 Roads: 66.091.057.112AN V = (7) 4) Level 3 Roads: 3.132.01.99AN V = (8) 5) Level 4 Roads: 0988.05.70A N V =(9) Where V is the average speed of the path section; A N is the traffic volume of thepath section.At the end, we can repeat assigning traffic volume of path sections with themethod in previous step, which is the idea of iterative capacity constraint assignment,until the traffic volume of every path section is stable.译文智能交通交通量分配预测模型介绍随着城市的可持续化发展、数字化城市的建设以及交通运输业的发展，智能交通系统（ITS）的发展越来越快。
交通灯外文翻译（5篇范文）
交通灯外文翻译（5篇范文）第一篇：交通灯外文翻译Traffic lights and PLCWith economic development, increased the number of vehicles, road congestion is becoming increasingly serious, intelligent traffic lights on the emerged.At present, the world's Intelligent Transportation System will be: a huge structure, management difficulties, such as the maintenance of large inputs.In order to improve the existing traffic conditions, and to overcome the existing shortcomings of intelligent transportation system I designed analog control traffic lights in urban and rural areas of small-scale smart traffic lights.It has small size, intelligence, maintenance into small, easy to install and so on.And other intelligent transportation system compared to the system to adapt to economic and social development, in line with the current status of scientific and technological development.Intelligent traffic lights are a comprehensive use of computer network communication technology, sensor technology to manage the automatic control system of traffic lights.Urban traffic control system is used for urban traffic data monitoring, traffic signal control and traffic management computer system;it is the modern urban traffic control system command and the most important component.In short, how to use the appropriate control method to maximize the use of costly cities to build high-speed roads, trunk road and the ramp to alleviate urban areas with the neighboring state of traffic congestion has become more and more traffic management and urban planning departments need to address the the main problem.Nowadays, traffic lights installed in each crossing, hasbecome the most common and dredge the traffic, the most effective means.The development of the society, people's consumption level unceasing enhancement, private vehicles unceasing increase.And more cars roads are narrow road traffic is clear.So adopting effective method to control the traffic light is imperative.PLC intelligent control principle is the core of the control system, PLC put the things direction or north-south direction according to quantity of vehicles, the corresponding scale what divides class given the green light direction between north and south direction according to certain rules too long.It can realize divides class according to a given the green cars duration scale of maximum car release, reduce crossroads vehicles, ease traffic congestion stagnation, realize the optimal control, so as to improve the efficiency of the traffic control system.The application of PLC is continuously, and drive to the deepening traditional control test new month benefit updates.It is simple in structure, programming and high reliability etc, convenient already widely used in industrial processes and position in the automatic control.Due to use of PLC has the characteristics of environmental adaptable, and its internal timer is very rich in resources, but the current widely used “progressive” lights, especially for precise control more than thecrossway control can be easily realized.So now increasingly applying PLC traffic light system.Meanwhile, PLC itself also has communication networking function, will the same path as part of a LAN signal unified dispatching management, can shorten the traffic wait times, realize scientific management.In real-time detection and automatic control of PLC application system, PLC is often used as a core components.In the 21st century, PLC willhave greater development.Technically, the computer technology can morely new achievements used in programmable controller design and manufacturing, there will be faster, storage and larger capacity, intelligent stronger varieties appear;Look from product size, can further to mini and super-large direction;Look from product compatibility, the variety of our products will be more rich, specification more complete, perfect man-machine interface and complete communication equipment can better adapt to all kinds of industrial control occasion demands;Look from the market, all countries to their production of multiple products with international competition intensifies and break, can appear a few brand monopoly international market situation, can appear international general programming languages;Judging from the development of the network, programmable controller and other industrial control computer networking constitute a large control system is programmable controller technology development direction.The current computer distributed control system DCS has already a lot of programmable controller applications.Along with the development of computer network, the programmable controller as automation control network and international general network will be an important part of the industry and industry, the numerous fields outside play an increasing role.In China the increasing amount of motor vehicles, many big cities like Beijing, Shanghai, nanjing and other ground appeared traffic overload running condition, traffic accidents problem also more and more serious.And because the various special vehicles(such as an ambulance, 119 120 car, police and various special vehicle 110 in emergency situations, by red under limited to traffic bring a lot of inconvenience, even cause traffic accident.And now, most traffic lights at the same moment willappear two or more than two direction at the same time for the green situation, and increase the incidence of the traffic accident.Therefore, design a kind of designed for special vehicles through and not cause any traffic accident, normal traffic control any time only one direction of modern intelligent traffic light green traffic control system is urgently needed.交通灯与PLC 随着经济的发展，车辆的数目不断增加，道路堵车现象日益严重，智能交通灯就应运而生了。
交通灯控制系统外文翻译--
本科毕业设计（外文翻译）题目小型交通灯控制系统的设计与制作姓名韦强专业电子科学与技术学号 201031090指导老师洪新华郑州科技学院电气工程学院二0一四年五月二日THE DESIGN AND MANUFACTURE OF SMALL TRAFFICLIGHT CONTROL SYSTEM8-bit Microcontroller With 8K Bytes Flash AT89C52 DescriptionThe AT89C52 is a low-power, high-performance CMOS 8-bit microcomputer with 8K bytes of Flash programmable and erasable read only memory (PEROM). The device is manufactured using Atmel’s high-density nonvolatile memory technology and is compatible with the industry-standard 80C51 and 80C52 instruction set and pin out. The on-chip Flash allows the program memory to be reprogrammed in-system or by a conventional nonvolatile memory programmer. By combining a versatile 8-bit CPU with Flash on a monolithic chip, the Atmel AT89C52 is a powerful microcomputer which provides a highly-flexible and cost-effective solution to many embedded control applications.Pin Configurations1Pin DescriptionVCCSupply voltage.GNDGround.Port 0Port 0 is an 8-bit open drain bi-directional I/O port. As an output port, each pin can sink eight TTL inputs. When 1s are written to port 0 pins, the pins can be used as high-impedance inputs. Port 0 can also be configured to be the multiplexed low-order address/data bus during accesses to external program and data memory. In this mode, P0 has internal pull-ups. Port 0 also receives the code bytes during Flash programming and outputs the code bytes during program verification. External pull-ups are required during program verification.Port 1Port 1 is an 8-bit bi-directional I/O port with internal pull-ups. The Port 1 output buffers can sink/source four TTL inputs. When 1s are written to Port 1 pins, they are pulled high by the internal pull-ups and can be used as inputs. As inputs, Port 1 pins that are externally being pulled low will source current (I IL) because of the internal pull-ups. In addition, P1.0 and P1.1 can be configured to be the timer/counter 2 external count input (P1.0/T2) and the timer/counter 2 trigger input (P1.1/T2EX), respectively, as shown in the following table. Port 1 also receives the low-order address bytes during Flash programming and verification.2Port 2Port 2 is an 8-bit bi-directional I/O port with internal pull-ups. The Port 2 output buffers can sink/source four TTL inputs. When 1s are written to Port 2 pins, they are pulled high by the internal pull-ups and can be used as inputs. As inputs, Port 2 pins that are externally being pulled low will source current (I IL) because of the internal pull-ups. Port 2 emits the high-order address byte during fetches from external program memory and during accesses to external data memories that use 16-bit addresses (MOVX @DPTR). In this application, Port 2 uses strong internal pull-ups when emitting 1s. During accesses to external data memories that use 8-bit addresses (MOVX @ RI), Port 2 emits the contents of the P2 Special Function Register. Port 2 also receives the high-order address bits and some control signals during Flash programming and verification.Port 3Port 3 is an 8-bit bi-directional I/O port with internal pull-ups. The Port 3 output buffers can sink/source four TTL inputs. When 1s are written to Port 3 pins, they are pulled high by the internal pull-ups and can be used as inputs. As inputs, Port 3 pins that are externally being pulled low will source current (I IL) because of the pull-ups.Port 3 also serves the functions of various special features of the AT89C51, as shown in the following table. Port 3 also receives some control signals for Flash programming and verification.3RSTReset input. A high on this pin for two machine cycles while the oscillator is running resets the device.PSENProgram Store Enable is the read strobe to external program memory. When the AT89C52 is executing code from external program memory, PSEN is activated twice each machine cycle, except that two PSEN activations are skipped during each access to external data memory.XTAL1Input to the inverting oscillator amplifier and input to the internal clock operating circuit.XTAL2Output from the inverting oscillator amplifier.Timer 2 RegistersControl and status bits are contained in registers T2CON and T2MOD for Timer 2. The register pair (RCAP2H, RCAP2L) are the Capture/Reload registers for Timer 2 in 16-bit capture mode or 16-bit auto-reload mode.Interrupt Registers4The individual interrupt enable bits are in the IE register. Two priorities can be set for each of the six interrupt sources in the IP register.5小型交通灯控制系统的设计与制作8位8字节闪存单片机AT89C52功能特性描述AT89S52是一种低功耗、高性能CMOS8位微控制器，具有8K内置可编程闪存。
智能交通信号灯设计毕业设计论文
毕业设计(论文)智能交通信号灯设计THE DESIGN OF INTELLGENT TRAFFICLIGHT毕业设计（论文）原创性声明和使用授权说明原创性声明本人郑重承诺：所呈交的毕业设计（论文），是我个人在指导教师的指导下进行的研究工作及取得的成果。
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单片机交通灯中英文对照外文翻译文献
中英文对照外文翻译原文DESIGN OF TRAFFIC LIGHT BASED ON MCUBecause of the rapid development of our economy resulting in the car number of large and medium-sized cities surged and the urban traffic, is facing serious test, leading to the traffic problem increasingly serious, its basically are behaved as follows: traffic accident frequency, to the human life safety enormous threat, Traffic congestion, resulting in serious travel time increases, energy consumption increase; Air pollution and noise pollution degree of deepening, etc. Daily traffic jams become people commonplace and had to endure. In this context, in combination with the actual situation of urban road traffic, develop truly suitable for our own characteristics of intelligent signal control system has become the main task.PrefaceIn practical application at home and abroad, according to the actual traffic signal control application inspection, planar independent intersection signal control basic using set cycle, much time set cycle, half induction, whole sensor etc in several ways. The former two control mode is completely based on planar intersection always traffic flow data of statistical investigation, due to traffic flow the existence of variable sex and randomicity, the two methods have traffic efficiency is low, the scheme, the defects of aging and half inductive and all the inductive the two methods are in the former two ways based on increased vehicle detector and according to the information provided to adjust cycle is long and green letter of vehicle, it than random arrived adaptability bigger, can make vehicles in the parking cord before as few parking, achieve traffic flowing effectIn modern industrial production,current,voltage,temperature, pressure, and flow rate, velocity, and switch quantity are common mainly controlled parameter. For example: in metallurgical industry, chemical production, power engineering, the papermaking industry, machinery and food processing and so on many domains, people need to transport the orderlycontrol. By single chip microcomputer to control of traffic, not only has the convenient control, configuration simple and flexible wait for an advantage, but also can greatly improve the technical index by control quantity, thus greatly improve product quality and quantity. Therefore, the monolithic integrated circuit to the traffic light control problem is an industrial production we often encounter problems.In the course of industrial production, there are many industries have lots of traffic equipment, in the current system, most of the traffic control signal is accomplished by relays, but relays response time is long, sensitivity low, long-term after use, fault opportunity increases greatly, and adopts single-chip microcomputer control, the accuracy of far greater than relays, short response time, software reliability, not because working time reduced its performance sake, compared with, this solution has the high feasibility.About AT89C511.function characteristics description:AT89C51 is a low power consumption, high performance CMOS8 bit micro-controller, has the 8K in system programmable Flash memory. Use high-density Atmel company the beltpassword nonvolatile storage technology and manufacturing, and industrial 80S51 product instructions and pin fully compatible. Chip Flash allow program memory in system programmable, also suitable for conventional programmer. In a single chip, have dexterous 8 bits CPU and in system programmable Flash, make AT89C51 for many embedded control application system provides the high flexible, super efficient solution. AT89C51 has the following standard function: 8k bytes Flash, 256 bytes RAM, 32-bit I/O mouth line, the watchdog timer, two data pointer, three 16 timer/counter, a 6 vector level 2 interrupt structure, full-duplex serial port, piece inside crystals timely clock circuit. In addition, AT89C51 can drop to 0Hz static logic operation, support two software can choose power saving mode. Idle mode, the CPU to stop working, allowing the RAM, timer/counter, serial ports, interruption continue to work. Power lost protection mode, RAM content being saved, has been frozen, microcontroller all work stop, until the next interruption or hardware reset so far. As shown in figure 1 for the AT89C51 pins allotment.Figure 1 the AT89C51 pins allotment2.interrupt introductionAT89C51 has six interrupt sources: two external interruption, (and), three timer interrupt (timer 0, 1, 2) and a serial interrupts. Each interrupt source can be passed buy bits or remove IE the relevant special register interrupt allow control bit respectively make effective or invalid interrupt source. IE also includes an interrupt allow total control bit EA, it can be a ban all interrupts. IE. Six is not available. For AT89C51, IE. 5 bits are also not be used. User software should not give these bits write 1. They AT89 series for new product reserved. Timer 2 can be TF2 and the T2CON registers EXF2 or logical triggered. Program into an interrupt service, the sign bit can be improved by hardware qing 0. In fact, the interrupt service routine must determine whether TF2 or EXF2 activation disruption, the sign bit must also by software qing 0. Timer 0 and 1 mark a timer TF0 and TF1 has been presented in the cycle count overflow S5P2 074 bits. Their value until the next cycle was circuit capture down. However, the timer 2 marks a TF2 in count overflow of the cycle of S2P2 074 bits, in the same cycle was circuit capture down3.external clock driving characteristicsTable 14.leisure and power lost pattern external pins stateTable 2About 8255 chip1.8255 features:(1)A parallel input/output LSI chips, efficacy of I/O devices, but as CPU bus and peripheral interface.(2)It has 24 programmable Settings of I/O mouth, even three groups of 8 bits I/O mouth to mouth, PB mouth and PA PC mouth. They are divided into two groups 12 I/O mouth, A group including port A and C mouth (high four, PC4 ~ PC7), including group B and C port B mouth (low four, PC0 ~ PC3). A group can be set to give basic I/O mouth, flash control (STROBE) I/O flash controlled, two-way I/O3 modes, Group B can only set to basic I/O or flash controlled the I/O, and these two modes of operation mode entirely by controlling registers control word decision.2. 8255 pins efficacy:(1). RESET: RESET input lines, when the input outside at high levels, all internal registers (including control registers) were removed, all I/O ports are denoting input methods.(2). CS: chip choose a standard lamp line 1, when the input pins for low levels, namely/CS = 0, said chip is selected, allow 8255 and CPU for communications, / CS = 1, 8255 cannot with CPU do data transmission.(3). RD: read a standard lamp line 1, when the input pins for low levels, namely/RD = 0 and/CS = 0, allow 8255 through the data bus to the CPU to send data or state information, namely the CPU 8255 read from the information or data.(4). The WR: write a standard lights, when the input pins for low levels, namely/WR = 0 and/CS = 0, allows the CPU will data or control word write 8255.(5). D7: three states D0 ~ two-way data bus, 8255 and CPU data transmission channel, when the CPU execution input/output instruction, through its realization 8 bits of data read/write operation, control characters and status information transmitted through the data bus.(6). PA0 ~ PA7: port A input and output lines, A 8 bits of data output latches/buffers, an 8 bits of data input latches.(7). PB0 ~ PB7: port B input and output lines, a 8 bits of I/O latches, an 8 bits of input and output buffer.(8). PC0 ~ PC7: port C input and output lines, a 8 bits of data output latches/buffers, an 8 bits of data input buffer. Port C can through the way of working setting into two four ports, every 4 digit port contains A 4 digit latches, respectively with the port A and port B cooperate to use, can be used as control standard lights output or state standard lights input ports.(9). A0, A1: address selection line, used to select the PA 8255 mouth, PB mouth, PC mouth and controlling registers.When A0=0, A1= 0, PA mouth be chosen;When A0=0, A1 = 1, PB mouth be chosen;When A0=0, A1 = 1, PC mouth be chosen;When A0=1, A1= 1, control register is selected.Concerning seven section LED display introductionThrough light emitting diode chip appropriate link (including series and parallel) andappropriate optical structure. May constitute a luminous display light-emitting segments or shine points. By these luminous segments or shine point can be composed digital tube, symbols tube, m word pipe, tube, multilevel matrix display tube etc. Usually the digital tube, symbols tube, m word tube were called stroke display, but the stroke displays and matrix tube collectively referred to as character displays.1. The LED display classification(1) by word high marks: stroke monitors word high least 1mm (monolithic integrated type more digital tube word high in commonly 2 ~ 3mm). Other types of stroke display tiptop1.27 mm (0.5 inch) even up to hundreds of mm.(2) color-coded score red, orange, yellow, green and several kinds.(3) according to the structure points, reflecting cover type, a single point-elastic and monolithic integrated type.(4) from the luminous section electrode connection mode of points of anode and cathode two kinds.2. LED display parametersDue to the LED display is LED based, so its light, and the electrical characteristics and ultimate meaning of the parameters with most of the same light emitting diode. But because the LED monitor containing multiple light emitting diode, it must has the following specific parameters:(1) the luminous intensity ratioDue to the digital tube paragraphs in the same driving voltage, each are not identical, so positive current each different. The luminous intensity All segments of the luminous intensity values the ratio of the maximum and minimum values for the luminous intensity ratio. The ratio between 2.3 in 1.5 ~, the maximum cannot exceed 2.5.(2) pulse positive currentIF each segment of typical strokes displays for positive dc working current IF, then the pulse, positive current can be far outweigh.someotherwordpeopledontthinkoffirst. Pulse 390v smaller, pulse positive current can be bigger.Traffic signal control typeThe purpose of the traffic signal control are three: first,in time and space space intersection traffic in different directions,control traffic operation order; Second, make onplanar cross the road network on the people and objects of transport at the highest efficiency, Third, as the road users to provide necessary information, and help them to effectively use the traffic facilities. Road traffic signal control of basic types have many points method.According to the control geometry characteristic is divided into: single intersection control - point control, the traffic trunk lines of coordinated control - wire, traffic network coordination control surface controlling; -- According to the control principle differentiates: timing control, induced control and adaptive control.About watch-dog circuitBy single-chip computers.the micro computer system, because of single chip work often can be affected by external electromagnetic interference, causing program run fly while into dead circulation, the program's normal operation be interrupted by single chip microcomputer control system was unable to work, can cause the whole system of come to a standstill, happen unpredictable consequences, so out of microcontroller running status real-time.according consideration, they generate a specially used for monitoring microcontroller program running state of the chip, commonly known as "watchdog" (watchdog).MAX692 was slightly system monitoring circuit chip, have back-up battery switching, power lost discriminant functions monitoring, the watchdog. The encapsulation and pin instructions as figure2shows.Figure 2 MAX692 encapsulation and pinsWatch-dog circuit application, make SCM can in no condition to achieve continuous work, its working principle is: the watchdog chip and MCU an I/O pins are linked together, the I/O pins through program control it regularly to the watchdog of the pins on into high level (or the low level), this program statement is scattered on SCM other control statements,once among single-chip due to the interference makes application run into a fly after the procedures section into dead circulation state, write the watchdog pins program cannot be executed, this time, the watch-dog circuit will be without microcontroller sent signals, then at it and MCU reset pin connected pin reset signal give out a a, make SCM reposition occurs, namely the program from program memory splittext started, so we realized the MCU automatic reset.Infrared detection circuitThe infrared radiation photon in semiconductor materials stimutes the non-equilibrium carriers (electronic or holes), cause electrical properties change. Because carrier does not escape in vitro, so called within the photoelectric effect. Quantum photoelectric effect high sensitivity, response speed heat detectors much faster, is optional detectors. In order to achieve the best performance, generally need worked in low temperature. Photoelectric detector can be divided into:(1) optical type: also called photoconductive resistance. The incident photon stimulate the valence band uniform semiconductor electronic across forbidden band into the conduction band and left in valence band, cause cavitation increases, for electric conductance eigen light conductivity. From the band gaps of impurity level also can stimulate light into the conduction band or born carriers valence band, and for impurities light conductivity. The cutoff wavelength by impurity ionization energy (ie) decision. Quantum efficiencies below eigen optical and require lower working temperature.(2) photovoltaic type: mainly p - n knot of light born volts effect. Energy more than the width of infrared photonic band gaps in "area and its nearby of electrons cavitation. Existing "electric field make hole into p area, electronic into n area, two parts appear potentials. Deoxidization device have voltage or current signal. Compared with optical detectors, pv detector detect rate more than forty percent of figure limit, Don't require additional bias electric field and load resistance, no power consumption, having a high impedance. These characteristics of preparation and use of the focal plane array bring great benefits.(3) light emitting - Schottky potential barrier detector: metal and semiconductor contact, typically include PtSi/Si structure and form was Schott potential barrier, infrared photon through Si layer for PtSi absorption, electronic Fermi level, obtain energy leap over left cavitation potential barrier into the Si substrate, PtSi layer of electronic was collected,complete infrared detection. Make full use of Si integration technology, facilitate production, with lower cost and good uniformity wait for an advantage, but make it mass (1024 x 1024 even greater) focal plane array to make up for the defect of quantum low efficiency. Have strict low temperature requirements. With this kind of detector, both at home and abroad has already produced as qualitative good thermography. Pt Si/Si structure made of FPA is the earliest IRFPA.Timing counting and traffic calculationUsing MCS - 51 internal timer/counter for timing, cooperate software delay realizes the timer. This method hardware cost saving, cut allows the reader in timer/counter use, disruptions and programming get exercise and improve. Computation formula is as follows: TC = M - CType in, M for counter touch value, the value and the counter working way concerned.For a traffic intersection, it can in the shortest possible time to achieve maximum traffic, even reached the best performance, we call in unit of time to achieve the maximum flow multi-energy for cars.Use the equation: (traffic = traffic/time) to represent.译文:基于单片机的交通灯设计我国经济快速发展，汽车数量猛增，大中型城市的城市交通正面临着严峻的考验，交通问题日益严重，其主要表现如下：交通事故频发，对人类生命安全造成极大威胁；交通拥堵严重，导致出行时间增加，能源消耗加大；空气污染和噪声污染程度日益加深等。
智能交通信号控制技术的研究与应用(英文中文双语版优质文档)
智能交通信号控制技术的研究与应用（英文中文双语版优质文档）Intelligent traffic signal control technology is a research based on artificial intelligence technology. It is mainly to solve the problem of road traffic congestion in modern cities, optimize the traffic signal system, reduce the incidence of traffic accidents, improve traffic efficiency, reduce energy consumption and environmental pollution .1. Research on Intelligent Traffic Signal Control TechnologyIntelligent traffic signal control technology mainly studies the optimal control of traffic flow and the control strategy of traffic lights. The traditional traffic signal control method adopts the timing control method. The main problem of this method is that it cannot adapt to the traffic flow changes in different time periods, and cannot realize the real sense of traffic optimization control. The intelligent traffic signal control technology uses artificial intelligence technology to realize the adaptive control of the traffic signal system through the analysis and processing of real-time traffic data, so as to realize the optimal control of traffic.The main research content of intelligent traffic signal control technology includes: real-time traffic flow monitoring based on intelligent transportation system, traffic flow prediction based on traffic simulation technology, signal control optimization algorithm based on traffic flow prediction, etc. Among them, real-time traffic flow monitoring based on intelligent transportation system is the basis of intelligent traffic signal control technology. Through collecting traffic data, traffic condition monitoring and data analysis, real-time monitoring and forecasting of traffic flow is realized. The traffic flow prediction based on traffic simulation technology is to predict the traffic flow by establishing a traffic simulation model, and provide traffic flow prediction data for the signal control system. The signal control optimization algorithm based on traffic flow prediction realizes the optimization of traffic signal control by optimizing the signal control strategy according to the forecast data.2. Application of intelligent traffic signal control technologyIntelligent traffic signal control technology has been widely used in many cities. For example, in Shenzhen, Shanghai, Guangzhou and other cities in China, intelligent traffic signal control technology has been widely used and achieved remarkable results. Among them, Shenzhen took the lead in promoting intelligent traffic signal control technology in 2009. Through real-time monitoring and prediction of traffic flow data, it realized adaptive control of traffic signals and effectively solved the problem of urban traffic congestion.In addition, there are many other application scenarios for intelligent traffic signal control technology. For example, in highways, airports, ports and other transportation hubs, through the monitoring and control of traffic flow, the smooth and efficient operation of traffic flow can be achieved, traffic efficiency can be improved, and the incidence of traffic accidents can be reduced. In the public transportation system, intelligent traffic signal control technology can also be applied to the control of bus priority and public bicycle lanes to provide more convenient services for public transportation.also be combined with other technologies, such as GPS positioning technology, vehicle identification technology, road monitoring technology, etc., to achieve more accurate traffic monitoring and signal control, and provide a more comprehensive solution for urban traffic management .3. Advantages and challenges of intelligent traffic signal control technologyadvantages over traditional traffic signal control technology. First of all, it can realize adaptive control of traffic signals, intelligently adjust according to real-time traffic data, and realize real traffic optimization control. Secondly, it can reduce the probability of traffic congestion and accidents, improve the efficiency of traffic operation, and reduce energy consumption and environmental pollution. In addition, intelligent traffic signal control technology can also be used in combination with other traffic management technologies to achieve more comprehensive and precise traffic management.However, intelligent traffic signal control technology also faces some challenges. First of all, it requires a large amount of data support and algorithm optimization, the establishment of a complete data collection and processing system, and the optimization and upgrading of intelligent algorithms. Secondly, its promotion and application need to fully consider the characteristics and actual conditions of urban traffic, and need to fully coordinate and cooperate with urban planning and traffic management departments. Finally, the safety and stability of intelligent traffic signal control technology also needs to be fully guaranteed to avoid traffic accidents and other problems caused by technical problems.4. Future OutlookWith the continuous development and application of artificial intelligence technology, intelligent traffic signal control technology will also be more widely used in the future. In the future, intelligent traffic signal control technology will pay more attention to the realization of traffic intelligence and automation, and use artificial intelligence technology and automatic driving technology to achieve more intelligent, efficient and safe urban traffic management. Specifically, the future intelligent traffic signal control technology will cover the development of the following aspects:1. The intelligence and adaptability of traffic signal control will be more perfect. With the continuous advancement of intelligent algorithms and data processing technologies, traffic signal control systems will become more intelligent, adaptive and flexible, able to more accurately predict and respond to changes in traffic flow, and achieve more efficient and precise traffic signal control.2. Intelligent traffic signal control technology will be integrated with other traffic management technologies to achieve more comprehensive and precise traffic management. In the future, intelligent traffic signal control technology will be used in combination with GPS positioning technology, vehicle identification technology, road monitoring technology and other traffic management technologies to achieve more accurate, comprehensive and efficient urban traffic management.3. Intelligent traffic signal control technology will be widely used in autonomous driving technology and intelligent transportation systems. With the development of autonomous driving technology, intelligent traffic signal control technology will be used in combination with autonomous driving technology to achieve more intelligent and automated urban traffic management. At the same time, intelligent traffic signal control technology will also be widely used in intelligent transportation systems to provide more comprehensive and efficient solutions for urban traffic management.In short, intelligent traffic signal control technology is an important technology in the field of urban traffic management, and has broad application prospects and development space. In the future, we have reason to believe that with the continuous innovation and progress of technology, intelligent traffic signal control technology will bring more extensive and far-reaching influence on urban traffic management and social development.智能交通信号控制技术是一项基于人工智能技术的研究，它主要是为了解决现代城市道路交通拥堵的问题，优化交通信号系统，减少交通事故的发生率，提高交通效率，降低能源消耗和环境污染。
城市智能交通灯系统_毕业设计论文
毕业论文（设计）题目：智能交通灯控制系统（Title）：Intelligent traffic light control system智能交通灯控制系统摘要本设计就是以单片机为架构的智能交通灯系统。
本系统由单片机系统、LED 显示、交通灯演示系统组成。
系统包括直行、左转、右转、以及基本的交通灯的功能。
系统除基本交通灯功能外，还具有倒计时、时间设置、紧急情况处理、分时段调整信号灯的点亮时间以及根据具体情况手动控制等功能。
目前的交通灯闪烁周期固定，导致上下班高峰期主干道路等待时间长。
本设计增加高峰期模式，进入高峰期时间段，通过调节闪烁时间缓解车流量大的道路压力。
同时还增加了交通灯系统的人行道盲人提示功能、急车紧急通过功能，可有效防止上下班时交通堵塞和车辆、人员滞留。
比起普通交通灯控制系统，此系统提高了交通灯控制的效率，保证交通有序进行。
关键词：AT89S52；交通灯；LED显示Intelligen traffic light control systemAbstractThis design is based on SCM for intelligent traffic light system architecture. This system consists of SCM system, LED display, traffic lights demonstration system. The system comprises a straight line, turn left, turn right, and the basic traffic lights function. In addition to the basic traffic lights function, also has the light time countdown, time setting, emergency handling, sub-period adjustment of signal and manual control functions according to the specific circumstances.At present, the traffic lights fixed period, resulting in the rush hour of trunk road to wait for a long time. Increase the peak pattern design, enter the peak period of time, by regulating the flashing time relieve the pressure large flow of car. At the same time also increased the traffic light system sidewalk blind prompt function, acute emergency vehicles through the function, can effectively prevent the commuting traffic and vehicles, staff retention. Compared with ordinary traffic light control system, the system improves the efficiency of traffic light control, ensure the orderly traffic.Key words: AT89S52；TRAFFIC LIGHT；LED DISPLAY目录一绪论 (1)1.1城市交通灯的作用 (1)1.2交通系统发展的现状 (2)1.3交通系统存在的问题 (3)1.4交通系统问题解决的途径 (4)1.5交通系统研究的主要内容 (5)二单片机控制交通系统总体设计 (6)2.1单片机交通控制系统通行方案设计 (6)2.2单片机交通控制系统的功能要求 (7)2.3单片机交通控制系统的显示界面方案 ............ 错误!未定义书签。
交通信号灯控制电路的设计外文翻译
附录4 外文资料Advantages of CDMA2000CDMA2000 benefited from the extensive experience acquired through several years of operation of cdmaOne systems. As a result, CDMA2000 is a very efficient and robust technology. It delivers the highest voice capacity and data throughput using the least amount of spectrum, and it can be used to provide services in urban as well as remote areas cost effectively.The unique features, benefits, and performance of CDMA2000 make it an excellent technology for high-voice capacity and high-speed packet data. Since CDMA2000 1X supports both voice and data services on the same carrier, it allows operators to provide both services cost efficiently. CDMA2000 1xEV-DO is optimized for data and is capable to support large volumes of data traffic at broadband speeds. 1xEV-DO is well suited to provide high-speed data services to its mobile subscribers and/or broadband access to the Internet.Due to its optimized radio technology, CDMA2000 enables operators to invest in fewer cell sites and deploy them faster, ultimately allowing the service providers to increase their revenues with faster Return On Investment (ROI).The CDMA2000 evolutionary path was designed to minimize investment and the impact to an operator’s network without service int erruption for the end-user. This has been achieved through backward and forward compatibility, hardware reuse, in-band migration and hybrid network configuration. This unique feature of CDMA2000 technologies has provided operators a significant time-to-market advantage over other 3G technologies.Increased Voice CapacityThe spectral efficiency of CDMA2000 1X permits high traffic deployments in a small amount (1.25 MHz channel) of spectrum. CDMA2000 1X can provide voicecapacity of nearly three times that of cdmaOne systems with Selectable Mode Vocoders (SMV) and antenna diversity techniques. CDMA2000 delivers 4-8 times higher voice capacity than TDMA-based technologies.CDMA2000 1X supports 35 traffic channels per sector per RF (26Erlangs/sector/RF) using the EVRC vocoder. Voice capacity improvement in the forward link is attributed to faster power control, lower code rates (1/4 rate), and transmit diversity (for single path Rayleigh fading). In the reverse link, capacity improvement is primarily due to coherent reverse link.For more information on CDMA2000 capacity click here.Higher Data ThroughputToday's commercial CDMA2000 1X networks support a peak data rate of 153 kbps (Rel. 0) or 307 kbps (Rel. 1). CDMA2000 1xEV-DO enables peak rates of up to 2.4 Mbps (Rev. 0) or 3.1 Mbps on the downlink, and 1.8 Mbps on the uplink (Rev A). 1xEV-DO networks deliver the highest data speeds commercially available today.Multicast ServicesWith the introduction of EV-DO Release 0 and followed by EV-DO Revisions A and B, operators have the ability to offer multicast services, “one to many” delivery, which allows transmitting the same information to an unlimited number of users without the need to rebroadcast the information multiple times. Multicast functionality offers significant advantages to operators and users.For operators, it allows a vast range of high-revenue generating services with minimum network resources at low cost. For the end-user, multicast services provide access to multimedia content, such as TV broadcasts, MP3 audio files, movies, etc., and a higher quality of services. For 1xEV-DO Rel 0, the multicast functionality is referred to as Gold Multicast and for 1xEV-DO Rev A it is called Platinum Multicast.Frequency Band FlexibilityCDMA2000 can be deployed in most cellular and PCS spectrum. CDMA2000 networks have already been deployed in the 450, 800, 1700, 1900 and 2100 MHz bands.Migration PathCDMA 2000 provides a direct migration path to 3G for first generation (1G) and second generation (2G) systems. CDMA2000 systems have been deployed by Greenfield, cdmaOne, TDMA and analog operators.For more information on migration to CDMA2000 click here.Serves Multiple MarketsCDMA2000 technologies support both fixed (Wireless Local Loop – WLL) and mobile services and can be used by operators to provide affordable voice services and broadband data access in urban, as well as remote areas, cost-effectively. While CDMA2000 technologies are mostly deployed by operators to offer mobile services, in many developing regions, i.e., Africa and South East Asia, CDMA2000 WLL technology is used to provide voice and data services to communities.Supports Multiple Service PlatformsCDMA2000 can be used with various operating systems (Palm and PocketPC), application platforms (JAVA and BREW), WAP, and emerging wireless technologies (WiFi and Push-to-Talk).Full backward compatibilityCDMA2000 is backward compatible with cdmaOne, and 1xEV-DO is backward compatible with both CDMA2000 1X and cdmaOne through multi-mode devices. Backward compatibility assures service transparency for the end user and smooth integration of 2G and 3G networks for the operator.Increased Battery LifeCDMA2000 significantly enhances battery performance. Benefits include:∙Quick paging channel operation∙Improved reverse link performance∙New common channel structure and operation∙Reverse link gated transmission∙New MAC states for efficient and ubiquitous idle time operation SynchronizationCDMA2000 is synchronized with the Universal Coordinated Time (UCT). The forward link transmission timing of all CDMA2000 base stations worldwide is synchronized within a few microseconds. Base station synchronization can be achieved through several techniques including self-synchronization, radio beep, or through satellite-based systems such as GPS, Galileo, or GLONASS. Reverse link timing is based on the received timing derived from the first multipath component used by the terminal.There are several benefits to having all base stations in a network synchronized:∙The common time reference improves acquisition of channels and hand-off procedures since there is no time ambiguity when looking for and addinga new cell in the active set.∙It also enables the system to operate some of the common channels in soft hand-off, which improves the efficiency of the common channel operation.∙Common network time reference allows implementation of very efficient "position location" techniques.Power ControlThe basic frame length is 20 ms divided into 16 equal power control groups. In addition, CDMA2000 defines a 5 ms frame structure, essentially to support signaling bursts, as well as 40 and 80 ms frames, which offer additional interleaving depth and diversity gains for data services. Unlike IS-95 where Fast Closed Loop Power Control was applied only to the reverse link, CDMA2000 channels can be power controlled at up to 800 Hz in both the reverse and forward links. The reverse link power control command bits are punctured into the F-FCH or the F-DCCH (explained in later sections) depending on the service configuration. The forward link power control command bits are punctured in the last quarter of the R-PICH power control slot.In the reverse link, during gated transmission, the power control rate is reduced to 400 or 200 Hz on both links. The reverse link power control sub-channel may also be divided into two independent power control streams, either both at 400 bps, or one at 200 bps and the other at 600 bps. This allows for independent power control of forward link channels.In addition to the closed loop power control, the power on the reverse link of CDMA2000 is also controlled through an Open Loop Power Control mechanism. This mechanism inverses the slow fading effect due to path loss and shadowing. It also acts as a safety fuse when the fast power control fails. When the forwardlink is lost, the closed loop reverse link power control is "freewheeling" and the terminal disruptively interferes with neighboring. In such a case, the open loop reduces the terminal output power and limits the impact to the system. Finally the Outer Loop Power drives the closed loop power control to the desired set point based on error statistics that it collects from the forward link or reverse link. Due to the expanded data rate range and various QoS requirements, different users will have different outer loop thresholds; thus, different users will receive different power levels at the base station. In the reverse link, CDMA2000 defines some nominal gain offsets based on various channel frame format and codingschemes. The remaining differences will be corrected by the outer loop itself.Soft Hand-offEven with dedicated channel operation, the terminal keeps searching for new cells as it moves across the network. In addition to the active set, neighbor set, and remaining set, the terminal also maintains a candidate set.When a terminal is traveling in a network, the pilot from a new BTS (P2) strength exceeds the minimum threshold TADD for addition in the active set. However, initially its relative contribution to the total received signal strength is not sufficient and the terminal moves P2 to the candidate set. The decision threshold for adding a new pilot to the active set is defined by a linear function of signal strength of the total active set. The network defines the slope and cross point of the function. When strength of P2 is detected to be above the dynamic threshold, the terminal signals this event to the network. The terminal then receives a hand-off direction message from the network requesting the addition of P2 in the active set. The terminal now operates in soft hand-off.The strength of serving BTS (P1) drops below the active set threshold, meaning P1 contribution to the total received signal strength does not justify the cost of transmitting P1. The terminal starts a hand-off drop timer. The timer expires and the terminal notifies the network that P1 dropped below the threshold. The terminal receives a hand-off message from the network moving P1 from the active set to the candidate set. Then P1 strength drops below TDROP and the terminal starts a hand-off drop timer, which expires after a set time. P1 is then moved from candidate set to neighbor set. This step-by-step procedure with multiple thresholds and timers ensures that the resource is only used when beneficial to the link and pilots are not constantly added and removed from the various lists, therefore limiting the associated signaling.附录5 外文资料译CDMA2000优点CDMA2000得到了广泛的业务经验,通过几年的cdmaOne系统. 因此,是一个非常有效的、强有力的CDMA2000技术. 它提供了最高的声音和数据能力使用量最少的频谱,它可以提供服务的城市以及偏远地区的成本效益. 独具特色的、效益、业绩优良的CDMA2000技术,使其高表达能力和高速数据包. 由于支持CDMA2000CDMA1X语音和数据服务,无论在同一载体,它使得经营者提供了有效的服务费用. CDMA20001xev,是优化数据,能支持大量数据流量的宽带速度. 1xev,是适合提供高速数据服务的移动用户和/或宽频上网. 由于无线电技术的优化,使经营CDMA2000投资少、部署地点细胞更快,最终使服务提供商增加其收入与投资回报快(港澳). CDMA2000的演进道路是为了减少投资和经营的影响,网络服务不中断的用户. 这是通过前后兼容性、硬件使用,波段移民和混合网络结构. 这一特点CDMA2000技术公司提供大量的时间和市场的优势,是其他3G技术.增加语音能力频谱效率高CDMA2000CDMA1X许可证部署少量交通(125兆赫频道)的频谱.CDMA2000CDMA1X可以提供语音能力近3倍cdmaOne系统五十九vocoders模式和天线多样性(SMV)技术. CDMA2000提供语音能力比4-8倍式基础技术. CDMA2000支持CDMA1X35元的交通渠道,每部门射频(26erlangs/界/RF)使用EVRCvocoder. 语音能力的提高与发展较快的原因是电力控制,降低税率法(1/4计算),将多样性(单路正在瑞利). 相反的联系,协调能力提高的主要原因是改变联系汇率制度. 更多信息CDMA2000能力按这里 . 高数据吞吐量今天的商业CDMA2000CDMA1X网络的数据传输率最高支持153千比特通信(0Rel.Rel.)、307千比特通信(1). CDMA20001xev小康,使最高税率达2.4Mbps(Rev0)或3.1mbps的下行,并在180Mbps上行(RevA). 1xev小康提供网络数据的速度最高可今天的商业.CDMA2000与cdmaOne落后,1xev,是符合落后两cdmaOne和CDMA2000CDMA1X通过多种方式的装置. 为保证兼容最终用户服务的透明度,并顺利地把3G网络的第二代服务营办商.提高电池的生活CDMA2000电池性能大大提高. 好处包括:∙传呼业务快速频道∙提高业绩扭转联系∙共同经营新格局∙扭转连接传输设∙新堡国家普遍闲置和高效运作同步CDMA2000与世界同步协调时间(UCT). 远期将传输时间是全世界所有CDMA2000基站同步数微米. 基地同步可以通过一些技术包括自营同步电台发出或通过卫星系统,如GPS、伽利略、GLONASS. 基于时间关系逆转何时收到来自第一部分多用码头. 有几个好处,在所有基站网同步:∙共同的时间和范围,改善采购渠道客手续时,因为没有地方,找一个新的细胞,并在积极制定.∙该系统还使一些经营渠道软手共同富裕,共同提高渠道运作效率.∙共同网执行时间允许范围非常有效"定位"技术.控制权基本框架的长度是20分16余平等权力控制集团. 此外,确定了5余CDMA2000结构框架,基本上是支持以讯号,以及40和80余架,提供更多的深度和多样性interleaving 收益数据服务. 不像-95快,是封闭性的控制权仅适用于反向连接,可CDMA2000渠道控制权高达800HZ,都改变了联系. 相反的指挥控制权将是穿透到位元 F-FCH 或者F-Dcch (后来解释部分)取决于配置服务. 前进指挥控制权将是位元刺穿在第四季R-PICH动力控制位置. 相反的联系,设在传输、电力控制率降至400或200HZ两环节. 反向连接控制权分管道也可以分为两个独立的电力控制流,不论是在400港元、200人,另在600个基点利率. 这允许独立的电力控制了联系渠道. 除了封闭性的权力控制、权力不放,倒也CDMA2000控制机制,通过开放性的控制权. 这一机制的作用逐渐缓慢inverses因道路跟踪和损失. 它作为一种安全又快速的导火索,没有控制权. 如果失去了联系,改变封闭性环节的控制权是"自由"与周边码头disruptively干扰. 在这种情况下,开放性降低终端限制输出功率及系统的影响. 终于在外封闭循环圈推动力量的控制权问题基于错误的预期数字,它收集了从连接或反向联系. 由于扩大了各种数据速率和QoS要求的各种不同的用户有不同的门槛外循环; 因此,不同的用户得到不同程度的电力基地. 相反的环节,明确了一些象征性收益用于CDMA2000基于各种形式和渠道,内码计划. 剩下的分歧会改正自己的外部环.软手客即使专用业务渠道,不断寻找新的终端细胞动作,因为这整个网络. 除了积极的、邻居的,剩下的,码头设有一组候选人. 当旅游网络终端,从一个新的输血服务中心试点(P2)Tadd实力超过最低限度的同时,积极制定. 然而,最初的相对贡献全部力量是不够的,接收到的信号和终端动作的P2确定候选人. 决定加入新起点,积极试行规定是指由直线职能积极信号总人数确定. 网络交叉点,把山坡的功能. 当发现P2实力将超过临界动态,对这一事件的网络信息终端. 码头,然后接到过指示,要求信息网络的同时,积极制定P2. 目前码头作业软手客. 输血服务中心的服务实力(P1)低于规定限额的活跃,即P1贡献力量并不完全接受信号为P1传输费用. 一开始,码头客落计时器. 计时器到期通知和终端网络P1降至最低. 最后,获得过信息网由P1积极推动订定的人选. P1实力则低于tdrop手踏上了码头和客落定时、定时间届满之后. 然后从P1邻居订定候选人. 这一步骤的界限,以多种定时器确保资源只用在有利于飞行员和联系不断增加,并没有排除各种名单,因此,相关限制信号.11。
智能交通中英文对照外文翻译文献
中英文对照外文翻译文献(文档含英文原文和中文翻译)智能交通的的设计由于我国经济的快速发展，导致大中型城市汽车数量激增，城市交通面临严峻的考验，导致交通问题增加，其主要表现为：交通事故频发，给人类生命安全造成巨大的威胁，造成严重的交通拥堵，出行时间增加，能源消费的增加；空气污染和噪声污染程度加深等，日常交通拥堵成为人们司空见惯而又不得不忍受。
在此背景下，结合实际情况城市道路交通，发展真正适合我们自己的特点的智能信号控制系统已成为主要任务。
前言在国内外实际应用中，根据实际交通信号控制的应用检验，平面独立的交叉口信号控制基本采用了定周期，多时间的设置周期，半感应，全传感器等几种方式。
前两者的控制模式是完全基于平面交叉口的交通流量数据的统计调查，由于交通流量的现在变性和随机性的存在，这两种方法具有交通效率低的缺陷，该方案，老化和半感应和感应两方法在前两种方式的基础上增加了车辆检测器，根据提供的信息来调整周期和车辆的绿色通道，它比随机到达的适应性大，可以使车辆在交通拥挤前先停车，实现对交通流量的影响。
在现代工业生产中，电流、电压、温度、压力、流量、速度、开关量等都是常用的主要被控参数。
例如：在冶金工业、化工药品的生产、电力工程、造纸行业、机械制造和食品加工等诸多领域，人们需要交通的有序控制。
通过单片机控制交通运输，不仅具有方便的控制、配置简单、灵活等优点，而且还可以通过控制量大幅度提高技术指标，从而大大提高了产品的质量和数量。
因此，单片集成电路的交通灯控制问题是一个工业生产中，我们经常遇到的问题。
在工业生产过程中，有很多行业有大量的交通设备，在目前的系统中，大部分的交通控制信号是通过继电器，而继电器的响应时间长、灵敏度低、长期使用后，故障的机会大大增加，相对于单片机控制，远大于继电器的精度、响应时间短，软件可靠性，不会因为工作时间的缘故而降低其性能，相比，该方案具有较高的可行性。
关于AT89C51（1）功能特点说明：AT89C51是一个低功耗，高性能CMOS8位微控制器，具有8K可编程Flash存储器。
交通信号智能控制系统外文文献及翻译
Agent controlled traffic lightsAuthor：Danko A. Roozemond，Jan L.H. RogierProvenance：Delft University of Technology IntroductionThe quality of (urban) traffic control systems is determined by the match between the control schema and the actual traffic patterns. If traffic patterns change, what they usually do, the effectiveness is determined by the way in which the system adapts to these changes. When this ability to adapt becomes an integral part of the traffic control unit it can react better to changes in traffic conditions. Adjusting a traffic control unit is a costly and timely affair if it involves human attention. The hypothesis is that it might offer additional benefit using self-evaluating and self-adjusting traffic control systems. There is already a market for an urban traffic control system that is able to react if the environment changes;the so called adaptive systems. "Real" adaptive systems will need pro-active calculated traffic information and cycle plans- based on these calculated traffic conditions- to be updated frequently.Our research of the usability of agent technology within traffic control can be split into two parts. First there is a theoretical part integrating agent technology and traffic control. The final stage of this research focuses on practical issues like implementation and performance. Here we present the concepts of agent technology applied to dynamic traffic control. Currently we are designing a layered model of an agent based urban traffic control system. We will elaborate on that in the last chapters.Adaptive urban traffic controlAdaptive signal control systems must have a capability to optimise the traffic flow by adjusting the traffic signals based on current traffic. All used traffic signal control methods are based on feed-back algorithms using traffic demand data -varying from years to a couple of minutes - in the past. Current adaptive systems often operate on the basis of adaptive green phases and flexible co-ordination in (sub)networks based on measured traffic conditions (e.g., UTOPIA-spot,SCOOT). These methods are still not optimal where traffic demand changes rapidly within a short time interval. The basic premise is that existing signal plan generation tools make rational decisions about signal plans under varying conditions; but almost none of the current available tools behave pro-actively or have meta-rules that may change behaviour of the controller incorporated into the system. The next logical step for traffic control is the inclusion of these meta-rules and pro active and goal-oriented behaviour. The key aspects of improved control, for which contributions from artificial intelligence and artificial intelligent agents can be expected, include the capability of dealing with conflicting objectives; the capability of making pro-active decisions on the basis of temporal analysis; the ability of managing, learning, self adjusting and responding to non-recurrent and unexpected events (Ambrosino et al.., 1994).What are intelligent agentsAgent technology is a new concept within the artificial intelligence (AI). The agent paradigm in AI is based upon the notion of reactive, autonomous, internally-motivated entities that inhabit dynamic, not necessarily fully predictable environments (Weiss, 1999). Autonomy is the ability to function as an independent unit over an extended period of time, performing a variety of actions necessary to achieve pre-designated objectives while responding to stimuli produced by integrally contained sensors (Ziegler, 1990). Multi-Agent Systems can be characterised by the interaction of many agents trying to solve a variety of problems in a co-operative fashion. Besides AI, intelligent agents should have some additional attributes to solve problems by itself in real-time; understand information; have goals and intentions; draw distinctions between situations; generalise; synthesise new concepts and / or ideas; model the world they operate in and plan and predict consequences of actions and evaluate alternatives. The problem solving component of an intelligent agent can be a rule-based system but can also be a neural network or a fuzzy expert system. It may be obvious that finding a feasible solution is a necessity for an agent. Often local optima in decentralised systems, are not the global optimum. This problem is not easily solved. The solution has to be found by tailoring the interaction mechanism or to have a supervising agent co-ordinating the optimisation process of the other agents. Intelligent agents in UTC,a helpful paradigmAgent technology is applicable in different fields within UTC. The ones most important mentioning are: information agents, agents for traffic simulation and traffic control. Currently, most applications of intelligent agents are information agents. They collect information via a network. With special designed agents user specific information can be provided. In urban traffic these intelligent agents are useable in delivering information about weather, traffic jams, public transport, route closures, best routes, etc. to the user via a Personal Travel Assistant. Agent technology can also be used for aggregating data for further distribution. Agents and multi agent systems are capable of simulating complex systems for traffic simulation. These systems often use one agent for every traffic participant (in a similar way as object oriented programs often use objects). The application of agents in (Urban) Traffic Control is the one that has our prime interest. Here we ultimately want to use agents for pro-active traffic light control with on-line optimisation. Signal plans then will be determined based on predicted and measured detector data and will be tuned with adjoining agents. The most promising aspects of agent technology, the flexibility and pro-active behaviour, give UTC the possibility of better anticipation of traffic. Current UTC is not that flexible, it is unable to adjust itself if situations change and can't handle un-programmed situations. Agent technology can also be implemented on several different control layers. This gives the advantage of being close to current UTC while leaving considerable freedom at the lower (intersection) level. Designing agent based urban traffic control systemsThe ideal system that we strive for is a traffic control system that is based on actuated traffic controllers and is able to pro actively handle traffic situations and handling the different, sometimes conflicting, aims of traffic controllers. The proposed use of the concept of agents in this research is experimental.Assumptions and considerations on agent based urban traffic controlThere are three aspects where agent based traffic control and -management can improve current state of the art UTC systems:- Adaptability. Intelligent agents are able to adapt its behaviour and can learn from earlier situations.- Communication. Communication makes it possible for agents to co-operate and tune signal plans.- Pro-active behaviour. Due to the pro active behaviour traffic control systems are able to plan ahead.To be acceptable as replacement unit for current traffic control units, the system should perform the same or better than current systems. The agent based UTC will require on-line and pro-active reaction on changing traffic patterns. An agent based UTC should be demand responsive as well as adaptive during all stages and times. New methods for traffic control and traffic prediction should be developed as current ones do not suffice and cannot be used in agent technology. The adaptability can also be divided in several different time scales where the system may need to handle in a different way (Rogier, 1999):- gradual changes due to changing traffic volumes over a longer period of time,- abrupt changes due to changing traffic volumes over a longer period of time,- abrupt, temporal, changes due to changing traffic volumes over a short period of time,- abrupt, temporal, changes due to prioritised traffic over a short period of time One way of handling the balance between performance and complexity is the use of a hierarchical system layout. We propose a hierarchy of agents where every agent is responsible for its own optimal solution, but may not only be influenced by adjoining agents but also via higher level agents. These agents have the task of solving conflicts between lower level agents that they can't solve. This represents current traffic control implementations and idea's. One final aspect to be mentioned is the robustness of agent based systems (if all communication fails the agent runs on, if the agent fails a fixed program can be executed.To be able to keep our first urban traffic control model as simple as possible we have made the following assumptions: we limit ourselves to inner city traffic control (road segments, intersections, corridors), we handle only controlled intersections with detectors (intensity and speed) at all road segments, we only handle cars and we use simple rule bases for knowledge representation.Types of agents in urban intersection controlAs we divide the system in several, recognisable, parts we define the following 4 types of agents:- Roads are represented by special road segment agents (RSA),- Controlled intersections are represented by intersection agents (ITSA),- For specific, defined, areas there is an area agent (higher level),- For specific routes there can be route agents, that spans several adjoining road segments (higher level).We have not chosen for one agent per signal. This may result in a more simple solution but available traffic control programs do not fit in that kind of agent. We deliberately choose a more complex agent to be able to use standard traffic control design algorithms and programs. The idea still is the optimisation on a local level (intersection), but with local and global control. Therefor we use area agents and route agents. All communication takes place between neighbouring agents and upper and lower level ones.Design of our agent based systemThe essence of a, demand responsive and pro-active agent based UTC consists of several ITSA's (InTerSection Agent).,some authority agents (area and route agents) and optional Road Segment Agents (RSA). The ITSA makes decisions on how to control its intersection based on its goals, capability, knowledge, perception and data. When necessary an agent can request for additional information or receive other goals or orders from its authority agent(s).For a specific ITSA, implemented to serve as an urban traffic control agent, the following actions are incorporated (Roozemond, 1998):- data collection / distribution (via RSA - information on the current state of traffic; from / to other ITSA's - on other adjoining signalised intersections);- analysis (with an accurate model of the surrounds and knowing the traffic and traffic control rules define current trend; detect current traffic problems);- calculation (calculate the next, optimal, cycle mathematically correct);- decision making (with other agent deciding what to use for next cycle; handle current traffic problems);- control (operate the signals according to cycle plan).In figure 1 a more specific example of a simplified, agent based, UTC system is given. Here we have a route agent controlling several intersection agents, which in turn manage their intersection controls helped by RSA's. The ITSA is the agent that controls and operates one specific intersection of which it is completely informed. All ITSA's have direct communication with neighbouring ITSA's, RSA's and all its traffic lights. Here we use the agent technology to implement a distributed planning algorit hm. The route agents’ tasks are controlling, co-ordinating and leading the ITSA’s towards a more global optimum. Using all available information the ITSA (re)calculates the next, most optimal, states and control strategy and operates the traffic signals accordingly. The ITSA can directly influence the control strategy of their intersection(s) and is able to get insight into on-coming trafficThe internals of the ITSA modelTraffic dependent intersection control normally works in a fast loop. The detectordata is fed into the control algorithm. Based upon predetermined rules a control strategy is chosen and the signals are operated accordingly. In this research we suggest the introduction of an extra, slow, loop where rules and parameters of a prediction- model can be changed by a higher order meta-model.ITSA modelThe internals of an ITSA consists of several agents. For a better overview of the internal ITSA model-agents and agent based functions see figure 2. Data collection is partly placed at the RSA's and partly placed in the ITSA's. The needed data is collected from different sources, but mainly via detectors. The data is stored locally and may be transmitted to other agents. The actual operation of the traffic signals is left to an ITSA-controller agent. The central part of the ITSA, acts as a control strategy agent. That agent can operate several control strategies, such as anti-blocking and public transport priority strategies. The control strategy agent uses the estimates of the prediction model agent which estimates the states in the near future. The ITSA-prediction model agent estimates the states in the near future. The prediction model agent gets its data related to intersection and road segments - as an agent that ‘knows’ the forecasting equations, actual traffic conditions and constraints - and future traffic situations can be calculated by way of an inference engine and it’s knowledge and data base. On-line optimisation only works if there is sufficient quality in traffic predictions, a good choice is made regarding the performance indicators and an effective way is found to handle one-time occurrences (Rogier, 1999).Prediction modelWe hope to include pro-activeness via specific prediction model agents with a task of predicting future traffic conditions. The prediction models are extremely important for the development of pro active traffic control. The proposed ITSA-prediction model agent estimates the states of the traffic in the near future via its own prediction model. The prediction meta-model compares the accuracy of the predictions with current traffic and will adjust the prediction parameters if the predictions were insufficient or not accurate. The prediction model agent is fed by several inputs: vehicle detection system, relevant road conditions, control strategies, important data on this intersection and its traffic condition, communication with ITSA’s of nearby intersections and higher level agents. The agent itself has a rule-base, forecasting equations, knows constraints regarding specific intersections and gets insight into current (traffic) conditions. With these data future traffic situations should be calculated by its internal traffic forecasting model. The predicted forecast is valid for a limited time. Research has shown that models using historic, up-stream and current link traffic give the best results (Hobeika & Kim, 1994).Control strategy modelThe prediction of the prediction model is used in the control strategy planning phase. We have also included a performance indicating agent, necessary to update thecontrol parameters in the slower loop. The control strategy agent uses the estimates of the prediction model agent to calculate the most optimal control strategy to pro-act on the forecasts of the prediction model agent, checks with other adjoining agents its proposed traffic control schema and then plans the signal control strategy The communication schema is based on direct agent to agent communication via a network link. The needed negotiation finds place via a direct link and should take the global perspective into consideration. Specific negotiation rules still have to be developed. Some traffic regulation rules and data has to be fed into the system initially. Data on average flow on the links is gained by the system during run-time. In the near future computer based programs will be able to do, parts of, these kind of calculus automatically. For real-time control the same basic computer programs, with some artificial knowledge, will be used. Detectors are needed to give information about queues and number of vehicles. The arrival times can also be given by the RSA so that green on demand is automatically covered.Conclusions and future workAdaptive signal control systems that are able to optimise and adjust the signal settings are able to improve the vehicular throughput and minimise delay through appropriate response to changes in the measured demand patterns. With the introduction of two un-coupled feed back loops, whether agent technology is used or not, a pro-active theory of traffic control can be met. There are several aspects still unresearched. The first thing we are going to do is to build a prototype system of a single intersection to see if the given claims of adaptability and pro activeness can be realised. A working prototype of such system should give appropriate evidence on the usability of agent based control systems. There are three other major subjects to be researched in depth; namely self adjustable control schema's, on-line optimisation of complex systems and getting good prediction models. For urban traffic control we need to develop self adjustable control schemes that can deal with dynamic and actuated data. For the optimisation we need mathematical programming methodologies capable of real-time on-line operation. In arterial and agent based systems this subject becomes complex due to several different, continuously changing, weights and different goals of the different ITSA's and due to the need for co-ordination and synchronisation. The research towards realising real-time on-line prediction models needs to be developed in compliance with agent based technology. The pro-active and re-active nature of agents and the double loop control schema seems to be a helpful paradigm in intelligent traffic management and control. Further research and simulated tests on a control strategy, based on intelligent autonomous agents, is necessary to provide appropriate evidence on the usability of agent-based control systems.代理控制交通灯作者：Danko A. Roozemond，Jan L.H. Rogier出处：Delft University of Technology前言（城市）交通控制系统的好坏决定于系统控制模式和实际交通流量模式是否相符。
交通信号智能控制系统外文文献及翻译.doc
Agent controlled traffic lightsAuthor：Danko A. Roozemond，Jan L.H. RogierProvenance：Delft University of Technology IntroductionThe quality of (urban) traffic control systems is determined by the match between the control schema and the actual traffic patterns. If traffic patterns change, what they usually do, the effectiveness is determined by the way in which the system adapts to these changes. When this ability to adapt becomes an integral part of the traffic control unit it can react better to changes in traffic conditions. Adjusting a traffic control unit is a costly and timely affair if it involves human attention. The hypothesis is that it might offer additional benefit using self-evaluating and self-adjusting traffic control systems. There is already a market for an urban traffic control system that is able to react if the environment changes;the so called adaptive systems. "Real" adaptive systems will need pro-active calculated traffic information and cycle plans- based on these calculated traffic conditions- to be updated frequently.Our research of the usability of agent technology within traffic control can be split into two parts. First there is a theoretical part integrating agent technology and traffic control. The final stage of this research focuses on practical issues like implementation and performance. Here we present the concepts of agent technology applied to dynamic traffic control. Currently we are designing a layered model of an agent based urban traffic control system. We will elaborate on that in the last chapters.Adaptive urban traffic controlAdaptive signal control systems must have a capability to optimise the traffic flow by adjusting the traffic signals based on current traffic. All used traffic signal control methods are based on feed-back algorithms using traffic demand data -varying from years to a couple of minutes - in the past. Current adaptive systems often operate on the basis of adaptive green phases and flexible co-ordination in (sub)networks based on measured traffic conditions (e.g., UTOPIA-spot,SCOOT). These methods are still not optimal where traffic demand changes rapidly within a short time interval. The basic premise is that existing signal plan generation tools make rational decisions about signal plans under varying conditions; but almost none of the current available tools behave pro-actively or have meta-rules that may change behaviour of the controller incorporated into the system. The next logical step for traffic control is the inclusion of these meta-rules and pro active and goal-oriented behaviour. The key aspects of improved control, for which contributions from artificial intelligence and artificial intelligent agents can be expected, include the capability of dealing with conflicting objectives; the capability of making pro-active decisions on the basis of temporal analysis; the ability of managing, learning, self adjusting and responding to non-recurrent and unexpected events (Ambrosino et al.., 1994).What are intelligent agentsAgent technology is a new concept within the artificial intelligence (AI). The agent paradigm in AI is based upon the notion of reactive, autonomous, internally-motivated entities that inhabit dynamic, not necessarily fully predictable environments (Weiss, 1999). Autonomy is the ability to function as an independent unit over an extended period of time, performing a variety of actions necessary to achieve pre-designated objectives while responding to stimuli produced by integrally contained sensors (Ziegler, 1990). Multi-Agent Systems can be characterised by the interaction of many agents trying to solve a variety of problems in a co-operative fashion. Besides AI, intelligent agents should have some additional attributes to solve problems by itself in real-time; understand information; have goals and intentions; draw distinctions between situations; generalise; synthesise new concepts and / or ideas; model the world they operate in and plan and predict consequences of actions and evaluate alternatives. The problem solving component of an intelligent agent can be a rule-based system but can also be a neural network or a fuzzy expert system. It may be obvious that finding a feasible solution is a necessity for an agent. Often local optima in decentralised systems, are not the global optimum. This problem is not easily solved. The solution has to be found by tailoring the interaction mechanism or to have a supervising agent co-ordinating the optimisation process of the other agents. Intelligent agents in UTC,a helpful paradigmAgent technology is applicable in different fields within UTC. The ones most important mentioning are: information agents, agents for traffic simulation and traffic control. Currently, most applications of intelligent agents are information agents. They collect information via a network. With special designed agents user specific information can be provided. In urban traffic these intelligent agents are useable in delivering information about weather, traffic jams, public transport, route closures, best routes, etc. to the user via a Personal Travel Assistant. Agent technology can also be used for aggregating data for further distribution. Agents and multi agent systems are capable of simulating complex systems for traffic simulation. These systems often use one agent for every traffic participant (in a similar way as object oriented programs often use objects). The application of agents in (Urban) Traffic Control is the one that has our prime interest. Here we ultimately want to use agents for pro-active traffic light control with on-line optimisation. Signal plans then will be determined based on predicted and measured detector data and will be tuned with adjoining agents. The most promising aspects of agent technology, the flexibility and pro-active behaviour, give UTC the possibility of better anticipation of traffic. Current UTC is not that flexible, it is unable to adjust itself if situations change and can't handle un-programmed situations. Agent technology can also be implemented on several different control layers. This gives the advantage of being close to current UTC while leaving considerable freedom at the lower (intersection) level. Designing agent based urban traffic control systemsThe ideal system that we strive for is a traffic control system that is based on actuated traffic controllers and is able to pro actively handle traffic situations and handling the different, sometimes conflicting, aims of traffic controllers. The proposed use of the concept of agents in this research is experimental.Assumptions and considerations on agent based urban traffic controlThere are three aspects where agent based traffic control and -management can improve current state of the art UTC systems:- Adaptability. Intelligent agents are able to adapt its behaviour and can learn from earlier situations.- Communication. Communication makes it possible for agents to co-operate and tune signal plans.- Pro-active behaviour. Due to the pro active behaviour traffic control systems are able to plan ahead.To be acceptable as replacement unit for current traffic control units, the system should perform the same or better than current systems. The agent based UTC will require on-line and pro-active reaction on changing traffic patterns. An agent based UTC should be demand responsive as well as adaptive during all stages and times. New methods for traffic control and traffic prediction should be developed as current ones do not suffice and cannot be used in agent technology. The adaptability can also be divided in several different time scales where the system may need to handle in a different way (Rogier, 1999):- gradual changes due to changing traffic volumes over a longer period of time,- abrupt changes due to changing traffic volumes over a longer period of time,- abrupt, temporal, changes due to changing traffic volumes over a short period of time,- abrupt, temporal, changes due to prioritised traffic over a short period of time One way of handling the balance between performance and complexity is the use of a hierarchical system layout. We propose a hierarchy of agents where every agent is responsible for its own optimal solution, but may not only be influenced by adjoining agents but also via higher level agents. These agents have the task of solving conflicts between lower level agents that they can't solve. This represents current traffic control implementations and idea's. One final aspect to be mentioned is the robustness of agent based systems (if all communication fails the agent runs on, if the agent fails a fixed program can be executed.To be able to keep our first urban traffic control model as simple as possible we have made the following assumptions: we limit ourselves to inner city traffic control (road segments, intersections, corridors), we handle only controlled intersections with detectors (intensity and speed) at all road segments, we only handle cars and we use simple rule bases for knowledge representation.Types of agents in urban intersection controlAs we divide the system in several, recognisable, parts we define the following 4 types of agents:- Roads are represented by special road segment agents (RSA),- Controlled intersections are represented by intersection agents (ITSA),- For specific, defined, areas there is an area agent (higher level),- For specific routes there can be route agents, that spans several adjoining road segments (higher level).We have not chosen for one agent per signal. This may result in a more simple solution but available traffic control programs do not fit in that kind of agent. We deliberately choose a more complex agent to be able to use standard traffic control design algorithms and programs. The idea still is the optimisation on a local level (intersection), but with local and global control. Therefor we use area agents and route agents. All communication takes place between neighbouring agents and upper and lower level ones.Design of our agent based systemThe essence of a, demand responsive and pro-active agent based UTC consists of several ITSA's (InTerSection Agent).,some authority agents (area and route agents) and optional Road Segment Agents (RSA). The ITSA makes decisions on how to control its intersection based on its goals, capability, knowledge, perception and data. When necessary an agent can request for additional information or receive other goals or orders from its authority agent(s).For a specific ITSA, implemented to serve as an urban traffic control agent, the following actions are incorporated (Roozemond, 1998):- data collection / distribution (via RSA - information on the current state of traffic; from / to other ITSA's - on other adjoining signalised intersections);- analysis (with an accurate model of the surrounds and knowing the traffic and traffic control rules define current trend; detect current traffic problems);- calculation (calculate the next, optimal, cycle mathematically correct);- decision making (with other agent deciding what to use for next cycle; handle current traffic problems);- control (operate the signals according to cycle plan).In figure 1 a more specific example of a simplified, agent based, UTC system is given. Here we have a route agent controlling several intersection agents, which in turn manage their intersection controls helped by RSA's. The ITSA is the agent that controls and operates one specific intersection of which it is completely informed. All ITSA's have direct communication with neighbouring ITSA's, RSA's and all its traffic lights. Here we use the agent technology to implement a distributed planning algori thm. The route agents’ tasks are controlling, co-ordinating and leading the ITSA’s towards a more global optimum. Using all available information the ITSA (re)calculates the next, most optimal, states and control strategy and operates the traffic signals accordingly. The ITSA can directly influence the control strategy of their intersection(s) and is able to get insight into on-coming trafficThe internals of the ITSA modelTraffic dependent intersection control normally works in a fast loop. The detectordata is fed into the control algorithm. Based upon predetermined rules a control strategy is chosen and the signals are operated accordingly. In this research we suggest the introduction of an extra, slow, loop where rules and parameters of a prediction- model can be changed by a higher order meta-model.ITSA modelThe internals of an ITSA consists of several agents. For a better overview of the internal ITSA model-agents and agent based functions see figure 2. Data collection is partly placed at the RSA's and partly placed in the ITSA's. The needed data is collected from different sources, but mainly via detectors. The data is stored locally and may be transmitted to other agents. The actual operation of the traffic signals is left to an ITSA-controller agent. The central part of the ITSA, acts as a control strategy agent. That agent can operate several control strategies, such as anti-blocking and public transport priority strategies. The control strategy agent uses the estimates of the prediction model agent which estimates the states in the near future. The ITSA-prediction model agent estimates the states in the near future. The prediction model agent gets its data related to intersection and road segments - as an agent that ‘knows’ the forecasting equation s, actual traffic conditions and constraints - and future traffic situations can be calculated by way of an inference engine and it’s knowledge and data base. On-line optimisation only works if there is sufficient quality in traffic predictions, a good choice is made regarding the performance indicators and an effective way is found to handle one-time occurrences (Rogier, 1999).Prediction modelWe hope to include pro-activeness via specific prediction model agents with a task of predicting future traffic conditions. The prediction models are extremely important for the development of pro active traffic control. The proposed ITSA-prediction model agent estimates the states of the traffic in the near future via its own prediction model. The prediction meta-model compares the accuracy of the predictions with current traffic and will adjust the prediction parameters if the predictions were insufficient or not accurate. The prediction model agent is fed by several inputs: vehicle detection system, relevant road conditions, control strategies, important data on this intersection and its traffic condition, communication with ITSA’s of nearby intersections and higher level agents. The agent itself has a rule-base, forecasting equations, knows constraints regarding specific intersections and gets insight into current (traffic) conditions. With these data future traffic situations should be calculated by its internal traffic forecasting model. The predicted forecast is valid for a limited time. Research has shown that models using historic, up-stream and current link traffic give the best results (Hobeika & Kim, 1994).Control strategy modelThe prediction of the prediction model is used in the control strategy planning phase. We have also included a performance indicating agent, necessary to update thecontrol parameters in the slower loop. The control strategy agent uses the estimates of the prediction model agent to calculate the most optimal control strategy to pro-act on the forecasts of the prediction model agent, checks with other adjoining agents its proposed traffic control schema and then plans the signal control strategy The communication schema is based on direct agent to agent communication via a network link. The needed negotiation finds place via a direct link and should take the global perspective into consideration. Specific negotiation rules still have to be developed. Some traffic regulation rules and data has to be fed into the system initially. Data on average flow on the links is gained by the system during run-time. In the near future computer based programs will be able to do, parts of, these kind of calculus automatically. For real-time control the same basic computer programs, with some artificial knowledge, will be used. Detectors are needed to give information about queues and number of vehicles. The arrival times can also be given by the RSA so that green on demand is automatically covered.Conclusions and future workAdaptive signal control systems that are able to optimise and adjust the signal settings are able to improve the vehicular throughput and minimise delay through appropriate response to changes in the measured demand patterns. With the introduction of two un-coupled feed back loops, whether agent technology is used or not, a pro-active theory of traffic control can be met. There are several aspects still unresearched. The first thing we are going to do is to build a prototype system of a single intersection to see if the given claims of adaptability and pro activeness can be realised. A working prototype of such system should give appropriate evidence on the usability of agent based control systems. There are three other major subjects to be researched in depth; namely self adjustable control schema's, on-line optimisation of complex systems and getting good prediction models. For urban traffic control we need to develop self adjustable control schemes that can deal with dynamic and actuated data. For the optimisation we need mathematical programming methodologies capable of real-time on-line operation. In arterial and agent based systems this subject becomes complex due to several different, continuously changing, weights and different goals of the different ITSA's and due to the need for co-ordination and synchronisation. The research towards realising real-time on-line prediction models needs to be developed in compliance with agent based technology. The pro-active and re-active nature of agents and the double loop control schema seems to be a helpful paradigm in intelligent traffic management and control. Further research and simulated tests on a control strategy, based on intelligent autonomous agents, is necessary to provide appropriate evidence on the usability of agent-based control systems.代理控制交通灯作者：Danko A. Roozemond，Jan L.H. Rogier出处：Delft University of Technology前言（城市）交通控制系统的好坏决定于系统控制模式和实际交通流量模式是否相符。
单片机智能路灯中英文对照外文翻译文献
单片机智能路灯中英文对照外文翻译文献单片机智能路灯中英文对照外文翻译文献(文档含英文原文和中文翻译)Based on single chip microcomputer intelligent street lightcontrol system【abstract 】 A street light automatic control system design, combined with the control, electric lamp switch control function; And street lamp fault detection and fault street lamp according to the function of the number. Use on STC 89C51 as the core Control unit; Using DS1302 clock chip to control the point open to turn off the lights when street lamps; By a photosensor complete collection of ambient light and street light fault detection, so as to realize the number of optically controlled open to turn off the lights and fault street lamp display. This system Can through the RS - 232 communication port with the street light control room of the upper machine communication.【key words】STC 89C51; Clock chip DS1302; photosensorIntroductionFor the most part at present domestic cities and regions of the street lamp Lighting adopts electric control, time control and single point of electrons Control, maintenance management and manual inspections and the masses The traditional way, because of the lack of scientific and effective monitoring Means, large area lighting during the day, night not large area Light phenomenon occurs frequently, often can't find and in a timely manner Processing, not only caused power resources, human resources Cost, improve the operating costs of the system and to citizens Life bring inconvenience.Intelligent road lighting system can according to different area Domain of different functional requirements, at different times and different every day Natural light or under different traffic flow conditions, the press According to a specific setting, realize dynamic wisdom of road lighting Can management, namely the TPO management (TIME/PLACE, TIME Location/OCCASION occasions). Intelligent road lighting Control system, through the comprehensive consideration and analysis and road Ming is closely related to the intensity of illumination time, road, environment and hand it in Scene control methods of factors such as flow rate, in themicrocomputer According to the preset control strategy, the road lighting into action Street lamp intelligent management and control in different conditions normally In different states implement diversified road lighting scene, To improve the quality of lighting at the same time get the best section Can effect.1. The system hardware designControl circuit mainly to light, temperature signal acquisition, data computing and analysis, and control of street lamp driver circuit according to the results of the operation. Circuit must have MD conversion function, adopt STCl2C5608AD single chip microcomputer as control unit, the single-chip computer as a single clock cycle enhanced 8051 kernel microcontroller, it contains 8 KB FLASH program memory, eight road lO MD conversion interface, can meet the need of data acquisition. Light intensity, temperature sensor using photosensitive resistance and thermal resistance,respectively.Figure 1Figure 2Photosensitive resistor Rx and resistance R2 bleeder circuit, light intensity changes, microcontroller P1.7 pin input voltage changes, and P1.7 pin can be set up for MD conversion interface, set a threshold voltage for light intensity can distinguish between day and night. Thermal resistor Rx and R3 bleeder circuit, the temperature changes, P1.5 pin voltage change, the figure 1 watch NA L/D conversion control circuit green quality can calculate the actual environment temperature and time control to modify parameters. S1 for four dial the code switch, can be used to think.1.1 hardware designSystem hardware modules include: control module, mining Use 89 c51 to realize on STC; Sensor module, Using photosensitive resistance on the surrounding environment light Sample, using photosensitive diode on-off to street lamp equipment Obstacle detection; The clock module, using DS1302 clock chip Slice; Display module, which is made up of four LED digital tube, use To display the fault street lamp number; Sound and light alarm module, Implementation of malfunctioning of the street lamp light hint; Communication moduleBlocks, used to transmit commands from PC.1.2 module functionOn STC 89 c51 based on DS1302 clock chip Provide the clock signal, according to the following time implementation control Turn off the lights.(1) : winter time 18:00 lights at night, The next morning at 7:30 to turn off the lights.(2) age season time: the evening number is turn on the light, The next morning at 6:30 to turn off the lights.(3) in the summer time: 20:00 lights at night, The next morning at 5:30 to turn off the lights.Dynamically changes of this period of time, changes in the operation A machine to complete, through the communication module will hold instructions written to STC 89 c51 chip, then changed the point open to turn off the lights During work time.Photosensitive resistance, by appropriate wavelength of light , the current will along with the increase of light intensity, thus Realize the photoelectric conversion. To die by ADC0832 device Hold number converted to provide single-chip, STC 89c51 according to The default program realize the electric lamp switch function.(1) automatic metering, during the day (or light) When lights go out, night (dark or light) street lights automatically Light up.(2) the sensitivity is adjustable, can adjust according to need Any work under the light.(3) to prevent the instant bright light interference, the AD hoc Delay off function (to strong light, the light switch When 30 seconds to shut down automatically).Photosensitive diode is to use silicon PN knot when the light is produced A photoelectric device, light current work in reverse bias Because of the pressure. During the day light or lamp light photosensitive 2 directly Diode reverse resistance decreases, and diode conduction; Light is very Hours photosensitive diode reverse resistance increases, the diode The check. Using photosensitive diode, detection of street lamp is night Normal work. When the photosensitive diode as shows that street lamp Equipment failure or theft, acousto-optic quote on STC 89 c51 started Alarm device, at the same time in four LED digital tube display the corresponding The street number.2.The system software designThe software design of this system is divided into seven parts, mainly Including the LED digital tube display program design; Light to check the Test program design; Equipment fault detection program design; when Clock driver chip design; Open to turn off the lights program design; Communication program design; Audible and visual alarm program design, etc.Software includes: main program, system initialization, anti-fuzzy functions,A/D conversion subroutine, communication processing subroutine, keyboard processing subroutine, warp/weft clock computing functions, dial the code switch handle child, switch input processing function, the switch quantity output treatment function, display function. MCU software programming to CodeVisionAVR C compiler as a development platform, USES C written in a high-level language.3.TAGUSES the wireless transceiver module and single-chip integration design, can reduce the hardware cost of the system, convenient installation, easy maintenance. Adopt type a 15 STR micropower wireless digital module, high efficiency forward error correction channel coding technology, improves the data the abrupt interference and random interference resistance ability. Using high-speed microcontroller W7E58, improve the measurement precision of the liquid level, simplified the hardware structure of the system. The system not only for level measurement is a kind of safe and effective solutions, can be applied to other material level measurement under the bad environment.Street lamp lighting system is indispensable to the road traffic Facilities, design a kind of intelligent street light control system, right Increase induced by road, improve the driving safety at night And comfort, effectively prevent criminal activity, beautify the environment, Save power resources, has a certain practical significance and can be Development value.References[1], truth, science and technology. 8051 series single chip microcomputer C program design manual [M]. Completely People post and telecommunications press, 2006.[2] realistic technology. Microcontroller peripheral devices and applications [M]. Typical people Posts and telecommunications press, 2006, 2.[3] BianChunYuan, wang zhiqiang. MCS - 51 single chip microcomputer application development practical subroutine [M]. People's posts and telecommunications press, 2005, 9.[4] Shen Gongwei. Based on single chip microcomputer intelligent syste design and implementation [M]. Electronic Industrial press, 2005. m[5] Wan Guangyi, nine sun Ann, Cai Jianping. SOC SCM experiment, practice and should be With design - based on C8051F series [M]. Beijing university ofaeronautics and astronautics Publisher, 2006.[6] Xu Aijun Peng Xiuhua. Keil Cx51 V7.0 microcontroller programming in a high-level language and Mu Vision2 application practice [M]. Beijing: electronic industry press, 2004.[7] blockbuster, special expensive, were yu. Intelligent street light control system design and application research. The modern electronic technology, 2010. (1) : 207-207.[8] kang hua guang, Chen Taiqin. Analog part electronic technology foundation [M]. Beijing: higher education press, 2001.基于单片机的智能路灯控制系统【摘要】设计了一个路灯自动控制系统，具有时控、光控相结合的路灯开关控制功能；以及路灯故障检测并显示故障路灯编号的功能。
毕业设计论文外文文献翻译智能交通信号灯控制中英文对照
英语原文Intelligent Traffic Light Controlby Marco Wiering The topic I picked for our community project was traffic lights. In a community, people need stop signs and traffic lights to slow down drivers from going too fast. If there were no traffic lights or stop signs, people’s lives would be in danger from drivers going too fast.The urban traffic trends towards the saturation, the rate of increase of the road of big city far lags behind rate of increase of the car.The urban passenger traffic has already become the main part of city traffic day by day and it has used about 80% of the area of road of center district. With the increase of population and industry activity, people's traffic is more and more frequent, which is unavoidable. What means of transportation people adopt produces pressure completely different to city traffic. According to calculating, if it is 1 to adopt the area of road that the public transport needs, bike needs 5-7, car needs 15-25, even to walk is 3 times more than to take public transits. So only by building road can't solve the city traffic problem finally yet. Every large city of the world increases the traffic policy to the first place of the question.For example，according to calculating, when the automobile owning amount of Shanghai reaches 800,000 (outside cars count separately ), if it distributes still as now for example: center district accounts for great proportion, even when several loop-lines and arterial highways have been built up , the traffic cannot be improved more than before and the situation might be even worse. So the traffic policy Shanghai must adopt , or called traffic strategy is that have priority to develop public passenger traffic of city, narrow the scope of using of the bicycle progressively , control the scale of growth of the car traffic in the center district, limit the development of the motorcycle strictly.There are more municipals project under construction in big city. the influence on the traffic is greater.Municipal infrastructure construction is originally a good thing of alleviating the traffic, but in the course of constructing, it unavoidably influence the local traffic. Some road sections are blocked, some change into an one-way lane, thus the vehicle can only take a devious route . The construction makes the road very narrow, forming the bottleneck, which seriously influence the car flow.When having stop signs and traffic lights, people have a tendency to drive slower andlook out for people walking in the middle of streets. To put a traffic light or a stop sign in a community, it takes a lot of work and planning from the community and the city to put one in. It is not cheap to do it either. The community first needs to take a petition around to everyone in the community and have them sign so they can take it to the board when the next city council meeting is. A couple residents will present it to the board, and they will decide weather or not to put it in or not. If not put in a lot of residents might be mad and bad things could happened to that part of the city.When the planning of putting traffic lights and stop signs, you should look at the subdivision plan and figure out where all the buildings and schools are for the protection of students walking and riding home from school. In our plan that we have made, we will need traffic lights next to the school, so people will look out for the students going home. We will need a stop sign next to the park incase kids run out in the street. This will help the protection of the kids having fun. Will need a traffic light separating the mall and the store. This will be the busiest part of the town with people going to the mall and the store. And finally there will need to be a stop sign at the end of the streets so people don’t drive too fast and get in a big accident. If this is down everyone will be safe driving, walking, or riding their bikes.In putting in a traffic light, it takes a lot of planning and money to complete it. A traffic light cost around $40,000 to $125,000 and sometimes more depending on the location. If a business goes in and a traffic light needs to go in, the business or businesses will have to pay some money to pay for it to make sure everyone is safe going from and to that business. Also if there is too many accidents in one particular place in a city, a traffic light will go in to safe people from getting a severe accident and ending their life and maybe someone else’s.The reason I picked this part of our community development report was that traffic is a very important part of a city. If not for traffic lights and stop signs, people’s lives would be in danger every time they walked out their doors. People will be driving extremely fast and people will be hit just trying to have fun with their friends. So having traffic lights and stop signs this will prevent all this from happening.Traffic in a city is very much affected by traffic light controllers. When waiting for a traffic light, the driver looses time and the car uses fuel. Hence, reducing waiting times before traffic lights can save our European society billions of Euros annually. To make traffic light controllers more intelligent, we exploit the emergence of novel technologies such as communication networks and sensor networks, as well as the use of more sophisticated algorithms for setting traffic lights. Intelligent traffic light control does not only mean thattraffic lights are set in order to minimize waiting times of road users, but also that road users receive information about how to drive through a city in order to minimize their waiting times. This means that we are coping with a complex multi-agent system, where communication and coordination play essential roles. Our research has led to a novel system in which traffic light controllers and the behaviour of car drivers are optimized using machine-learning methods.Our idea of setting a traffic light is as follows. Suppose there are a number of cars with their destination address standing before a crossing. All cars communicate to the traffic light their specific place in the queue and their destination address. Now the traffic light has to decide which option (ie, which lanes are to be put on green) is optimal to minimize the long-term average waiting time until all cars have arrived at their destination address. The learning traffic light controllers solve this problem by estimating how long it would take for a car to arrive at its destination address (for which the car may need to pass many different traffic lights) when currently the light would be put on green, and how long it would take if the light would be put on red. The difference between the waiting time for red and the waiting time for green is the gain for the car. Now the traffic light controllers set the lights in such a way to maximize the average gain of all cars standing before the crossing. To estimate the waiting times, we use 'reinforcement learning' which keeps track of the waiting times of individual cars and uses a smart way to compute the long term average waiting times using dynamic programming algorithms. One nice feature is that the system is very fair; it never lets one car wait for a very long time, since then its gain of setting its own light to green becomes very large, and the optimal decision of the traffic light will set his light to green. Furthermore, since we estimate waiting times before traffic lights until the destination of the road user has been reached, the road user can use this information to choose to which next traffic light to go, thereby improving its driving behaviour through a city. Note that we solve the traffic light control problem by using a distributed multi-agent system, where cooperation and coordination are done by communication, learning, and voting mechanisms. To allow for green waves during extremely busy situations, we combine our algorithm with a special bucket algorithm which propagates gains from one traffic light to the next one, inducing stronger voting on the next traffic controller option.We have implemented the 'Green Light District', a traffic simulator in Java in which infrastructures can be edited easily by using the mouse, and different levels of road usage can be simulated. A large number of fixed and learning traffic light controllers have already been tested in the simulator and the resulting average waiting times of cars have been plotted and compared. The results indicate that the learning controllers can reduce average waiting timeswith at least 10% in semi-busy traffic situations, and even much more when high congestion of the traffic occurs.We are currently studying the behaviour of the learning traffic light controllers on many different infrastructures in our simulator. We are also planning to cooperate with other institutes and companies in the Netherlands to apply our system to real world traffic situations. For this, modern technologies such as communicating networks can be brought to use on a very large scale, making the necessary communication between road users and traffic lights possible.中文翻译：智能交通信号灯控制马克·威宁我所选择的社区项目主题是交通灯。
智能交通信号控制外文翻译
《现代控制理论》题目智能交通信号控制学生姓名学号学院专业指导教师二Ｏ一三年12 月15 日Intelligent Traffic Signal Control Using Wireless SensorNetworksVignesh.Viswanathan and Vigneshwar. SanthanamAbstract:The growing vehicle population in all developing and developed countries calls for a major change in the existing traffic signaling systems. The most widely used automated system uses simple timer based operation which is inefficient for non-uniform traffic. Advanced automated systems in testing use image processing techniques or advanced communication systems in vehicles to communicate with signals and ask for routing. This might not be implementable in developing countries as they prove to be complex and expensive. The concept proposed in this paper involves use of wireless sensor networks to sense presence of traffic near junctions and hence route the traffic based on traffic density in the desired direction. This system does not require any system in vehicles so can be implemented in any traffic system easily. This system uses wireless sensor networks technology to sense vehicles and a microcontroller based routing algorithm for traffic management.Keywords:Intelligent traffic signals, intelligent routing, smart signals, wireless sensor networks.I. INTRODUCTIONThe traffic density is escalating at an alarming rate in developing countries which calls for the need of intelligent traffic signals to replace the conventional manual and timer based systems. Experimental systems in existence involve image processing based density identification for routing of traffic which might be inefficient in situations like fog, rain or dust. The other conceptual system which is based on interaction of vehicles with traffic signals and each other require hardware modification on each vehicle and cannot be practically implemented in countrieslike India which have almost 100 million vehicles on road [1]. The system proposed here involves localized traffic routing for each intersection based on wireless sensor networks. The proposed system has a central controller at every junction which receives data from tiny wireless sensor nodes placed on the road. The sensor nodeshave sensors that can detect the presence of vehicle and the transmitter wirelessly transmits the traffic density to the central controller. The controller makes use of the proposed algorithm to find ways to regulate traffic efficiently.II. THE NEED FOR AN ALTERNATE SYSTEMT he most prevalent traffic signaling system in developing countries is the timer based system. This system involves a predefined time setting for each road at an intersection. While this might prove effective for light traffic, heavy traffic requires an adaptive system that will work based on the density of traffic on each road. The first system proposed for adaptive signaling was based on digital image processing techniques. This system works based on the captured visual input from the roads and processing them to find which road has dense traffic. This system fails during environmental interaction like rain or fog. Also this system in testing does not prove efficient. The advanced system in testing at Pittsburgh [2] involves signals communicating with each other and also with the vehicles. The proposed system does not require a network between signals and vehicles and is a standalone system at each intersection.III. THE PROPOSED SYSTEMThis paper presents the concept of intelligent traffic routing using wireless sensor networks. The primary elements of this system are the sensor nodes or motes consisting of sensors and a transmitter. The sensors interact with the physical environment while the transmitter pages the sensor’s data to the central controller. This system involves the 4 x 2 array of sensor nodes in each road. This signifies 4 levels of traffic and 2 lanes in each road. The sensors are ultrasonic or IR based optical sensors which transmits status based on presence of vehicle near it. The sensor nodes transmit at specified time intervals via ZigBee protocol to the central controller placed at every intersection. The controller receives the signal and computes which road and which lane has to be given green signal based on the density of traffic. The controller makes use of the discussed algorithm to perform the intelligent traffic routing.IV. COMPONENTS INVOLVED IN THE SYSTEMThe proposed system involves wireless sensor networks which are comprised of three basic components: the sensor nodes or motes, power source and a central controller. The motes in turn are comprised of Sensors and transceiver module. The sensors sense the vehicles at intersections and transceiver transmit the sensor’s data to the central controller through a wireless medium. The Power source provides the power needed for the sensor nodes and is mostly regenerative. The central controller performs all the computations for the sensor networks. The controller receives the input from all sensors and processes simultaneously to make the required decisions.A.SensorsSensors are hardware devices that produce a measurable response to a change in a physical condition like temperature or pressure. Sensors measure physical data of the parameter to be monitored. The continual analog signal produced by the sensors is digitized by an analog-to-digital converter and sent to controllers for further processing. A sensor node should be small in size, consume extremely low energy, operate in high volumetric densities, be autonomous and operate unattended, and be adaptive to the environment. As wireless sensor nodes are typically very small electronic devices, they can only be equipped with a limited power source of less than 0.5-2 ampere-hour and 1.2-3.7 volts. Sensors are classified into three categories: passive Omni-directional sensors; passive narrow-beam sensors; and active sensors [3].The sensors are implemented in this system placed beneath the roads in an intersection or on the lane dividers on each road. The sensors are active obstacle detectors that detect the presence of vehicles in their vicinity. The sensors are set in four levels on each road signifying four levels of traffic from starting from the STOP line. The fourth level indicates high density traffic and signifies higher priority for the road to the controller. The sensors required for obstacle detection can be either ultrasonic or Infrared LASER based sensors for better higher efficiency.B. MotesA mote, also known as a sensor node is a node in a wireless sensor network that is capable of performing some processing, gathering sensory information and communicating with other connected nodes in the network. The main components of a sensor node are a microcontroller, transceiver, external memory, power source and one or more sensors [3].Fig. 1 Block Diagram of a MoteC. Need for MotesThe primary responsibility of a Mote is to collect information from the various distributed sensors in any area and to transmit the collected information to the central controller for processing. Any type of sensors can be incorporated with these Motes based on the requirements. It is a completely new paradigm for distributed sensing and it opens up a fascinating new way to look at sensor networks.D. Advantages of Motes●The core of a mote is a small, low-cost, low-power controller.●The controller monitors one or more sensors. It is easy to interface all sorts ofsensors, including sensors for temperature, light, sound, position, acceleration, vibration, stress, weight, pressure, humidity, etc. with the mote.●The controller connects to the central controller with a radio link. The mostcommon radio links allow a mote to transmit at a distance of about 3 to 61 meters.Power consumption, size and cost are the barriers to longer distances. Since a fundamental concept with motes is tiny size and associated tiny cost, small and low-power radios are normal.●As motes shrink in size and power consumption, it is possible to imagine solarpower or even something exotic like vibration power to keep them running. It is hard to imagine something as small and innocuous as a mote sparking a revolution, but that's exactly what they have done.●Motes are also easy to program, either by using serial or Ethernet cable to connectto the programming board or by using Over the Air Programming (OTAP).Fig. 2 Block Diagram of the Proposed SystemE. TransceiversSensor nodes often make use of ISM band, which gives free radio, spectrum allocation and global availability. The possible choices of wireless transmission media are radio frequency (RF), optical communication and infrared. Lasers require less energy, but need line-of-sight for communication and are sensitive to atmospheric conditions. Infrared, like lasers, needs no antenna but it is limited in its broadcasting capacity. Radio frequency-based communication is the most relevant that fits most ofthe WSN applications. WSNs tend to use license-free communication frequencies: 173, 433, 868, and 915 MHz; and 2.4 GHz. The functionality of bothtransmitter and receiver are combined into a single deviceknown as a transceiver [3].To bring about uniqueness in transmitting and receiving toany particular device various protocols/algorithms are devised. The Motes are often are often provided with powerful transmitters and receivers collectively known as transceivers for better long range operation and also toachieve better quality of transmission/reception in any environmental conditions.F. Power SourceT he sensor node consumes power for sensing, communicating and data processing. More energy is required for data communication than any other process. Power is stored either in batteries or capacitors. Batteries, both rechargeable and non-rechargeable, are the main source of power supply for sensor nodes. Current sensors are able to renew their energy from solar sources, temperature differences, or vibration. Two power saving policies used are Dynamic Power Management (DPM) and Dynamic V oltage Scaling (DVS). DPM conserves power by shutting down parts of the sensor node which are not currently used or active. A DVS scheme varies the power levels within the sensor node depending on the non-deterministic workload. By varying the voltage along with the frequency, it is possible to obtain quadratic reduction in power consumption.G. Tmote SkyTmote Sky is an ultra low power wireless module for use in sensor networks, monitoring applications, and rapid application prototyping. Tmote Sky leverages industry standards like USB and IEEE802.15.4 to interoperate seamlessly with other devices. By using industry standards, integrating humidity, temperature, and light sensors, and providing flexible interconnection with peripherals, Tmote Sky enables a wide range of mesh network applications [4]. The TMote is one of the most commonly used motes in wireless sensor technology. Any type of sensor can be used in combination with this type of mote.Tmote Sky features the Chipcon CC2420 radio for wireless communications. TheCC2420 is an IEEE 802.15.4 compliant radio providing the PHY and some MAC functions [5]. With sensitivity exceeding the IEEE 802.15.4 specification and low power operation, the CC2420 provides reliable wireless communication. The CC2420 is highly configurable for many applications with the default radio settings providing IEEE 802.15.4 compliance. ZigBee specifications can be implemented using the built-in wireless transmitter in the Tmote Sky.Fig. 3 Tmote SkyH. Tmote Key Features•250kbps 2.4GHz IEEE 802.15.4 Chipcon Wireless Transceiver• Interoperability with other IEEE 802.15.4 devices.• 8MHz Texas Instruments MS P430 microcontroller (10k RAM, 48k Flash Memory)• Integrated ADC, DAC, Supply V oltage Supervisor, and DMA Controller• Integrated onboard antenna with 50m range indoors / 125m range outdoors• Integrated Humidity, Temperature, and Light sensors• Ultra low current consumption• Fast wakeup from sleep (<6μs)• Hardware link-layer encryption and authentication• Programming and data collection via USB• 16-pin expansion support and optional SMA antenna connector• TinyOS support : mesh net working and communication implementation• Complies with FCC Part 15 and Industry Canada regulations• Environmentally friendly – complies with RoHS regulations [4].I. ZigBee Wireless TechnologyZigBee is a specification for a suite of high level communication protocols using small, low-power digital radios based on an IEEE 802.15.4 standard for personal area networks [6] [7]. ZigBee devices are often used in mesh network form to transmit data over longer distances, passing data through intermediate devices to reach more distant ones.This allows ZigBee networks to be formed ad-hoc, with no centralized control or high-power transmitter/receiver able to reach all of the devices. Any ZigBee device can be tasked with running the network. ZigBee is targeted at applications that require a low data rate, long battery life, and secure networking. ZigBee has a defined rate of 250kbps, best suited for periodic or intermittent data or a single signal transmissionfrom a sensor or input device. Applications include wireless light switches, electrical meters with in-home-displays, traffic management systems, and other consumer and industrial equipment that requires short-range wireless transfer of data at relatively low rates. The technology defined by the ZigBee specification is intended to be simpler and less expensive than other WPANs, such as Bluetooth.J. Types of ZigBee DevicesZigBee devices are of three types:●ZigBee Coordinator (ZC): The most capable device, the Coordinator forms theroot of the network tree and might bridge to other networks. There is exactly one ZigBee Coordinator in each network since it is the device that started the network originally. It stores information about the network, including acting as the Trust Center & repository for security keys. The ZigBee Coordinator the central controller is in this system.●ZigBee Router (ZR): In addition to running an application function, a devicecan act as an intermediate router, passing on data from other devices.●ZigBee End Device (ZED): It contains just enough functionality to talk to theparent node. It cannot relay data from other devices. This relationship allows the node to be asleep a significant amount of the time thereby giving long battery life. A ZED requires the least amount of memory, and therefore can be less expensive to manufacture than a ZR or ZC.K. ZigBee ProtocolsThe protocols build on recent algorithmic research to automatically construct a low-speed ad-hoc network of nodes. In most large network instances, the network will be a cluster of clusters. It can also form a mesh or a single cluster. The current ZigBee protocols support beacon and non-beacon enabled networks. In non-beacon-enabled networks, an un-slotted CSMA/CA channel access mechanism is used. In this type of network, ZigBee Routers typically have their receivers continuously active, requiring a more robust power supply. However, this allows for heterogeneous networks in which some devices receive continuously, while others only transmit when an external stimulus is detected. In beacon-enabled networks, the special network nodes called ZigBee Routers transmit periodic beacons to confirm their presence to other network nodes. Nodes may sleep between beacons, thus lowering their duty cycle and extending their battery life. Beacon intervals depend on data rate; they may range from 15.36ms to 251.65824s at 250 kbps. In general, the ZigBee protocols minimize the time the radio is on, so as to reduce power use. In beaconing networks, nodes only need to be active while a beacon is being transmitted. In non-beacon-enabled networks, power consumption is decidedly asymmetrical: some devices are always active, while others spend most of their time sleeping.V. PROPOSED ALGORITHMA. Basic AlgorithmConsider a left side driving system (followed in UK, Australia, India, Malaysia and 72 other countries). This system can be modified for right side driving system (USA, Canada, UAE, Russia etc.) quite easily. Also consider a junction of four roads numbered as node 1, 2, 3 and 4 respectively. Traffic flows from each node to three other nodes with varied densities. Consider road 1 now given green signal in all directions.Fig. 4 Intersection Under Consideration1) Free left turn for all roads (free right for right side driving system).2) Check densities at all other nodes and retrieve data from strip sensors.3) Compare the data and compute the highest density.4) Allow the node with highest density for 60sec.5) Allowed node waits for 1 time slot for its turn again and the process is repeated from step 3.B. Advanced AlgorithmAssume road three is currently given green to all directions. All left turns are always free. No signals/sensors for left lane. Each road is given a time slot of maximum 60 seconds at a time. This time can be varied depending on the situation of implementation. Consider 4 levels of sensors Ax, Bx, Cx, Dx with A having highest priority and x representing roads 1 to 4. Also consider 3 lanes of traffic: Left (L), Middle (M) and Right(R) corresponding to the direction of traffic. Since leftturn is free, Left lanes do not require sensors. So sensors form 4x2 arrays with 4 levels of traffic and 2 lanes and are named MAx, RAx, MBx, RBx and so on and totally 32 sensors are employed.The following flow represents the sequence of operation done by the signal.1) Each sensor transmits the status periodically to the controller.2) Controller receives the signals and computes the following3) The sensors Ax from each road having highest priority are compared.4) If a single road has traffic till Ax, it is given green signal in the next time slot.5) If multiple roads have traffic till Ax, the road waiting for the longest duration is given the green.6) Once a road is given green, its waiting time is reset and its sensor status is neglected for that time slot7) If traffic in middle lane, green is given for straight direction, based on traffic, either right side neighbor is given green for right direction, of opposite road is give green for straight direction.8) If traffic in right lane, green is given for right, and based on traffic, left side neighbor is given green for straight or opposite is given green for right.9) Similar smart decisions are incorporated in the signal based on traffic density and directional traffic can be controlled.C. Implementation and RestrictionsThis system can be implemented by just placing the sensor nodes beneath the road or on lane divider and interfacing the central controller to the existing signal lights and connecting the sensor nodes to the controller via the proposed wireless protocol. The only restriction for implementing the system is taking the pedestrians into consideration. This has to be visualized for junctions with heavy traffic such as highway intersections and amount of pedestrians is very less. Also major intersections have underground or overhead footpaths to avoid interaction of pedestrians with heavy traffic.VI. CONCLUSIONThe above proposed system for automated traffic signal routing using Wireless Sensor Networks is advantageous to many existing systems. The wireless sensors nodes create a standalone system at each intersection making it easy to implement in the intersections having heavy density of vehicles. It is also cost inexpensive and does not require any system in the vehicles making it more practical than existing systems. The use of various systems of sensor nodes can be altered based on the requirement and any type of sensor can be used based on the feasibility of the location.ACKNOWLEDGMENTThe Authors would like to take this opportunity to thank Ms. P. Sasikala, Assistant Professor, ECE department, Sri Venkateswara College of Engineering, Sriperumbudur, who gave the basic insight into the field of Wireless Sensor Networks. We also thank Mrs. G. Padmavathi, Associate Professor, ECE department, Sri Venkateswara College of Engineering, Sriperumbudur, who with her expertise in the field of networks advised and guided on practicality of the concept and provided helpful ideas for future modifications. We also express our gratitude to Dr. S. Ganesh Vaidyanathan, Head of the department of ECE, Sri Venkateswara College of Engineering, Sriperumbudur, who supports us for every innovative project and encourages us “think beyond”for better use of technology. And finally we express our heart filled gratitude to Sri Venkateswara College of Engineering, which has been the knowledge house for our education and introduced us to the field of Engineering and supports us for working on various academic projects.基于无线传感器网络的智能交通信号控制摘要：在所有发展中国家和发达国家，不断增长的汽车数量将促使现有的交通信号系统发生重大变革。
外文翻译—智能交通灯模拟器方案和硬件模糊逻辑实现
毕业设计外文资料翻译学院：电子工程学院专业班级：自动化 091学生姓名：学号：指导教师：外文出处：(外文>附件： 1.外文资料翻译译文； 2.外文原文基于智能交通灯模拟器的设计和硬件模糊逻辑实现文章历史：本研究的目的是开发基于模糊逻辑的交通路口的光模拟器系统和智能交通路口的灯控制器的目的并观察其性能设计。
交通仿真硬件开发，克服困难，在真实的环境中工作，容易验证控制器的性能。
通过建立交通灯模拟研究，结果是不断的持续时间<常规）交通灯控制器和基于模糊逻辑的交通灯光控制器相比，在车的输入是由模拟器。
统计从实现仿真表明，模糊逻辑的交通灯的实验结果控制器大大减少了等待红灯的时间，因为根据控制器的适应交通密度。
很明显，智能灯光控制器有着重要的优势在经济和环境方面。
2009 Elsevier B.V.保留所有权利。
1 景区简介大多数的交通路口的信号控制器固定周期式<常规），即，恒定的绿/红相各交通信号周期。
虽然这种操作方式简单，其性能在交通应用中一般较差。
一个合理的选择是不是一个智能控制器的设计固定周期的交通灯控制系统。
因为他们有很多智能交通灯的优点，尤其不能忽视在都市区。
在Zadeh的模糊集理论中的定义1965，这项技术已被广泛应用于工程应用。
一些研究应用模糊集理论的交通信号控制进行了[1– 6 ]。
其中最受欢迎的是通过Pappis和Mamdani 提出[ 1 ]。
他们为建立一个很好的模型双向交通处各有一个车道的交通流[ 1 ]。
这nakatsuyama实现了基于模糊逻辑的交通灯控制的级联1984双向交通路口[2],1993等。
介绍了一个交通灯控制器多车道交通枢纽[ 4 ]。
最近，特拉比亚等人。
[6]四车道leftturning带模拟单结交通流的考虑。
目前的研究[ 7-14 ]有考虑交通信号控制从不同的角度方面。
这些研究的目的是获得最佳的交通流量达到最小等待时间。
这些研究都是基于软件仿真模型。
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智能交通信号灯摘要：信号控制是一种必要的措施以确保的质量和安全,交通循环。
现在的信号控制的进一步发展具有极大的潜力来减少运行时间、车辆、事故成本和整车排放。
检测的发展和计算机技术改变了交通信号控制从定时开环规定自适应反馈控制。
目前的自适应控制方法,像英国、瑞典MOV A SOS)和英国(孤立的信号(area-wide又控制),采用数学优化与仿真技术来调整信号波动的时间观察到的交通流实时的。
优化是通过改变时间和周期长度的绿色的信号。
在area-wide交叉口控制偏移是之间也发生了变化。
已经开发为几种方法确定最优周期长度和最小延迟在十字路口,但基于不确定性和严格的交通信号控制的本质,全局最优是不可能找到的。
1．引文：由于越来越多的公众意识的环境影响道路交通许多当局现在所追求的政策来:，管理供求−拥挤，影响模式和路径选择−;贯彻“三个代表”重要思想,提高公共汽车−有轨电车和其他公共服务车辆;设施提供更好的、更安全,骑自行车和行人的道路使用者等脆弱;降低汽车排放−、噪声和视觉入侵;为所有道路改善安全−用户群。
在自适应交通信号控制的弹性增强的增加的数量在周期层叠的绿色阶段,从而使数学优化非常复杂和困难。
因为这个原因,自适应信号控制在大多数情况下不是建立在精确的优化上,而是建立在绿色的扩展原理。
在实践中,遵循的均匀性是最主要的交通信号控制安全的原因。
这一规定的限制的周期时间和相位的安排。
因此,在实践中是交通信号控制的针对性的解决方案和调整的基础上由交通规划者。
现代可编程信号控制器以大量的可调参数是非常适合这一过程。
对于好的结果,一个经验丰富的策划人和微调领域中是必要的。
模糊控制已经被证明是成功的,在这些问题中,精确的数学建模是困难的或不可能的,但一名有经验的人可以控制的工艺操作。
因此,交通信号控制是一种适合于任务特别为模糊控制。
事实上,最古老的文化之一的潜力的例子是一个模拟的模糊控制在一个inter-section交通信号控制的两个单向的街道。
即使在这个非常简单的情况下,模糊控制是至少在作为一个良好的传统的自适应控制。
一般而言,模糊控制是发现在复杂问题都优于用多目标决策。
在交通信号控制多种交通流竞争来自同一时间和空间,而且不同的优先选择往往不同交通流或车辆组。
此外,优化标准,包括几个同时喜欢平均和最大车辆和行人延误、最大队列长度和百分比停止的车辆。
所以,它很可能是很有竞争力的模糊控制在复杂真实的十字路口的地方传统的优化方法的使用是有问题的。
2．模糊逻辑：介绍了模糊逻辑,并成功地应用于大范围的自动控制任务。
最大的好处模糊逻辑是有机会模型与不确定的模糊决策。
此外,模糊逻辑有能力理解语言指令和控制策略的基础上产生的先验的沟通。
这一点在利用模糊逻辑来控制理论的基础上,是模仿人类专家控制的知识,而不是为了构建过程本身。
的确,模糊控制已经被证明是成功的,在这些问题中,精确的数学建模是困难的或不可能的,但一名有经验的操作员可以控制的过程。
一般而言,模糊控制是发现在复杂问题都优于多目标决策。
目前,有大量的基于模糊推论系统技术。
不过它们当中的主要部分,受含糊不清的根基;即使它们大都是古典数学方法表现更好,他们还带有黑色的盒子,如德模糊化,这是很难证明数学或逻辑的。
例如,如果-然后模糊规则,它们在核心的模糊推理系统,经常报道的工作方式,是Ponens概括规则推理机制的经典,但随便起来就不是这样的,这之间的关系,这些规则和多值逻辑是任何已知的复杂和人工。
此外,专家系统的性能应相当于人类专家:它应该得到同样的结果,专家给,但提醒当控制问题是如此模糊,专家是不确定适当的行为。
现有的模糊专家系统很少满足这第二种情况。
然而,很多研究观察,模糊推理的方法是基于相似。
Kosko,举个例子,写的模糊隶属……代表的相似性定义对象特性的imprecisely。
以这句话严重,我们学习系统的多值等价,即模糊相似度。
原来,从Lukasiewicz多值逻辑的定义,我们能构建出一个模糊推理方法的表演,依赖于专家知识推理和只在定义的逻辑概念。
所以,我们不需要任何人造的解模糊化方法确定(如重心)决定最后输出的推断。
我们基本的观察是,任何的模糊集的生成一个模糊相似度,这些相似之处可以结合到一个模糊关系,变成了一个模糊相似度,太。
我们把这称为诱导模糊关系总模糊相似度。
如果-然后模糊推论系统实际上是选择:比较了每一个问题的IF-part规则库以一实际输入值,找到最相似案例和火相应的THEN-part;如果它并非是独一无二的,使用一个标准赋予了一位专家来进行。
基于多值逻辑Lukasiewicz welldefined,我们展示如何使用该方法可以正式实施。
假设和原则模糊交通信号控制交通信号控制是用来最大限度地提高效率的现有交通系统。
然而,交通系统的效率,甚至可以模糊。
通过提供时间分离的权利的方式接近流动,交通信号产生深刻影响了效率的交通流。
它们能操控的优势或者劣势的车辆和行人的;取决于权利的分配方式。
因此,正确的应用、设计、安装、操作和保养维护,交通信号的关键,是安全、高效有序的交通十字路口的运动。
在交通信号控制的,我们都能找到某种中不确定性的许多层面。
交通信号控制的输入是不准确的,而且这也意味着我们无法处理的交通方式的确切位置。
可能性是复杂的控制,并处理这些可能性是一个极其复杂的任务。
安全、最小化最大化,减少延迟环境方面的一些目标的控制,但这是很难处理大家聚在一起,传统的交通信号控制。
causeconsequence -关系的解释也不可能在交通信号控制。
这些都是典型特征的模糊控制。
基于模糊逻辑控制器的设计来捕获的关键因素,而不需要控制过程中许多详细的数学公式。
由于这个事实,他们有许多优势,在实时应用。
有一个简单的运算的控制器结构,因为它们不需要很多的数值计算。
他们的IFTHEN逻辑推理规则不需要很多的计算时间。
同时,控制器能够进行了大范围的输入,因为不同的控制规则可适用于他们。
如果系统相关知识是为代表的IFTHEN——简单模糊控制器的规则,fuzzy-based可以控制系统具有效率及减轻。
的主要目标是确保交通信号控制交叉口安全系统通过保持冲突交通流分开。
最优性能的十字路口相结合的系统工程,环境影响时间价值和交通安全。
我们的目标是优化系统,但是我们需要来决定什么属性和重量将被用来判断最优。
整个的知识的过程中,系统设计者对交通信号控制在这种情况下,被控制的能量储存在规则知识库。
有一个基本的规则从而影响系统的闭环的行为,因此它们应该是获得了彻底。
规则的发展是很耗时,设计师经常需要为他翻译过程知识转化为合适的规则。
Sugeno 提到的四种方法,推导出恶化模糊控制规则:1.运营商经验2:控制工程师的知识2,3,6,7,11,14]3;该主算子的来讲模糊建模的控制措施4.模糊建模的过程5.酥脆的建模过程6;髓启发式的设计规则7;往往在线改编的规则。
通常一个组合这些现象的一些方法是必要的,以获得较好效果。
在常规控制经验,增加设计的模糊控制器,导致减少开发时间。
项目的主要目标是FUSICO-research理论分析的模糊交通信号控制,广义模糊规则的交通信号控制使用语言变量,验证了模糊控制原理和校准的隶属度函数,并发展了一种模糊自适应信号控制器。
vehicle-actuated控制的策略,如SOS,MOV A和LHOVRA是控制算法,对第一代。
模糊控制算法,该算法可以之一的第二代,代的人工智能(AI)。
摘要模糊控制是有能力处理多目标的、多维的和复杂的交通状况,如交通信号。
模糊控制的典型优点是简单的流程,有效１控制,提高产品质量。
3．FUSICO：FUSICO-project塑造出的经验的警察。
这个规则库的发展是在1996年秋季。
j . they Kari正常,经验丰富的交通信号规划师,工作时在赫尔辛基理工大学在这个时间。
每天工作小组讨论,他的经验帮助我们模型对我们的规则。
在特定情况下病理交通拥堵或很少有车辆在循环;在那里first-in-first-out是唯一合理的控制策略。
该算法寻找最相似的实际IF-part输入值,并给出了相应的THEN-part然后被解雇了。
交通信号控制系统三个现实的方法来构造算法和仿真模型检验他们的表现。
要解决问题,类似的仿真Mamdani non-fuzzy和古典风格的模糊推理系统,也是。
结果对车辆和行人延误或平均平均车辆延误,在大多数情况下更好的在模糊相似度为基础的控制比在其他的控制系统。
比较模糊相似度为基础的模糊控制的控制和Mamdani风格也强度的假定,在近似推理过程中时,一个基本概念是多值之间的相似的对象,而不是一种概括规则的推理方式,Ponens经典。
FUSICO项目结果这个计画的结果表明,模糊信号控制的潜力是孤立交叉口控制的一种方法。
比较结果的Pappis-Mamdani控制、模糊孤立的人行过街和模糊两阶段的控制是很不错的。
结果表明,孤立的人行过街的模糊控制提供了有效的两种对立的目标妥协,最低行人延误和最小的车辆的延误。
结果对两相控制和Pappis-Mamdani控制表明,模糊控制应用领域很广。
改进的最大延时超过20%,这意味着模糊控制的效率可以比传统的vehicle-actuated控制的效率。
根据这些结果,我们可以说,模糊信号控制可以多目标和更有效率,比常规自适应信号控制现在。
最大的好处,或许,达到更复杂的十字路口和环境。
这FUSICO-project仍在继续。
目的是将一步步的更复杂的交通信号,并继续对模糊控制理论著作。
第一个例子将公共交通优先考虑的问题。
原文：Intelligent traffic lightsAbstract：Signal control is a necessary measure to maintain the quality and safety of traffic circulation. Further development of present signal control has great potential to reduce travel times, vehicle and accident costs, and vehicle emissions. The development of detection and computer technology has changed traffic signal control from fixed-time open-loop regulation to adaptive feedback control. Present adaptive control methods, like the British MOV A, Swedish SOS (isolated signals) and British SCOOT (area-wide control), use mathematical optimization and simulation techniques to adjust the signal timing to the observed fluctuations of traffic flow２in real time. The optimization is done by changing the green time and cycle lengths of the signals. In area-wide control the offsets between intersections are also changed. Several methods have been developed for determining the optimal cycle length and the minimum delay at an intersection but, based on uncertainty and rigid nature of traffic signal control, the global optimum is not possible to find out.1.Citation：As a result of growing public awareness of the environmental impact of road traffic many authorities are now pursuing policies to:− manage demand and congestion;− influence mode and route choice;− improve priority for buses, trams and other public service vehicles;− provide better and safer facilities for pedestrians, cyclists and other vulnerable road users;− reduce vehicle emissions, noise and visual intrusion; and− improve safety for all road user groups.In adaptive traffic signal control the increase in flexibility increases the number of overlapping green phases in the cycle, thus making the mathematical optimization very complicated and difficult. For that reason, the adaptive signal control in most cases is not based on precise optimization but on the green extension principle. In practice, uniformity is the principle followed in signal control for traffic safety reasons. This sets limitations to the cycle time and phase arrangements. Hence, traffic signal control in practice are based on tailor-made solutions and adjustments made by the traffic planners. The modern programmable signal controllers with a great number of adjustable parameters are well suited to this process. For good results, an experienced planner and fine-tuning in the field is needed. Fuzzy control has proven to be successful in problems where exact mathematical modelling is hard or impossible but an experienced human can control the process operator. Thus, traffic signal control in particular is a suitable task for fuzzy control. Indeed, one of the oldest examples of the potentials of fuzzy control is a simulation of traffic signal control in an inter-section of two one-way streets. Even in this very simple case the fuzzy control was at least as good as the traditional adaptive control. In general, fuzzy control is found to be superior in complex problems with multiobjective decisions. In traffic signal control several traffic flows compete from the same time and space, and different priorities are often set to different traffic flows or vehicle groups. In addition, the optimization includes several simultaneous criteria, like the average and maximum vehicle and pedestrian delays, maximum queue lengths and percentage of stopped vehicles. So, it is very likely that fuzzy control is very competitive in complicated real intersections where the use of traditional optimization methods is problematic.Fuzzy logic has been introduced and successfully applied to a wide range of automatic３control tasks. The main benefit of fuzzy logic is the opportunity to model the ambiguity and the uncertainty of decision-making. Moreover, fuzzy logic has the ability to comprehend linguistic instructions and to generate control strategies based on priori communication. The point in utilizing fuzzy logic in control theory is to model control based on human expert knowledge, rather than to model the process itself. Indeed, fuzzy control has proven to be successful in problems where exact mathematical modelling is hard or impossible but an experienced human operator can control process. In general, fuzzy control is found to be superior in complex problems with multi-objective decisions.At present, there is a multitude of inference systems based on fuzzy technique. Most of them, however, suffer ill-defined foundations; even if they are mostly performing better that classical mathematical method, they still contain black boxes, e.g. de fuzzification, which are very difficult to justify mathematically or logically. For example, fuzzy IF - THEN rules, which are in the core of fuzzy inference systems, are often reported to be generalizations of classical Modus Ponens rule of inference, but literally this not the case; the relation between these rules and any known many-valued logic is complicated and artificial. Moreover, the performance of an expert system should be equivalent to that of human expert: it should give the same results that the expert gives, but warn when the control situation is so vague that an expert is not sure about the right action. The existing fuzzy expert systems very seldom fulfil this latter condition.Many researches observe, however, that fuzzy inference is based on similarity. Kosko, for example, writes 'Fuzzy membership...represents similarities of objects to imprecisely defined properties'. Taking this remark seriously, we study systematically many-valued equivalence, i.e. fuzzy similarity. It turns out that, starting from the Lukasiewicz well-defined many-valued logic, we are able to construct a method performing fuzzy reasoning such that the inference relies only on experts knowledge and on well-defined logical concepts. Therefore we do not need any artificial defuzzification method (like Center of Gravity) to determine the final output of the inference. Our basic observation is that any fuzzy set generates a fuzzy similarity, and that these similarities can be combined to a fuzzy relation which turns out to a fuzzy similarity, too. We call this induced fuzzy relation total fuzzy similarity. Fuzzy IF - THEN inference systems are, in fact, problems of choice: compare each IF-part of the rule base with an actual input value, find the most similar case and fire the corresponding THEN-part; if it is not unique, use a criteria given by an expert to proceed. Based on the Lukasiewicz welldefined many valued logic, we show how this method can be carried out formally.Hypothesis and Principles of Fuzzy Traffic Signal Control Traffic signal control is used to maximize the efficiency of the existing traffic systems [6]. However, the efficiency of traffic system can even be fuzzy. By providing temporal separation of rights of way to approaching４flows, traffic signals exert a profound influence on the efficiency of traffic flow. They can operate to the advantage or disadvantage of the vehicles or pedestrians; depend on how the rights of ways are allocated. Consequently, the proper application, design, installation, operation, and maintenance of traffic signals is critical to the orderly safe and efficient movement of traffic at intersections.In traffic signal control, we can find some kind of uncertainties in many levels. The inputs of traffic signal control are inaccurate, and that means that we cannot handle the traffic of approaches exactly. The control possibilities are complicated, and handling these possibilities are an extremely complex task. Maximizing safety, minimizing environmental aspects and minimizing delays are some of the objectives of control, but it is difficult to handle them together in the traditional traffic signal control. The causeconsequence- relationship is also not possible to explain in traffic signal control. These are typical features of fuzzy control.Fuzzy logic based controllers are designed to capture the key factors for controlling a process without requiring many detailed mathematical formulas. Due to this fact, they have many advantages in real time applications. The controllers have a simple computational structure, since they do not require many numerical calculations. The IFTHEN logic of their inference rules does not require much computational time. Also, the controllers can operate on a large range of inputs, since different sets of control rules can be applied to them. If the system related knowledge is represented by simple fuzzy IFTHEN- rules, a fuzzy-based controller can control the system with efficiency and ease. The main goal of traffic signal control is to ensure safety at signalized intersections by keeping conflict traffic flows apart. The optimal performance of the signalized intersections is the combination of time value, environmental effects and traffic safety. Our goal is the optimal system, but we need to decide what attributes and weights will be used to judge optimality.The entire knowledge of the system designer about the process, traffic signal control in this case, to be controlled is stored as rules in the knowledge base. Thus the rules have a basic influence on the closed-loop behaviour of the system and should therefore be acquired thoroughly. The development of rules is time consuming, and designers often have to translate process knowledge into appropriate rules. Sugeno and Nishida mentioned four ways to derive fuzzy control rules:1. operators experience2. control engineer's knowledge3. fuzzy modelling of the operator's control actions4. fuzzy modelling of the process5. crisp modeling of the process５6. heuristic design rules7. on-line adaptation of the rules.Usually a combination of some of these methods is necessary to obtain good results. As in conventional control, increased experience in the design of fuzzy controllers leads to decreasing development times.3. FUSICOThe main goals of FUSICO-research project are theoretical analysis of fuzzy traffic signal control, generalized fuzzy rules for traffic signal control using linguistic variables, validation of fuzzy control principles and calibration of membership functions, and development of a fuzzy adaptive signal controller. The vehicle-actuated control strategies, like SOS, MOV A and LHOVRA, are the control algorithms of the first generation. The fuzzy control algorithm can be one of the algorithms of the second generation, the generation of artificial intelligence (AI). The fuzzy control is capable of handling multi-objective, multi-dimensional and complicated traffic situations, like traffic signalling. The typical advantages of fuzzy control are simple process, effective control and better quality.FUSICO-project modelled the experience of policeman. The rule base development was made during the fall 1996. Mr. Kari J. Sane, experienced traffic signal planner, was working at the Helsinki University of Technology at this time. Everyday discussions and working groups helped us to model his experience to our rules.In particular pathological traffic jams or situations where there are very few vehicles in circulation; there first-in-first-out is the only reasonable control strategy. The Algorithm is looking for the most similar IF-part to the actual input value, and the corresponding THEN-part is then fired. Three realistic traffic signal control systems were constructed by means of the Algorithm and a simulation model tested their performance. Similar simulations were made to a non-fuzzy and classical Mamdani style fuzzy inference systems, too. The results with respect to average vehicle and pedestrian delay or average vehicle delay were in most cases better on fuzzy similarity based control than on the other control systems. Comparisons between fuzzy similarity based control and Mamdani style fuzzy control also strength an assumption that, in approximate reasoning, a fundamental concept is many-valued similarity between objects rather than a generalization of classical Modus Ponens rule of inference.The results of this project have indicated that fuzzy signal control is the potential control method for isolated intersections. The comparison results of Pappis-Mamdani control, fuzzy isolated pedestrian crossing and fuzzy two-phase control are good. The results of isolated pedestrian crossing indicate that the fuzzy control provides the effective compromise between the two opposing objectives, minimum pedestrian delay and minimum vehicle delay. The results６of two-phase control and Pappis-Mamdani control indicate that the application area of fuzzy control is very wide. The maximum delay improvement was more than 20 %, which means that the efficiency of fuzzy control can be better than the efficiency of traditional vehicle-actuated control.According to these results, we can say that the fuzzy signal control can be multiobjective and more efficient than conventional adaptive signal control nowadays. The biggest benefits can, probably, be achieved in more complicated intersections and environments. The FUSICO-project continues. The aim is to move step by step to more complicated traffic signals and to continue the theoretical work of fuzzy control. The first example will be the public transport priorities.７。