智能交通灯控制系统 英文翻译

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智能交通系统的交通信号控制技术

智能交通系统的交通信号控制技术

智能交通系统的交通信号控制技术智能交通系统(Intelligent Transportation System,ITS)是一种利用先进的信息技术、电子技术和自动化技术对交通进行智能化管理和控制的系统。

交通信号控制技术作为智能交通系统中的重要组成部分,起到了至关重要的作用。

本文将介绍智能交通系统中的交通信号控制技术,并探讨其在提高交通效率、保障交通安全和减少交通拥堵方面的作用。

一、智能交通系统的交通信号控制技术概述智能交通系统的交通信号控制技术主要通过对交通信号灯的控制,实现对交通流的调节和管理。

传统的交通信号灯系统往往采用固定的方案,导致交通拥堵问题的产生。

而智能交通系统中的交通信号控制技术,通过实时监测交通流量、车辆速度等信息,能够根据实际情况进行调整,提高交通效率,减少交通拥堵。

二、智能交通系统的交通信号控制技术的应用与功能1.动态调整信号配时智能交通系统中的交通信号控制技术能够根据实时交通信息,动态调整交通信号灯的配时方案。

通过对信号配时的优化,可以提高交通流的通行效率,缓解交通拥堵状况。

2.协调多个交通信号灯智能交通系统中的交通信号控制技术还能够实现多个交通信号灯的协调。

通过交通信号灯之间的通信,确保各个路口的交通信号灯同步配合,进一步提高交通效率。

3.实时监测交通流量和车辆速度交通信号控制技术还能够实时监测交通流量和车辆速度等信息。

通过高精度的传感器和数据采集设备,可以对交通流进行精确监测,为交通信号的调整提供准确的依据。

4.应急信号优化智能交通系统中的交通信号控制技术还可以根据实时交通情况,优化应急信号。

在交通事故发生、道路施工或突发事件等情况下,系统能够自动调整信号,为应急车辆提供通畅的通行条件。

三、智能交通系统的交通信号控制技术的意义及优势智能交通系统中的交通信号控制技术在提高交通效率、保障交通安全和减少交通拥堵方面具有重要的意义和优势。

1.提高交通效率智能交通系统中的交通信号控制技术能够根据实时交通信息,动态调整信号配时和协调多个交通信号灯,提高交通流的通行效率,减少等待时间,提高交通吞吐能力。

交通灯外文翻译

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 andmore traffic management and urban planning departments need to address the the main problem.Nowadays, traffic lights installed in each crossing, has become the most common and dredge the traffic, the most effective means. The developme nt of the society, people's consumption level unceasing enhancement, pri vate vehicles unceasing increase. And more cars roads are narrow road tra ffic is clear. So adopting effective method to control the traffic light is im perative. PLC intelligent control principle is the core of the control syste m, PLC put the things direction or north-south direction according to qua ntity of vehicles, the corresponding scale what divides class given the gre en light direction between north and south direction according to certain r ules too long. It can realize divides class according to a given the green ca rs duration scale of maximum car release, reduce crossroads vehicles, eas e traffic congestion stagnation, realize the optimal control, so as to impro ve the efficiency of the traffic control system.The application of PLC is continuously, and drive to the deepening traditi onal control test new month benefit updates. It is simple in structure, prog ramming and high reliability etc, convenient already widely used in indus trial processes and position in the automatic control. Due to use of PLC h as the characteristics of environmental adaptable, and its internal timer is very rich in resources, but the current widely used "progressive" lights, es pecially for precise control more than thecrossway control can be easily realized. So now increasingly applying P LC 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 manage ment. In real-time detection and automatic control of PLC application sys tem, PLC is often used as a core components.In the 21st century, PLC will have greater development. Technically, the c omputer technology can morely new achievements used in programmable controller design and manufacturing, there will be faster, s torage and larger capacity, intelligent stronger varieties appear; Look fro m product size, can further to mini and super-large direction; Look from p roduct compatibility, the variety of our products will be more rich, specifi cation more complete, perfect man-machine interface and complete com munication equipment can better adapt to all kinds of industrial control oc casion demands; Look from the market, all countries to their production of multiple products with international competition intensifies and break, c an appear a few brand monopoly international market situation, can appea r international general programming languages; Judging from the develop ment of the network, programmable controller and other industrial control computernetworking constitute a large control system is programmable controller t echnology development direction. The current computer distributed contr ol system DCS has already a lot of programmable controller applications. Along with the development of computer network, the programmable con troller as automation control network andinternational general network will be an important part of the industry an d industry, the numerous fields outside play an increasing role.In China the increasing amount of motor vehicles, many big cities like Be ijing, Shanghai, nanjing and other ground appeared trafficoverload running condition, traffic accidents problem also more and m ore serious. And because the various special vehicles (such as an ambulance, 119 120 car, police and various special vehicle 110 in emergency situa tions, by red under limited to traffic bring a lot of inconvenience, even ca use traffic accident. And now, most traffic lights at the same moment will appear two or more than two direction at the same time for the green situa tion, and increase the incidence of the traffic accident. Therefore, design a kind of designed for special vehicles through and not cause any traffic ac cident, normal traffic control any time only one direction of modern intell igent 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。

智能交通信号控制

智能交通信号控制

智能交通信号控制智能交通信号控制(Intelligent Traffic Signal Control,ITSC)是一种基于先进技术的交通管理系统,旨在提高路口交通流量的效率和安全性。

它利用人工智能、物联网和数据分析等技术手段,实现智能化的交通信号控制,以便根据实时交通情况和需求进行信号调度和优化。

一、智能交通信号控制的背景及意义现代城市交通面临着日益严峻的挑战,交通拥堵、事故频发和交通效率低下已成为城市发展的瓶颈。

传统的时间固定和感应器控制方式已经无法适应复杂的交通环境和大量车辆流动的需求。

因此,引入智能交通信号控制系统成为改善交通状况的重要手段。

智能交通信号控制的意义在于:1. 提高交通效率:智能交通信号控制能够通过实时调度信号灯,减少车辆的等待时间和死循环,提高交通效率,缩短路线的通行时间。

2. 减少拥堵和排队长度:通过实时监测交通流量和疏导交通,智能交通信号控制可以减少拥堵和排队长度,提高道路通行能力。

3. 提升交通安全:智能交通信号控制可以根据实时交通情况自动调整信号灯时间和配时策略,减少交叉路口的事故发生概率,提升交通安全。

二、智能交通信号控制的工作原理智能交通信号控制的工作原理是一个复杂的系统工程,主要包括以下几个方面:1. 数据采集和处理:通过安装交通监测设备(如摄像头、传感器等),实时采集交通流量、速度和车辆类型等数据,并进行处理和分析。

2. 交通状态感知和识别:利用计算机视觉和图像处理技术,对交通场景进行感知和识别,包括车辆检测、跟踪和识别、行人检测等。

3. 交通流量预测:通过数据分析和建模,对交通流量进行预测,以便为信号控制提供参考。

4. 信号灯控制策略制定:根据实时交通情况和预测结果,制定最优的信号灯控制策略,包括信号灯绿灯时间、配时调整等。

5. 信号灯控制实施:将制定的信号灯控制策略实施到交通信号设备中,通过控制器控制交通灯的状态和时长。

6. 实时优化和调整:根据实时交通情况和反馈信息,不断优化信号控制策略,以最大程度地提高交通效率和安全性。

ADAS系统英文缩写及概念

ADAS系统英文缩写及概念

ADAS英文缩写及相关概念先进的驾驶系统(Advanced Driver Assistance Systems)即高级驾驶员辅助系统,简称ADAS,是利用安装于车上各式各样的传感器,在第一时间收集车内的环境数据,进行静、动态物体的辨识、侦测与追踪等技术上的处理,从而能够让驾驶者在最快的时间察觉可能发生的危险。

汽车高级辅助驾驶系统通常包括:GPS导航(Car navigation systems)、ITS智能交通系统(Intelligent Traffic System)、实时交通系统TMC(Traffic Message Channel),AVM全车监视系统(Around View Monitoring),AP自动泊车系统(Automatic parking)、ISA电子警察系统(Intelligent speed adaptation或intelligent speed advice)、车联网(Internet of Vehicles)、ACC自适应巡航(Adaptivecruise control)、AEB自动紧急制动(Autonomous Emergency Braking)、LDWS车道偏移报警系统(Lanedeparture warning system)、LKAS车道保持辅助系统(Lane Keeping Assist System)、FCWS前车防撞预警系统(Forward Collision Warning System)、碰撞避免或预碰撞系统(Collision avoidance system或Precrash system)、夜视系统(Night Vision System)、HBA远近光灯辅助系统(High Beam Assist)、AFS自适应前照灯系统(Adaptive Front-lighting System)、PCW行人避撞预警(Pedestrian Collision Warning)、TSR交通标志识别(Traffic sign recognition)、TLR交通信号灯识别系统(Traffic Light Recognition)、BSD盲点探测(Blind spot detection),DFM疲劳驾驶预警系统(Driver Fatigue Monitor System)、DAC下坡行车辅助控制系统(Down-hill assist control)和电动汽车报警系统(Electric vehicle warningsounds)AVM全车监视系统(Around View Monitoring)俯视停车辅助系统使用四个鱼眼或广角镜头摄像头来拍摄车辆周围的图像,并将拍摄到的4个图像转换为鸟瞰图,然后合成以上4个图像和本车俯视图并予以显示,以便在停车时提供必要的辅助。

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。

测控技术与仪器专业交通灯智能控制系统毕业论文外文文献翻译及原文

测控技术与仪器专业交通灯智能控制系统毕业论文外文文献翻译及原文

毕业设计(论文)外文文献翻译文献、资料中文题目:交通灯智能控制系统文献、资料英文题目:Intelligent Traffic Light Control 文献、资料来源:文献、资料发表(出版)日期:院(部):专业:测控技术与仪器班级:姓名:学号:指导教师:翻译日期: 2017.02.14本科生毕业设计(论文)外文文献翻译毕业设计题目:交通灯智能控制系统学院:信息科学与工程学院专业班级:测控技术与仪器外文原文Intelligent Traffic Light Control Marco Wiering, Jelle van Veenen, Jilles Vreeken, and Arne Koopman IntelligentSystems GroupInstitute of Information and Computing Sciences Utrecht UniversityPadualaan 14, 3508TB Utrecht, The Netherlandsemail:***********.nlJuly 9, 2004AbstractVehicular travel is increasing throughout the world, particularly in large urban areas.Therefore the need arises for simulating and optimizing traffic control algorithms to better accommodate this increasing demand. In this paper we study the simulation and optimization of traffic light controllers in a city and present an adaptive optimization algorithm based on reinforcement learning. We have implemented a traffic light simulator, Green Light District, that allows us to experiment with different infrastructures and to compare different traffic light controllers. Experimental results indicate that our adaptive traffic light controllers outperform other fixed controllers on all studied infrastructures.Keywords: Intelligent Traffic Light Control, Reinforcement Learning, Multi-Agent Systems (MAS), Smart Infrastructures, Transportation Research1 IntroductionTransportation research has the goal to optimize transportation flow of people and goods.As the number of road users constantly increases, and resources provided by current infrastructures are limited, intelligent control of traffic will become a very important issue in the future. However, some limitations to the usage of intelligent traffic control exist. Avoiding traffic jams for example is thought to be beneficial to both environment and economy, but improved traffic-flow may also lead to an increase in demand [Levinson, 2003].There are several models for traffic simulation. In our research we focus on microscopic models that model the behavior of individual vehicles, and thereby can simulate dynamics of groups of vehicles. Research has shown that such models yield realistic behavior [Nagel and Schreckenberg, 1992, Wahle and Schreckenberg, 2001].Cars in urban traffic can experience long travel times due to inefficient traffic light control. Optimal control of traffic lights using sophisticated sensors and intelligent optimization algorithms might therefore be very beneficial. Optimization of traffic light switching increases road capacity and traffic flow, and can prevent traffic congestions. Traffic light control is a complex optimization problem and several intelligent algorithms, such as fuzzy logic, evolutionary algorithms, and reinforcement learning (RL) have already been used in attempts to solve it. In this paper we describe a model-based, multi-agent reinforcement learning algorithm for controlling trafficlights.In our approach, reinforcement learning [Sutton and Barto, 1998, Kaelbling et al., 1996] with road-user-based value functions [Wiering, 2000] is used to determine optimal decisions for each traffic light. The decision is based on a cumulative vote of all road users standing for a traffic junction, where each car votes using its estimated advantage (or gain) of setting its light to green. The gain-value is the difference between the total time it expects to wait during the rest of its trip if the light for which it is currently standing is red, and if it is green. The waiting time until cars arrive at their destination is estimated by monitoring cars flowing through the infrastructure and using reinforcement learning (RL) algorithms.We compare the performance of our model-based RL method to that of other controllers using the Green Light District simulator (GLD). GLD is a traffic simulator that allows us to design arbitrary infrastructures and traffic patterns, monitor traffic flow statistics such as average waiting times, and test different traffic light controllers. The experimental results show that in crowded traffic, the RL controllers outperform all other tested non-adaptive controllers. We also test the use of the learned average waiting times for choosing routes of cars through the city (co-learning), and show that by using co-learning road users can avoid bottlenecks.This paper is organized as follows. Section 2 describes how traffic can be modelled, predicted, and controlled. In section 3 reinforcement learning is explained and some of its applications are shown. Section 4 surveys several previous approaches to traffic light control, and introduces our new algorithm. Section 5 describes the simulator we used for our experiments, and in section 6 our experiments and their results are given. We conclude in section 7.2 Modelling and Controlling TrafficIn this section, we focus on the use of information technology in transportation.A lot of ground can be gained in this area, and Intelligent Transportation Systems (ITS) gained interest of several governments and commercial companies [Ten-T expert group on ITS, 2002, White Paper, 2001, EPA98, 1998].ITS research includes in-car safety systems, simulating effects of infrastructural changes, route planning, optimization of transport, and smart infrastructures. Its main goals are: improving safety, minimizing travel time, and increasing the capacity of infrastructures. Such improvements are beneficial to health, economy, and the environment, and this shows in the allocated budget for ITS.In this paper we are mainly interested in the optimization of traffic flow, thus effectively minimizing average traveling (or waiting) times for cars. A common tool for analyzing traffic is the traffic simulator. In this section we will first describe two techniques commonly used to model traffic. We will then describe how models can be used to obtain real-time traffic information or predict traffic conditions. Afterwards we describe how information can be communicated as a means of controlling traffic, and what the effect of this communication on traffic conditions will be. Finally, we describe research in which all cars are controlled using computers.2.1 Modelling Traffic.Traffic dynamics bare resemblance with, for example, the dynamics of fluids and those of sand in a pipe. Different approaches to modelling traffic flow can be used to explain phenomena specific to traffic, like the spontaneous formation of traffic jams. There are two common approaches for modelling traffic; macroscopic and microscopic models.2.1.1 Macroscopic models.Macroscopic traffic models are based on gas-kinetic models and use equations relating traffic density to velocity [Lighthill and Whitham, 1955, Helbing et al., 2002]. These equations can be extended with terms for build-up and relaxation of pressure to account for phenomena like stop-and-go traffic and spontaneous congestions [Helbing et al., 2002, Jin and Zhang, 2003, Broucke and Varaiya, 1996]. Although macroscopic models can be tuned to simulate certain driver behaviors, they do not offer a direct, flexible, way of modelling and optimizing them, making them less suited for our research.2.1.2 Microscopic models.In contrast to macroscopic models, microscopic traffic models offer a way ofsimulating various driver behaviors. A microscopic model consists of an infrastructure that is occupied by a set of vehicles. Each vehicle interacts with its environment according to its own rules. Depending on these rules, different kinds of behavior emerge when groups of vehicles interact.Cellular Automata. One specific way of designing and simulating (simple) driving rules of cars on an infrastructure, is by using cellular automata (CA). CA use discrete partially connected cells that can be in a specific state. For example, a road-cell can contain a car or is empty. Local transition rules determine the dynamics of the system and even simple rules can lead to chaotic dynamics. Nagel and Schreckenberg (1992) describe a CA model for traffic simulation. At each discrete time-step, vehicles increase their speed by a certain amount until they reach their maximum velocity. In case of a slower moving vehicle ahead, the speed will be decreased to avoid collision. Some randomness is introduced by adding for each vehicle a small chance of slowing down. Experiments showed realistic behavior of this CA model on a single road with emerging behaviors like the formation of start-stop waves when traffic density increases.Cognitive Multi-Agent Systems. A more advanced approach to traffic simulation and optimization is the Cognitive Multi-Agent System approach (CMAS), in which agents interact and communicate with each other and the infrastructure. A cognitive agent is an entity that autonomously tries to reach some goal state using minimal effort. It receives information from the environment using its sensors, believes certain things about its environment, and uses these beliefs and inputs to select an action. Because each agent is a single entity, it can optimize (e.g., by using learning capabilities) its way of selecting actions. Furthermore, using heterogeneous multi-agent systems, different agents can have different sensors, goals, behaviors, and learning capabilities, thus allowing us to experiment with a very wide range of (microscopic) traffic models.Dia (2002) used a CMAS based on a study of real drivers to model the drivers’ response to travel information. In a survey taken at a congested corridor, factors influencing the choice of route and departure time were studied. The results were usedto model a driver population, where drivers respond to presented travel information differently. Using this population, the effect of different information systems on the area where the survey was taken could be simulated. The research seems promising, though no results were presented.A traffic prediction model that has been applied to a real-life situation, is described in [Wahle and Schreckenberg, 2001]. The model is a multi-agent system (MAS) where driving agents occupy a simulated infrastructure similar to a real one. Each agent has two layers of control; one for the (simple) driving decision, and one for tactical decisions like route choice. The real world situation was modelled by using detection devices already installed. From these devices, information about the number of cars entering and leaving a stretch of road are obtained. Using this information, the number of vehicles that take a certain turn at each junction can be inferred. By instantiating this information in a faster than real-time simulator, predictions on actual traffic can be made. A system installed in Duisburg uses information from the existing traffic control center and produces real-time information on the Internet. Another system was installed on the freeway system of North Rhine-Westphalia, using data from about 2.500 inductive loops to predict traffic on 6000 km of roads.中文译文智能交通灯控制马克威宁,简丽范威,吉尔威瑞肯,安瑞库普曼智能系统小组乌得勒支大学信息与计算科学研究所荷兰乌得勒支Padualaan14号邮箱:***********.nl2004年7月9日摘要世界各地的车辆运行逐渐增多,尤其是在一个大的本地区域。

城市智能交通灯系统_毕业设计论文

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。

智能交通系统英文缩写

智能交通系统英文缩写

第1章智能交通系统发展概述❝IVHS( Intelligent Vehicle-Highway System):智能车路系统❝RTI(Road Transport Informatics):道路交通信息❝ATT(Advanced Transport Telematics):先进的交通远程通讯❝ERGS(Electronic Route Guidance System):电子路线引导系统❝DRGS(Dynamic Route Guidance System):动态路线诱导系统❝CACS(Comprehensive Automobile Control System):汽车综合控制系统❝ALI(Autofahrer Leit Information System):汽车导航信息系统❝DRIVE(Dedicated Road Infrastructure for Vehicle Safety in Europe):欧洲汽车安全专用道路设施❝PROMETHEUS(PROgraMme for a European Traffic with Highest Efficiency and Unprecedented Safety):欧洲高效安全道路交通计划❝ISTEA(Intermodal Surface Transportation Efficiency Act):陆路联合运输效率法❝ERTICO(European Road Transport Telematics Implementation Coordination Organization):欧洲道路交通远程通讯执行协作组织❝VERTIS(Vehicle, Road and Traffic Intelligence Society):汽车道路交通智能化协会❝TEA-21(Transportation Equity Act for the 21st Century):21世纪交通平等法案❝PROMOTE(Programme for Mobility in Transportation in Europe):❝RACS (Road/Automobile Control System):路车间通信系统❝AMTICS (Advanced Mobile Traffic Information &Communication System):先进的汽车交通信息通信系统❝ASV (Advanced Safety Vehicle):先进安全汽车❝SSVS (Super Smart Vehicle System):高智能汽车系统❝VICS (Vehicle Information&Communication System):道路交通信息通信系统❝UTMS (Universal Traffic Management System):通用的交通管理系统❝ARTS(Advanced Road Transportation Systems):先进的道路交通系统第2章交通信息采集技术❝AVL:Automatic Vehicle location,自动车辆定位❝AVI :Automatic Vehicle Identification,自动车辆识别❝GNSS:Global Navigation Satellite System❝GPS:Global Positioning System❝DR:dead-reckoning❝RFID:Radio Frequency Identification❝RTMS:Remote Traffic Microwave Sensor,远程交通微波检测器❝VID:Video Image Detection❝FVD:Float Vehicle Data第3章交通信息传输技术❝ASK:Amplitude Shift Keyin,幅移键控❝FSK:Frequency-shift keying,频移键控❝PSK:Phase-shift keying,相移键控❝PCM:Pulse Code Modulation,脉冲编码调制❝FDM:Frequency-division multiplexing,频分多路复用❝TDM:Time Division Multiplexing,时分多路复用❝STDM:Synchronization Time-Division Multiplexing,同步时分多路复用❝ATDM:Asynchronous time Division Multiplexing,异步时分多路利用❝CDM:Code Division Multiplexing,码分多路复用❝RVC:road vehicle communication,路车通信❝DSRC:dedicated short-range communication, 专用短程通信❝OBU:On-Board Unit,车载单元❝RSU:Road-side Unit,路侧单元❝IVC:inter vehicle communication,车车通信❝RDS-TMC: radio data system-traffic message channel,数据广播系统-交通信息频道第4章交通信息处理技术❝GIS:Geographic Information Systems,地理信息系统❝AID:Automatic Incident Detection,自动事件检测第5章交通信息发布技术❝CRT:Cathode Ray Tube,阴极射线管❝PDP:Plasma Display Panel,等离子显示板❝LCD:Liquid Crystal Display,液晶显示器❝LED:light-emitting diode displays,发光二极管显示❝DMS,dynamic message sign❝VMS,variable message sign第6章交通信息利用技术❝SCATS:Sidney Coordinated Adaptive Traffic System ❝SCOOT:Split-Cycle-Offset Optimization Technique 第7章ITS体系结构❝ATMS (Advanced Traffic Management Systems)❝ATIS (Advanced Traveler Information Systems)❝APTS (Advanced Public Transportation Systems)❝CVO (Commercial Vehicle Operations)❝AVCS (Advanced Vehicle Control Systems)❝EMS (Emergency Management System)❝ETC(Electronic Toll Collection)第8章ITS的用户服务功能❝UTC(urban traffic control)❝HOV(high-occupancy vehicle)❝HOT(High Occupancy Toll)❝EPS(Electronic Payment System)❝EFC(Electronic Fee Collection)❝AFC(Automatic Fare Collection system❝VPS(Virtual positioning system)。

交通控制相关英语词汇归纳-精华归纳

交通控制相关英语词汇归纳-精华归纳
交通控制相关词汇
有关领域词汇前缀:(普通适用,但不限于此) 1. 电的… Electric, elect- 电扇- electric fan 2. 电气的... Electrical 电气工程师—electrical engineer 3. 电子的 Electronic-(E-) 电子商务 electrical business, E-business, E-police 4. 电磁的 Electro-magnetic -->电磁场 electromagnetic field 5. 光电的... photo-electric- 光(电)感应器 photo-sensor (photoelectric sensor) 6. 光学的 optical 光纤维 optical fiber 7.
一、 交通控制系统 智能交通系统 智能交通管理系统 信号控制子系统 视频检测子系统(电子警察) 流量采集子系统 交通诱导系统 指路标志 交通指挥中心 实时信息 信息技术 数据通讯技术 电子传感技术 电子控制技术 计算机处理技术 交通运输管理体系 交通运输效率 缓解交通阻塞 道路通行能力 交通事故 交通信息服务系统 实时交通信息 公共交通 交通路线 自动定位导航系统 信息采集、处理、传输
高清摄像机 标清摄像机 自动生成 违章处罚通知单 监控区域 遗漏记录 特征图像 车辆全景图像 车牌号码(信息) 车牌颜色 自动采集 车辆图像 摄像抓怕 检测抓拍 循环覆盖技术 存储设备 帧/秒 段/秒 数据包/秒 关键帧/帧相关/帧缓冲 拍摄范围 车辆超速 实时执法 布控车辆数据库 匹配比对 接触报警 日志 停车诱导系统 车辆泊位信息 有线/无线传静态显示区域 路网分布 行驶路径 空余泊位数 交通流 占有率 排队长度 环形线圈
Traffic control system Intelligent transportation system Intelligent traffic system Intelligent transportation management system Intelligent traffic management system Signal controlling subsystem Video monitoring subsystem(E-Police) Traffic flow collecting subsystem Traffic Guidance information delivering Subsystem Road sign Traffic command center Real-time information Information technology Data telecommunication technology Electronic sensor technology Electronic control technology Computer processing technology Transportation management system Transportation efficiency Alleviate traffic congestion Road capacity Traffic accident Traffic information service system Real-time traffic information Public transportation Transport route Automatic positioning and navigating system Information collection, process and transmission

交通信号智能控制系统外文文献及翻译

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。

交通行业智能交通信号系统

交通行业智能交通信号系统

交通行业智能交通信号系统智能交通信号系统(Intelligent Traffic Signal System,简称ITSS)是一种运用现代信息技术与通信技术,对路段交通流进行监测、控制与调度的系统。

它旨在提高交通管理的效率和安全性,缓解城市交通拥堵问题。

本文将探讨交通行业智能交通信号系统的原理、功能和发展前景。

一、智能交通信号系统的原理智能交通信号系统基于传感器、通信网络和控制器的相互连接,通过实时监测和分析路段交通流量、车辆速度等数据信息,进行信号灯的自动调节,以实现交通流畅和交通事故的减少。

其原理主要包括以下几个方面:1.数据采集与处理:通过在道路上安装车辆流量传感器、摄像头等设备,实时采集并处理车辆的数量、速度、车型等信息。

2.交通流分析与预测:通过对采集到的交通数据进行分析和算法模型推导,预测未来一段时间内的交通流量和交通拥堵情况。

3.信号灯控制与调整:根据交通流量和拥堵情况的预测结果,自动调整交通信号灯的配时策略,以优化路口的交通流动效果。

二、智能交通信号系统的功能智能交通信号系统具有多种功能,如下所述:1.实时交通监测:通过传感器和摄像头等设备,实时监测路口的交通流量、车辆速度等数据信息,并将数据传输至控制中心。

2.拥堵预测与缓解:通过数据分析和算法模型推导,预测未来一段时间内交通拥堵的位置和程度,并采取措施减缓拥堵状况。

3.信号灯配时优化:根据交通流量和拥堵情况的变化,智能交通信号系统可以自动调整信号灯的配时策略,以最大程度减少交通拥堵。

4.智能交通调度:通过数据分析和交通模型优化,对整个城市或路段的交通流进行调度和管理,提高道路的通行效率和交通系统的整体性能。

三、智能交通信号系统的发展前景智能交通信号系统作为一种先进的交通管理技术,具有广阔的发展前景和应用空间。

以下是其发展前景的几个方面:1.人工智能与大数据:随着人工智能和大数据技术的快速发展,智能交通信号系统可以更加准确地预测和分析交通流量,实现更高效的交通调度和管理。

交通信号智能控制系统外文文献及翻译.doc

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。

智能照明控制系统 外文翻译

智能照明控制系统 外文翻译

智能照明控制系统外文翻译XXX of "pre-set" control modes and components to accurately set up and manage XXX。

the system takes advantageof natural outdoor light and only uses the necessary amount of energy to achieve the required brightness。

XXX-saving effect of more than 30%.1.2Bus-type star-shaped structureThe XXX control system is based on a bus-type star-shaped structure。

which allows for easy XXX control。

The system can be easily connected to us sensors and control components。

making it suitable for a wide range of ns.2.Advantages of XXX systemXXX XXX control system has several advantages。

including:2.1 Good XXX-saving effectAs ned earlier。

the system can achieve a clear XXX-saving effect of more than 30% by utilizing natural outdoor light and only using the necessary amount of energy to achieve the required brightness.2.2 Flexible controlThe system is based on a bus-type star-shaped structure。

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

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。

《交通设计手册》第八章智能交通系统翻译

《交通设计手册》第八章智能交通系统翻译

专业英语翻译文献摘自《交通设计手册》第八章智能交通系统CHAPTER 8 INTELLIGENT TRANSPORTATION SYSTEMS8.0 INTRODUCTIONThis Chapter of the Tennessee Department of Transportation Traffic Design Manual will be used to address policies, guidelines, standard procedures, etc. related to Intelligent Transportation Systems (ITS) and the Systems Engineering Analysis (SEA) documentation.TDOT' s Intelligent Transportation System is referred to as the TDOT SmartWay. It is designed to reduce traffic congestion by decreasing incident clearance time, increase safety by decreasing the number of secondary accidents, and, working alongside our incident management program (HELP), improving emergency response to traffic situations. TDOT SmartWay uses cameras to monitor the highways from Traffic Management Centers, sensors to gauge traffic flow, large electronic message signs to send urgent traffic notices to drivers along the highways and the Highway Advisory Radio system to alert motorists of important information. Nashville, Knoxville, Memphis, and Chattanooga have fully integrated TDOT SmartWay systems.TDOT SmartWay advanced information technologies take many forms such as:Roadway Traffic Sensors to report traffic counts, speed and travel time;Camera Video Surveillance to monitor freeway traffic flows and provideimproved incident management capabilities;Dynamic Message Signs to provide real-time traffic, construction, and weatherinformation to motorists, as well as provide information on Amber Alerts;Highway Advisory Radio to provide urgent real-time traffic, construction, andweather information to motorists via AM radio, as well as provide information on Amber Alerts;HELP Freeway Service Patrols to reduce congestion by removing minor incidents in a timely fashion;Transportation Management Centers (TMC) serve as a central location fortraffic management operations and communications in their respective Regions;Incident Management to detect, verify, and respond to incidents in an efficientmanner and manage traffic conditions around the incident site;Construction Information is provided to advise motorists traveling throughconstruction sites;TDOT SmartWay Information System (TSIS) is a system communicating datafrom TDOT SmartWay devices to a central location and distributing that transportation information to motorists and other interested parties before and while making t rips. Information is distributed via TDOT ' s Web site and through the media. TDOT also provides motorist information on Tennessee 511, a component of TDOT SmartWay.Information on Weather-Related Road Conditions informs travelers where problems may exist onany state road due to severe weather conditions.While the potential of ITS is significant, deployment and operation of these systems requires specialized coordination, design, device specifications, procurement / construction, operations management, and maintenance. The TDOT Design Divisionshall provide implementation plans for ITS and policies for ITS operation.8.1 23 CFR 940 COMPLIANCE8.1.1 INTRODUCTION AND SCOPEThese requirements apply to Federal Aid projects, as required by Federal Highway Administration, Department of Transportation 23 CFR Part 940. State-funded projects will follow the same process for consistency.In accordance with 23 CFR 940, ITS projects funded through the highway trust fund shall conform to the National ITS Architecture and applicable standards. 23 CFR 940 also stipulates that“ conformance with the National ITS Architecture is interpreted to mean the use of the National ITS Architecture to develop a Regional ITS Architecture, as applicable, and the subsequent adherence of all ITS projects to that Regional ITS Architecture. ”This chapter outlines the TDOT procedures forimplementing these requirements. The level of documentation should be commensurate with the project scope.8.1.2 GENERAL CRITERIAIn accordance with 23 CFR 9 40.3, an ITS project is “ any project that in whole orin part funds the acquisition of technologies or systems of technologies that provide or significantly contribute to the provision of one or more ITS user services as defined in the National ITS Archite cture ” . Any reference to the ITS Architecture in this document refers to Statewide and Regional Architectures. The following required documentation shall be completed by staff that has qualified ITS experience. They shall have completed a Systems Engineering Analysis on at least (3) projects, including at least one project that meets the high risk level criteria.In Tennessee, a project would be considered to be an ITS project if it meets any of the following: It requires the integration of multiple separate systems;It is a project that has significant potential to involve the integration of technologies on a multi-jurisdictional level;It replaces existing or installs new centrally controlled software.ITS Projects may be either High Risk, Low Risk, or Exempt ITS Projects. The SEA development process is different for each category.The following describes the categories of ITS projects in Tennessee: High Risk,Low Risk, and Exempt . The decisive factor in this determination is the scale and complexity of the project. Traffic Signal projects are the most common scale sensitive projects. The nature of the engineering development for ITS projects implies a greater risk and uncertainties to successful completion. Project risk may be defined in terms of schedule, cost, quality, and requirements. These risks can increase or decrease significantly based on several identified factors associated with ITS projects.The factors are:Number of jurisdictions and modes;Extent of software creation;Extent of proven hardware and communications technology used; Number and complexity ofnew interfaces to other systems; Level of detail in requirements and documentation; Level of detail in operating procedures and documentation; Service life of technology applied toequipment and software.Generic criteria for the determination of risk are shown in the list below. Technology: functions are not fully identified, user interface not right, unrealistic technical requirements, componentshortcomings; People: personnel shortfalls;Physical Environment: external dependencies, device placement;Political Environment: adding requirements that are not tied to a need, do you have a champion;Contract Issues: unrealistic schedules and budgets, requirements change; Additional RiskFactors are shown in Table 8.1.8.1.3 HIGH RISK ITS PROJECTSA High Risk ITS project is an ITS project that implements part of a regional ITS initiative that is multijurisdictional, multi-modal, or otherwise affects regional integration of ITS. Multi-jurisdictional does not necessarily mean that a project with termini in more than one city is High Risk ITS. The key criteria is TS “ Regional I initiative. ”High Risk ITS projects have one (or more) of the following characteristics: Multi-Jurisdictional or Multi-modal;Custom software is required; Hardware and Communications are “ cu-ettdingge ” or not in common use;New interfaces to other systems are required;System requirements not detailed or not fully documented; Operating procedures not detailed or not fully documented; Technology service life shortens project life-cycle.The following are examples of High Risk ITS projects: TDOT SmartWay (if additional functionality is to be added); Traffic Signal systems scoped to be centrally controlled (Closed loop systems are NOT central control systems);Traffic signal projects that require the integration of signal systems with TDOT SmartWay, an Arterial Management System, or RWIS systems;An ITS system that involves multiple political jurisdictions;Regional Transit Systems;Transit Signal Priority Systems.8.1.4 LOW RISK ITS PROJECTSLow-Risk ITS projects are often referred to as ITS infrastructure expansion projects.Low Risk ITS projects will have all of the following characteristics:Single jurisdiction and single transportation mode (highway, transit, or rail);No software creati on —commercial-off-the-shelf (COTS) or prove n software;Proven COTS hardware & communications technology;No new interfaces;System requirements fully detailed in writing;Operating procedures fully detailed in writing;Project life-cycle not shortened by technology service life.The following are examples of Low Risk ITS projects:Traffic signals with emergency vehicle preemption;Roadway Weather Information System (RWIS);Parking Management Systems;Various surveillance or control systems that could functionally be integratedinto a Freeway Management System;Expanding existing communications systems —this consists of extendingexisting fiber-optic or wireless communications systems, using the same technology andspecifications as the preexisting system;Leasing turnkey services only (e.g., website-based information service) —with no hardware or software purchases.8.1.5 EXEMPT ITS PROJECTSExempt ITS projects do not require a Systems Engineering Analysis (SEA). All activities of the traditional roadway project development life-cycle process will be followed. No further ITS-specific action is necessary.Exempt ITS projects can be classified into two categories:An exempt ITS project is one that does not use federal funding;ITS System expansions that do not add new functionality. In other words, a project that by itself may have been considered high or low risk, but if the scope of the project simply expands this system it can be considered Exempt.The following are examples of Exempt ITS projects:Upgrades to an existing traffic signal —This may include, for example, adding or revising left turn phasing or other phasing, adding pedestrian-crossing displays;Installing an “isolated ” trafficThs i sgnisala signal n—ot connected to any type of external signal-control system, nor likely to be in the future because of its isolation;The project adding new intersections could be considered Exempt because it is an expansion of an existing system within the same jurisdiction with no new functionality.A signal interconnect project that uses existing software and is on an isolatedcorridor connecting multiple signals;Traffic sig nal timi ng projects -This in eludes all “ studies ” whose purpose is tocha nge the coord in ati on parameters for con trolli ng a group of sig nals —but with no installation of new hardware or software;A project to add DMS devices to SmartWay with existi ng DMS devices could be con sidered an Exempt project;Studies, Pla ns, An alyses —This in cludes ITS Master Pla ns, Deployme nt Pla ns,Tech no logy Studies, etc. whose product is on ly a docume nt, with no new hardware or software in stalled;Routi ne Operati ons —This in cludes operati ng and maintaining any ITS eleme nts or systems -aga in with no new hardware or software in stalled.第八章智能交通系统8.0介绍在这一章里,田纳西交通部交通设计手册将用来应对政策、指导方针、标准程序等与智能交通系统(ITS)和系统工程分析(SEA文件。

AIGC智能交通信号控制的新方案

AIGC智能交通信号控制的新方案

AIGC智能交通信号控制的新方案智能交通信号控制系统(Intelligent Traffic Signal Control,简称ITS)是为解决城市交通拥堵、提高道路通行效率而设计的一种新型交通管理系统。

在过去的几十年里,由于城市化进程的加速以及私家车的普及,交通拥堵已成为制约城市发展的一个重要因素。

为了解决这一问题,各种交通信号控制系统相继出现,但是其效果并不理想。

为了改变这种局面,AIGC公司推出了一种创新的智能交通信号控制方案。

AIGC智能交通信号控制方案的核心是利用人工智能技术进行信号灯的优化控制。

传统的交通信号控制主要是根据固定的时序来控制信号灯的切换,但是这种方式无法适应道路交通的实际情况。

而AIGC的新方案则是利用大数据和机器学习技术对交通流量进行实时监测与分析,并根据分析结果自动调整信号灯的时序,以最大程度地提高交通的通行效率。

此外,AIGC的智能交通信号控制方案还具备以下特点:1. 实时响应能力:借助先进的传感器技术,AIGC系统能够实时监测道路上的交通情况,并根据实时数据进行信号灯的调整。

这意味着交通信号可以根据实际情况进行动态变化,最大化地适应交通流量的变化。

2. 交通流优化:AIGC系统通过算法模型不断学习和优化,可以根据历史数据及时发现并解决交通瓶颈,提高交通运输效率。

它不仅可以根据交通状况进行信号灯的优化控制,还能够预测交通流量的变化,从而采取相应的措施来引导交通。

3. 多元交通模式:AIGC的智能交通信号控制方案不仅适用于汽车交通,还适用于其他交通模式,如公交车、自行车和行人。

通过综合考虑各种交通模式,AIGC系统可以更加全面地进行交通信号的控制,提高道路的通行效率和安全性。

4. 接入性强:AIGC系统可以与现有的交通基础设施进行无缝对接,无需对整个交通系统进行大规模改造。

这一特点使得AIGC系统的部署和应用更加便捷和经济。

总结起来,AIGC智能交通信号控制方案通过采用人工智能技术和大数据分析手段,实现了交通信号的智能化控制。

智能交通英语词汇

智能交通英语词汇

JJitney 随停公车;简便公车Job Mix Formula 工地拌合公式Joint Opening 开口宽度;Joint Operation of Transport 联运Jointed Concrete Pavement JCP 接缝式混凝土铺面Jointed Reinforced Concrete Pavement JRCP 接缝式钢筋混凝土铺面Joule 焦耳(能量单位)Journal Resistance 轴颈阻力Jumbo 钻堡Junction 路口Junction box 汇流井KKalman filter algorithm 卡门滤波法Kalman filter, Kalman filtering 卡门滤波Keep right sign 靠右标志Key count station 关键调查站Kinematic Viscosity 动黏度Kink 纽结Kiss-and-Ride 停车转乘Kneading Action 辗挤作用Knot 节(等于每小时1.85公里)Knowledge Base 知识库Kurtosis 峰度LLag 间距Lag time 延迟时间Land Access 可及性Land Expropriation 土地征收Land Transportation 陆路运输Land use 土地使用;土地利用Landfill site 掩埋场Landscape design 景观设计Landslide/Slump 坍方Lane, traffic lane 车道Lane 巷道Lane allocation, Lane layout 车道配置Lane Balance 车道平衡Lane change 变换车道Lane control 车道管制Lane distribution 车道分布Lane Group 车道群Lane headway 车道行进间距Lane Line 车道线Lane Reduction Transition Line 路宽渐变线Lane residual width 巷道剩余宽度Lane Width 车道宽度Lane-direction control signal 车道行车方向管制号志Large Network Grouping 大型网络群组划分Large Passenger Vehicle 大客车Large-area Detector 大区域侦测器Latent travel demand 潜在旅次需求Lateral Acceleration 横向加速率Lateral clearance 侧向净距Lateral Collision Avoidance 侧向防撞Lateral Separation 左右隔离Lateral shift 侧向位移Laws of randomness 随机定理Lay-Down Vehicle Days 停驶延日车数Leading 绿灯早开Leading & lagging design 早开迟闭设计Leading Car 领导车Leading design 早开设计Learning Permit 学习驾照Lease 租赁Left turn 左转Left turn accel-decel & storage lane island 左转加减速-停储车道式分向岛Left turn acceleration lane island 左转加速车道式分向岛Left turn crossing 左转交叉穿越Left turn lane 左转车道Left turn maneuver 左转运行Left turn on red 在红灯时段内进行左转运行Left turn waiting zone 左转待转区Left turning vehicle 左转车辆Leg 路肢Legibility 公认性;易读性Length 长度Length of Economical Haul 经济运距Length of grade 坡长Length of lane change operation 变换车道作业的长度Length of Superelevation Runoff 超高渐变长度Length of time parked 停车时间的久暂Level 水准仪;横坑;水平面Level Crossing 平面交叉Level of illumination 明亮度水准Level of Service 服务水准Level or flat terrain 平原区Level surface 水准面Leveling Course 整平层License Plate 汔车号牌License Plate Method 牌照法License Suspension 吊扣驾照License Termination 吊销License Plate 汽车号牌License plate method 车辆牌照记录法;车辆牌照法License Plate Recognition 车牌辨识License renewal method 换照法Life cycle assessments LCA 生命周期评估Lift-On/Lift-Off 吊上吊下式Light Characteristics 灯质Light List 灯质表Light Motorcycle 轻型机踏车Light on method 亮灯法Light Phase 灯相Light Rail Rapid Transit LRRT 轻轨捷运Light Rail Transit LRT 轻轨运输Light Truck 小货车Lighting System 灯光系统Limited purpose (parking) survey 局部目的(停车)调查Line Capacity 路线容量Line marking 标线Linear Referencing System 线性参考系统Linear Shrinkage 线收缩Linear-Induction Motor LIM 线性感应马达Linear-Synchronous Motor LSM 线性同步马达Link arrival rate 路段流量到达率Link flow 路段流量Link performance function 道路绩效函数Linked or coordinated signal system 连锁号志系统Lip Curb 边石Liquidate 变成液体:偿还:破产Liquidated Damage 违约罚金Load Equivalent Factor LEF 荷重当量系数;载重当量因素Load Factor 负荷指数Load limit 载重限制Load Safety Factor 载重安全因素Loading 载重Loading & unloading 装卸Loading & unloading zone 上下旅客区段或装卸货物区段Loading Island 旅客上下车的车站岛Local Area Network LAN 局域网络Local Controller 路口控制器Local street 地区性街道Local traffic 地区性交通Local transmission network 区域传输网络Localizer 左右定位台Location file 地点档案Location of stop 站台设置位置Locked Joint 连锁接头Log Likelihood Function 对数概似函数Logical Architecture 逻辑架构Logit Model 罗吉特模式Logo 标记;商标Long Loop 长线圈Long tunnel 长隧道Long tunnel system 长隧道系统Long vehicle tunnel 车行长隧道Long-chord 长弦Longitude 经度Longitudinal Collision Avoidance 纵向防撞Longitudinal distribution of vehicle 车辆的纵向分布Longitudinal Drain 纵向排水Longitudinal Grade 纵坡度Longitudinal Joint 纵向接缝Longitudinal Separation 前后隔离Longitudinal Slope For Grade Line 纵断坡度Longitudinal ventilation 纵流式通风Longitudinal Warping 纵向扭曲Long-Range Planning 长程规划Long-term scour depth 长期冲刷深度Loop 环道(公路方面);回路(电路方面)Loop Detector 环路型侦测器Loop inductance 感应回路Los Angeles Abrasion Test 洛杉矶磨耗试验Lost Time 损失时间Louvers of Daylight Screening Structure 遮阳隔板Low beam 近灯Low Heat 低热Low or first gear 低速檔Low Pressure Sodium Lamp 低压钠气灯Low relative speed 低相对速率Low Truss 低架式Lumen 流明Luminance 辉度Luminaire 灯具Luminous Efficiency of a Source 光源效应Luminous flux 光流;光束Luminous Intensity 光度;光强度Lux 勒克斯MMacro or mass analysis 汇总分析;宏观分析Macroscopic 巨观Magnetic detector 电磁(磁性)侦测器Magnetic Levitation Maglev 磁浮运输系统Magnetic loop detector 磁圈侦测器Magnitude 规模Mainline 主线Maintenance Factor 维护系数Maintenance Work 养护工程Major flow 主要车流Major parking survey 主要停车调查Major Phase 主要时相Management Information Base MIB 网管信息库(管理讯息库)Management Information System MIS 管理信息系统Maneuverability 运行性Manhole 人孔;井Man-machine driving behavior 人机驾驶行为Man-machine interaction 人机互动Manual counts 人工调查法Map Matching Method 地图配对法Map scale 图比例尺Marginal vehicle 边际车辆Marker 标物;标记Market Package 产品组合Market Segment 市场区隔Marking 标线Marshaling Yard 货柜汇集场Marshall Test 马歇尔试验Mass Diagram 土积图Mass transportation 大众运输Match Fund 配合款Master 主路口Master controller 主要(总枢纽)控制器Master Node 主控制点Master Plan 主计画Material handling 物料搬运Maturity 成熟程度Max out 绿灯时间完全使用之现象Maximum allowable gradient 最大容许坡度Maximum Allowable Side Friction Factor 最大容许侧向摩擦系数Maximum Arterial Flow Method 最大干道流量法Maximum capacity 最大容量Maximum Density 最大密度Maximum flow rate 最大流率Maximum Grade 最大坡度Maximum individual delay 最大个别延滞Maximum Likelihood Function 最大概似法Maximum Load Section MLS 最大承载区间Maximum Peak Hour Volume 最尖峰小时交通量Maximum possible rate of flow 最大可能车流率Maximum queue 最大等待量(车队长度)Maximum Theoretical Specific Gravity 最大理论比重Mean Absolute Value of Error MAE 平均绝对误差Mean deviation 平均差Mean difference 均互差Mean Square Error MSE 平均平方误差Mean variance 离均差Mean velocity 平均速度Measure of Effectiveness MOE 绩效评估指针Mechanic License 技工执照Mechanical counter 机械式计数器Mechanical garage 机械式停车楼(间)Mechanical Kneading Compactor 揉搓夸压机Mechanical Load-Transfer Devices 机械传重设备Mechanical parking 机械停车Mechanical power 机械动力Median 中央分隔带;中央岛Median (50th percentile) speed 中位数速率;第50百分位数速率Median Bus Lane 设于道路中央之公车专用车道Median conflicts 中央冲突点Median Curing Cutback Asphalt MC 中凝油溶沥青Median island 中央岛Million Vehicles Kilometer MVK 百万车公里Median opening 中央分向岛缺(开)口Medium Distribution 中分布Memorandum of Understanding MOU 备忘录Mental factor 精神因素Mercury Vapor Lamp 水银蒸汽灯Merge 合并;并流;进口匝道;并入Merging area 并流区域Merging behavior 并入行为Merging conflicts 并流冲突点Merging maneuver 并流运行Merging of traffic 交通汇流Merging point 并流点Merging traffic 汇合交通Message Set 讯息集Metadata 诠释资料Metered Freeway Ramp 匝道仪控Metering rate 仪控率Metropolitan Planning Area 大都会规划区Micro or spot analysis 重点分析;微观分析Microwave Beacon 微波信号柱Mid-block (bus) stop 街廓中段公车站台Mid-block delay 街廓中段延滞Mid-Block Flow 中途转入流量Middle Ordinate 中距Mide-Block 街廓中央停靠方式Mile Per Gallon MPG 每加仑油量可跑的英哩数Milled Materials 刨除料Million Vehicles Kilometer MVK 百万车公里Mini car 迷你车Minibus 小型公车Minimum Curve Length 曲线之最短Minimum Design for Turning Roadway 转向道之最小设计Minimum Grade 最小纵断坡度Minimum Green Time 最短绿灯时间Minimum Phase Time 最短时相时间Minimum running time 最短行车时间Minimum separation 最小间距Minimum sight triangle 最小视界三角形Minimum speed limit 最低速率Minimum turning radius 最小转弯半径Minimum-speed curve 最低速率曲线Minor flow 次要车流Minor Phase 次要时相Minor street 次要道路Mix Design 配合设计Mixed fleet 混合车队Mixed fleet operation 混合车队营运Mixed flow, Mixed traffic, Mixed traffic flow 混合车流Mobile Communications 行动通讯Mobile Data 行动数据Mobile Data Network 行动数据网络Mobile Plant 移动式厂拌;活动式厂拌Mobile radio unit 车装式无线电话机Mobility 可行性Modal Split 运具分配Mode 运具Model traffic ordinance 模范交通条例Modem 通讯解调器Modular 模块化Modulus of Elasticity 弹性系数Modulus of Rupture 破裂模数Modulus of Subgrade Reaction 路基反应系数Moment of inertia 惯性力矩Monitoring 监测Monorail 单轨铁路Mortality 死亡数Motivation 动机Motor License 行车执照Motor transport service 汽车运输业Motor vehicle code 机动车辆规范Motorcycle lane 机车道Motorcycle user 机车使用者Motorcycle waiting zone 机车停等区Motorcyclist 机车驾驶人Motorcyclist Safety 机车骑士安全Mountable Curb or Rolled Curbs 可越式绿石Mountain road 山区道路Mountain terrain 山岭区Mounting height 装设高度Movement Distribution 流向分配Movement-Oriented 流动导向Moving belt 输送带Muck 碴Mud 泥浆Multi-Trip Ticket 多程票或回数票Multicommodity flow problem 多商品流量问题Multicommodity network flow problem 多重货物网络流动问题Multi-function Alarm Sign 多功能警示标志Multilane highway 多车道公路Multi-lane rural highway 多车道郊区公路Multilayer 多层Multileg Interchange 多路立体交叉Multileg Intersection 多路交叉Multimodal 多运具的Multimode mixed traffic 多车种车流Multi-parameter detector 多参数侦测器Multi-path effect 多路径效应Multipath Traffic Assignment Model 多重路线指派模式Multiperiod 多时段Multiple commodity network flow problem 多重商品网络流动问题Multiple cordon survey 多环周界调查Multiple network flow problem with side constraint 含额外限制多重网络流动问题Multiple turning lane 多线转向车道Multiple use area 多用途空间Multiple user classes 多种用路人Multiple-ride-ticket 回数票Multistories or multifloor garage 高楼停车间Multi-Tasking 多任务作业NNaphtha 石脑油National Cooperative Highway Research Program NCHRP 美国公路合作研究组织群National freeway 国道National Freeway Construction & Management Fund 国道公路建设管理基金National freeway network 国道路网National System Architecture 国家级架构National System of Interstate and Defense Highway 洲际国防公路Native Asphalt 天然沥育Natural (normal) distribution 自然(常态)分布Natural Disaster Traffic Management 自然灾害交通管理Natural moisture content 自然含水量Natural path 自然迹线Natural Rubber Latex 天然橡胶流质Natural Subgrade 天然路基Natural ventilation 自然通风Natural ventilation effect 自然通风效应Navigation 引导;导航Near-Side 路口近端Near-side bus stop 近端公车停靠站台Neon regulatory sign 霓虹式禁制标志Net Tractive Effort 净牵引力Net Weight 净重Network 网络New Jersey concrete barrier 纽泽西混凝土护栏Night visibility 夜间可见(视)性Night vision 夜间视力Nighttime driving 夜间驾驶Nitrogen Oxides NOX 氧化碳No left turn 不准左转;请勿左转No parking 禁止停车No parking on yellow line 禁止停车黄线No passing zone 不准超车区段No passing zone marking 不准超越地带标线No right turn 不准右转;请勿右转No standing on red line 禁止临时停车红线No turning 不准转向运行No U-turn 不准回转;请勿回转Noise 噪音Noise analysis 噪音分析Noise barrier, Sound insulating wall 隔音墙Noise control 噪音控制Noise induced annoyance 噪音干扰Noise intensity 噪音强度Noise Level 噪音水准Noise pollution 噪音污染Noise prevention 噪音防制Noise sensitive area 噪音敏感地区Nomograph 换算图Non-collision accident 非碰撞性肇事Non-Cutoff 无遮被型Non-Cutoff type NC/O 无遮蔽型Nonfatal Injury 非致命性的伤害Nonhomogeneous flow 不同流向的车流;非均质车流Non-Motorist 非机动车使用者(如行人)Non-Overlap 非重叠时相Nonpassing Sight Distance 不超车视距Non-Recurrent Congestion 非重现性交通壅塞Non-road user 非用路者Nonskid Surface Treatment 防滑处理Nonsynchronous controller 异步控制器No-Passing Zone Markings 禁止超车路段线Normal Crown NC 正常路拱Not approved 认定不应开发Novelty 新奇性Number of accident 肇事件数Number of conflict 冲突点数目Number of fatality 死亡人数Number of injury 受伤人数Number of Operating Vehicles 营业车辆数Number of parking spaces 停车车位数Number of Passengers 客运人数Number of Registered Vehicle 车辆登记数Numbers 要求之重复Numerical speed limit 数值速率限制Nurture room 育婴室来源:智能交通观察() 原文链接:/library/html/8914/加载数据网站地图| 设为首页| 加入收藏首页┆资讯┆技术┆ITS人物┆产品┆公司┆解决方案┆应用案例┆ITS文库┆下载┆视频┆问吧┆论坛首页交通规划城市规划智能交通公共交通物流运输交通经济静态交通组织管理交通统计3S技术企业管理交通管理新闻搜索产品搜索企业搜索软件搜索视频搜索热门标签:智能交通(13) 电子警察(9) ETC(7) 不停车收费系统(5) 英语词汇(3) 交通事故(2) 当前位置:智能交通观察→ITS文库→交通管理→交通控制交通控制英语词汇大全作者:ITS观察来源: 日期:2009-04-02 交通新闻投稿智能交通论坛智能交通观察网推荐您阅读:交通控制英语词汇大全Stop-line——停车线A congested link——阻塞路段Weighting factor——权重因子Controller——控制器Emissions Model——排气仿真the traffic pattern——交通方式Controller——信号机Amber——黄灯Start-up delay——启动延误Lost time——损失时间Off-peak——非高峰期The morning peak——早高峰Pedestrian crossing——人行横道Coordinated control systems——协调控制系统On-line——实时Two-way——双向交通Absolute Offset——绝对相位差Overlapping Phase——搭接相位Critical Phase——关键相位Change Interval——绿灯间隔时间Flow Ratio——流量比Arterial Intersection Control 干线信号协调控制Fixed-time Control——固定式信号控制Real-time Adaptive Traffic Control——实时自适应信号控制Green Ratio——绿信比Through movement——直行车流Congestion——阻塞,拥挤The percentage congestion——阻塞率The degree of saturation——饱和度The effective green time——有效绿灯时间The maximum queue value——最大排队长度Flow Profiles——车流图示Double cycling——双周期Single cycling——单周期Peak——高峰期The evening peak periods——晚高峰Siemens——西门子Pelican——人行横道Fixed time plans——固定配时方案One-way traffic——单向交通Green Ratio——绿信比Relative Offset——相对相位差Non-overlapping Phase——非搭接相位Critical Movement——关键车流Saturation Flow Rate——饱和流率Isolated Intersection Control——单点信号控制(点控)Area-wide Control——区域信号协调控制Vehicle Actuated (VA)——感应式信号控制The Minimum Green Time——最小绿灯时间Unit Extension Time——单位绿灯延长时间The Maximum Green Time——最大绿灯时间Opposing traffic——对向交通(车流)Actuation——Control——感应控制方式Pre-timed Control——定周期控制方式Remote Control——有缆线控方式Self-Inductfanse——环形线圈检测器Signal——spacing——信号间距Though-traffic lane——直行车道Inbound——正向Outbound——反向第一章交通工程——Traffic Engineering运输工程——Transportation Engineering铁路交通——Rail Transportation航空交通——Air Transportation水上交通——Water Transportation管道交通——Pipeline Transportation交通系统——Traffic System交通特性——Traffic Characteristics人的特性——Human Characteristics车辆特性——Vehicular Characteristics交通流特性——Traffic Flow Characteristics道路特性——Roadway Characteristics交通调查——Traffic Survey交通流理论——Traffic Flow Theory交通管理——Traffic Management交通环境保护——Traffic Environment Protection 交通设计——Traffic Design交通统计学——Traffic Statistics交通心理学——Traffic Psychology汽车力学——Automobile Mechanics交通经济学——Traffic Economics汽车工程——Automobile Engineering人类工程——Human Engineering环境工程——Environment Engineering自动控制——Automatic Control应用数学——Applied Mathematics电子计算机——Electric Computer第二章公共汽车——Bus无轨电车——Trolley Bus有轨电车——Tram Car大客车——Coach小轿车——Sedan载货卡车——Truck拖挂车——Trailer平板车——Flat-bed Truck动力特性——Driving Force Characteristics牵引力——Tractive Force空气阻力——Air Resistance滚动阻力——Rolling Resistance坡度阻力——Grade Resistance加速阻力——Acceleration Resistance附着力——Adhesive Force汽车的制动力——Braking of Motor Vehicle自行车流特性——Bicycle flow Characteristics 驾驶员特性——Driver Characteristics刺激——Stimulation感觉——Sense判断——Judgment行动——Action视觉——Visual Sense听觉——Hearing Sense嗅觉——Sense of Smell味觉——Sense of Touch视觉特性——Visual Characteristics视力——Vision视野——Field of Vision色彩感觉——Color Sense眩目时的视力——Glare Vision视力恢复——Return Time of Vision动视力——Visual in Motion亮度——Luminance照度——Luminance反应特性——Reactive Characteristics刺激信息——Stimulant Information驾驶员疲劳与兴奋——Driving Fating and Excitability 交通量——Traffic Volume交通密度——Traffic Density地点车速——Spot Speed瞬时车速——Instantaneous Speed时间平均车速——Time mean Speed空间平均车速——Space mean speed车头时距——Time headway车头间距——Space headway0交通流模型——Traffic flow model自由行驶车速——Free flow speed阻塞密度——Jam density速度-密度曲线——Speed-density curve流量-密度曲线——Flow-density curve最佳密度——Optimum concentration流量——速度曲线——Flow-speed curve最佳速度——Optimum speed连续流——Uninterrupted traffic间断流——Interrupted traffic第三章交通调查分析——Traffic survey and analysis交通流调查——Traffic volume survey车速调查——Speed survey通行能力调查——Capacity survey车辆耗油调查——Energy Consumption Survey居民出行调查——Trip Survey车辆出行调查——Vehicle Trip Survey停车场调查——Parking Area Survey交通事故调查——Traffic Accident Survey交通噪声调查——Traffic Noise Survey车辆废气调查——Vehicle Emission Survey平均日交通量——Average Daily Traffic(ADT)周平均日交通量——Week Average Daily Traffic月平均日交通量——Month Average Daily Traffic年平均日交通量——Annual Average Daily Traffic高峰小时交通量——Peak hour Volume年最大小时交通量——Highest Annual Hourly Volume年第30位最高小时交通量——Thirtieth Highest Annual Hourly Volume 高峰小时比率——Peak Ratio时间变化——Time Variation空间变化——Spatial Variation样本选择——Selection Sample样本大小——Size of Sample自由度——Freedom车速分布——Speed Distribution组中值——Mid-Class Mark累计频率——Cumulative Frequency频率分布直方图——Frequency Distribution Histogram85%位车速——85% Percentile Speed限制车速——Regulation Speed服务水平——Level of Service牌照对号法——License Number Matching Method跟车测速——Car Following Method浮动车测速法——Moving Observer Speed Method通行能力调查——Capacity Studies饱和流量——Saturation Flow第四章泊松分布——Poisson Distribution交通特性的统计分布——Statistical Distribution of Traffic Characteristics 驾驶员处理信息的特性Driver Information Processing Characteristics跟车理论——Car Following Theory交通流模拟——Simulation of Traffic Flow间隔分布——Interval Distribution二项分布——Binomial Distribution拟合——Fitting移位负指数分布——Shifted Exponential Distribution排队论——Queuing Theory运筹学——Operations Research加速骚扰——Acceleration Noise停车波——Stopping Wave起动波——Starting Wave第五章城市交通规划——Urban Traffic Planning土地利用——Land-Use可达性——Accessibility起讫点调查——Origin –Destination Survey出行端点——Trip End期望线——Desire Line主流倾向线——Major Directional Desire Line调查区境界线——Cordon Line分隔查核线——Screen Line样本量——Sample Size出行发生——Trip Generation出行产生——Trip Production出行吸引——Trip Attraction发生率法——Generation Rate Method回归发生模型——Regression Generation Model类型发生模型——Category Generation Model出行分布——Trip Distribution现在型式法——Present Pattern Method重力模型法——Gravity Model Method行程时间模型——Travel Time Model相互影响模型——Interactive Model分布系数模型——Distribution Factor Model交通方式划分——Model Split , Mode Choice转移曲线——Diversion Curve交通量分配——Traffic Assignment最短路径分配(全有全无)Shortest Path Assignment(All-or-Nothing)多路线概率分配Probabilistic Multi-Route Assignment线权——Link Weight点权——Point Weight费用——效益分析——Cost –benefit Analysis现值法——Present Value Method第六章交通安全——Traffic Safety交通事故——Traffic Accident交通死亡事故率——Traffic Fatal-Accident Rate交通法规——Traffic Law多发事故地点——High accident Location交通条例——Traffic Regulation交通监视——Traffic Surveillance事故报告——Accident Report冲撞形式——Collision Manner财产损失——Property Damage事故档案——Accident File事故报表——Accident Inventory固定目标——Fixed Object事故率——Accident Ratelxy事故数法——Accident Number Method 质量控制法——Quality Control Method 人行横道——Pedestrian Crosswalk 行人过街道信号——Pedestrian Crossing Beacon 人行天桥——Passenger Foot-Bridge 人行地道——Passenger Subway 栅栏——Gate 立体交叉——Underpass(Overpass) 标线——Marking 无信号控制交叉口——Uncontrolled Intersection 让路标志——Yield Sign 停车标志——Stop Sign 渠化交通——Channelization traffic 单向交通——One-Way 禁止转弯——No Turn Regulation 禁止进入——No-Entry 禁止超车——Prohibitory Overtaking 禁止停车——Prohibitory Parking 禁止通行——Road Closed 安全带——Life Belt 第七章交通控制与管理——Traffic Control and Management 交通信号——Traffic Signal 单点定时信号——Isolated Pre-timed Signal 信号相位——Signal Phase 周期长度——Cycle Length 绿信比——Split 优先控制——Priority Control 延误——Delay 流量比——Flow Ratio 有效绿灯时间——Effective Green Time 损失时间——Loss Time 绿灯间隔时间——Intergreen Interval 信号配时——Signal Timing (or Signal Setting) 交通感应信号——Traffic Actuated Signal 城市交通控制系统——Urban Traffic Control System 联动控制——Coordinated Control 区域控制——Area Control 时差——Offset同时联动控制——Simultaneous Coordinated Control交变联动控制——Alternate Coordinated Control绿波带——Green Wave连续通行联动控制——Progressive Coordinated Control中心控制器——Master Controller局部控制器——Local——Controller实时——Real Time联机——On-line脱机——Off-line爬山法——Hill-Climbing“小型高效”区域控制系统——Compact Urban Traffic Control System道路控制系统——Corridor Control System交通仿真——Traffic Simulation时间扫描法——Time Scanning事件扫描法——Event ScanningTags:交通控制英语词汇作者:ITS观察[本日:3 本周:4 本月:4 总数:137 ] [返回上一页] [打印] 0好的评价如果您觉得此文库好,就请您0%(0)差的评价如果您觉得此文库差,就请您100%(1)特别声明:本站文章版权归文章原始作者所有,转载文章必须先获得作者同意,请务必注明出处和原始作者。

Intelligentlightingcontrolsystem(智能照明控制系统)外文翻译

Intelligentlightingcontrolsystem(智能照明控制系统)外文翻译

Intelligent lighting control systemAbstract: Intelligent lighting control system the main aim is to save energy, smart lighting control system with a variety of "pre-set" control mode and control components, at different times on different degrees of illumination for accurate set-up and rational management of energy-saving. This automatic adjustment of the illumination means, take full advantage of the natural outdoor light, only when necessary when the lamp or light to the required brightness, use the least energy to ensure that the required illumination level, energy-saving effect is very clear, usually ranging from more than 30%.Keywords: Intelligent lighting control system bus-type star-shaped structure1 the use of intelligent lighting control system for the superiority of1.1 good energy saving effectIntelligent lighting control system using the main purpose is to save energy, smart lighting control system with a variety of "pre-set" control mode and control components, at different times on different degrees of illumination for accurate set-up and rational management of energy-saving. This automatic adjustment of the illumination means, take full advantage of the natural outdoor light, only when necessary when the lamp or light to the required brightness, use the least energy to ensure that the required illumination level, energy-saving effect is very clear, usually ranging from more than 30%. In addition, the intelligent lighting control system for fluorescent lamp dimming control, etc., due to the use of a fluorescent active tunable filter electronic ballast technology and reduce the harmonic content, to improve the power factor and reduce the low-voltage reactive power loss.1.2 to extend the life span of light sourceLight source can not only extend the life savings, but also significantly reduce the workload of lamp replacement, reducing the operating costs of lighting systems, management and maintenance becomes simple.Both the thermal radiation source, or gas discharge light source, voltage fluctuations are a major cause of light damage. Therefore, the effective suppression of the fluctuations in voltage can extend the life of light sources.Intelligent lighting control system can successfully suppress the surge voltage power grid, but also have a voltage limit and the conjugate stream functions of filtering, to avoid over-voltage and under-voltage damage to the light. The use of soft-start and soft turn-off technology, to avoid the impact of current damage to the light. Through this method, the light source to extend the life span of usually 2 to 4 times.1.3 to improve the working environment, improve efficiencyGood working environment is to improve the efficiency of a necessary condition. Good design and reasonable choice of light source, lamps and lighting quality control systems, can improve the quality of lighting.Intelligent lighting control system dimming control panel module to replace the traditional lighting of the level switch control is an effective way to control the overall room illumination value, thereby enhancing the uniformity of illumination. At the same time, this control method used in electrical components have also solved the stroboscopic effect, will not create uncomfortable, confused, feeling eyestrain.1.4 to achieve a variety of lighting effectsA wide range of lighting control, the same building can have a variety of artistic effect, for a lot of construction hyperchromic. Modern buildings, lighting is not simply to meet people on the visual effect of light and shade, they should have control of a variety of programs to make buildings more vivid, more artistic, giving a wealth of visual effects and aesthetics. As an example of a project, building the exhibition hall, lecture hall, lobby, atrium, etc., if with intelligent lighting control system, according to different times, different uses, different effects, using the corresponding pre-set scene control, can achieve the wealth of artistic effect.1.5 facilitate the management of maintenanceIntelligent lighting control system for the control of lighting based on the automatic control of modular-based, supplemented by manual control, preset lighting scenes to the parameters stored in the EPROM Digital, these information is very convenient to set up and replaced, so that building lighting management and maintenance easier.1.6 have a high economic rate of returnOur reference point for the Shanghai region, from energy-saving lights and provincial estimates of the two made a come to this conclusion: with three to five years, the owner can recover the basic intelligent lighting control system to increase the total costs. Intelligent lighting control system can improve the environment and improve employee productivity and reduce maintenance and management costs, but also for the owners to save a substantial amount of costs.2 intelligent lighting control system componentsWe know that the intelligent lighting control system of building control system is only one part of the. If you want to focus on the various control systems to the control center to control, then the control system must have the standard communication interface and protocol version. Although such a system integration is feasible in theory, but it is very difficult to put into practice. Thus, in engineering, intelligent management of our building a distributed system, distributed, that is relatively independent of each control subsystem, self-contained, the implementation of specific control, intelligent building management system control subsystem of the relative independence, self-contained, the implementation of specific control, intelligent building management system from the control subsystem is a signal collection and monitoring role.At present, the intelligent lighting control system in accordance with sub-network topology, the following two forms, namely, bus and star-shaped structure-based hybrid. Both forms have the characteristics of a number of bus more flexibility, easy expansion, control of relative independence, lower costs; mixed some high reliability, fault diagnosis and rule out the simple, easy access to the agreement, transfer rate higher.Engineering design, we consider the building of intelligent lighting control system as an independent subsystem, use of international standards and agreements of the communication interface text, into the intelligent building management systems. Intelligent lighting control system uses a distributed, distribution-based approach, that is, the dimming control unit is relatively independent, self-contained, non-interfering, through centralized management and information interfaces, and intelligent building managementsystem linked to the achievement of the building control center subsystem of the collection and monitoring of the signal. In short, the intelligent lighting control should be the main system is a centralized management, and the main trunk and information interface components consisting of the regional implementation of the same sample of control and signal networks; its subsystems should be a dimmer by the various types of modules , control panels, illumination detector dynamic and static and dynamic components consisting of detectors, respectively, of the regional implementation of the specific control of different networks, the main system and subsystems, such as between the components through the interface to connect, to achieve data transmission.3 Intelligent lighting control system and control of the control of the contentA project to control the use of intelligent lighting control system include the following categories: technology office hall, computer center and other important room, lecture hall, such as multi-function hall, exhibition hall, conference center, lobby and courtyard, walkways and elevators, such as the Office of Public site; building facade lighting in general and also by the intelligent lighting control systems to control switch signal.Control the content of the term of the Interpretation:(1) clock controlClock management, etc. through the electrical components, to achieve the normal work of regions for the state of lighting in different time control.(2) the automatic adjustment control illuminationThrough each module and illumination dimming dynamic electrical components such as detectors, to achieve under normal conditions in the regions for the normal work of the state of the automatic lighting dimming control, making the region, such as illumination will not be outside with the sunshine factors change, and always maintain the default value in the illumination around.(3) control of the regional sceneThrough each dimmer module and the control panel and other electrical components, to achieve under normal conditions in the regions for the normal work of the state of the scene lighting control switch.(4) static and dynamic detection of controlThrough each dimming modules and electrical components, such as movement detectors, to achieve under normal conditions in the regions for the normal work of the state of the automatic lighting control switch.(5) Reduction state of emergency controlThrough each of the normal lighting control module, such as dimming of the electrical components, to achieve a state of emergency for the normal work of the various districts in the state of lighting and to give up the number of relief, such as dimming control.(6) Manual remote controlThrough the infra-red remote control, to achieve under normal conditions in the regions for the normal work of the state of lighting control and manual control of the regional scene.(7) Emergency lighting controlHere mainly refers to the control of intelligent lighting control system to the specialregion by the implementation of the emergency lighting control, including the following two controls:1) under normal illumination and the automatic adjustment control of the regional scene with the regulation of the normal work of lighting the same manner as the control.2) a state of emergency automatic discharge dimming control, through each of the emergency lighting dimming control module, such as electrical components, to achieve a state of emergency for the regions under a state of emergency lighting dimmers, such as giving up control, so that the accident in the state of emergency lighting to reach 100%.These are the characteristics of intelligent lighting control systems analysis and office buildings in a specific application in a number of experiences, hoping to play the role of forward, so that the field of technology in the lighting to fully play its role.智能照明控制系统摘要:采用智能照明控制系统的主要目的是节约能源,智能照明控制系统借助各种不同的"预设置"控制方式和控制元件,对不同时间不同环境的光照度进行精确设置和合理管理,实现节能。

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英文Because 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 orderly control. 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 AT89C51(1)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(2)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 downAbout 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) and appropriate 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 tiptop 1.27 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 on planar 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 strictlow 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.中文由于我国经济的快速发展从而导致了汽车数量的猛增,大中型城市的城市交通,正面临着严峻的考验,从而导致交通问题日益严重,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。

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