智能交通外文原文及译文

合集下载

智能交通系统中英文对照外文翻译文献

智能交通系统中英文对照外文翻译文献(文档含英文原文和中文翻译)原文:Traffic Assignment Forecast Model Research in ITS IntroductionThe intelligent transportation system (ITS) develops rapidly along with the city sustainable development, the digital city construction and the development of transportation. One of the main functions of the ITS is to improve transportation environment and alleviate the transportation jam, the most effective method to gain the aim is to forecast the traffic volume of the local network and the important nodes exactly with GIS function of path analysis and correlation mathematic methods, and this will lead a better planning of the traffic network. Traffic assignment forecast is an important phase of traffic volume forecast. It will assign the forecasted traffic to every way in the traffic sector. If the traffic volume of certain road is too big, which would bring on traffic jam, planners must consider the adoption of new roads or improving existing roads to alleviate the traffic congestion situation. This study attempts to present an improved traffic assignment forecast model, MPCC, based on analyzing the advantages and disadvantages of classic traffic assignment forecast models, and test the validity of the improved model in practice.1 Analysis of classic models1.1 Shortcut traffic assignmentShortcut traffic assignment is a static traffic assignment method. In this method, the traffic load impact in the vehicles’ travel is not considered, and the traffic impedance (travel time) is a constant. The traffic volume of every origination-destination couple will be assigned to the shortcut between the origination and destination, while the traffic volume of other roads in this sector is null. This assignment method has the advantage of simple calculation; however, uneven distribution of the traffic volume is its obvious shortcoming. Using this assignment method, the assignment traffic volume will be concentrated on the shortcut, which isobviously not realistic. However, shortcut traffic assignment is the basis of all theother traffic assignment methods.1.2 Multi-ways probability assignmentIn reality, travelers always want to choose the shortcut to the destination, whichis called the shortcut factor; however, as the complexity of the traffic network, thepath chosen may not necessarily be the shortcut, which is called the random factor.Although every traveler hopes to follow the shortcut, there are some whose choice isnot the shortcut in fact. The shorter the path is, the greater the probability of beingchosen is; the longer the path is, the smaller the probability of being chosen is.Therefore, the multi-ways probability assignment model is guided by the LOGIT model:∑---=n j ii i F F p 1)exp()exp(θθ (1)Where i p is the probability of the path section i; i F is the travel time of thepath section i; θ is the transport decision parameter, which is calculated by the followprinciple: firstly, calculate the i p with different θ (from 0 to 1), then find the θwhich makes i p the most proximate to the actual i p .The shortcut factor and the random factor is considered in multi-ways probabilityassignment, therefore, the assignment result is more reasonable, but the relationshipbetween traffic impedance and traffic load and road capacity is not considered in thismethod, which leads to the assignment result is imprecise in more crowded trafficnetwork. We attempt to improve the accuracy through integrating the several elements above in one model-MPCC.2 Multi-ways probability and capacity constraint model2.1 Rational path aggregateIn order to make the improved model more reasonable in the application, theconcept of rational path aggregate has been proposed. The rational path aggregate,which is the foundation of MPCC model, constrains the calculation scope. Rationalpath aggregate refers to the aggregate of paths between starts and ends of the trafficsector, defined by inner nodes ascertained by the following rules: the distancebetween the next inner node and the start can not be shorter than the distance betweenthe current one and the start; at the same time, the distance between the next innernode and the end can not be longer than the distance between the current one and theend. The multi-ways probability assignment model will be only used in the rationalpath aggregate to assign the forecast traffic volume, and this will greatly enhance theapplicability of this model.2.2 Model assumption1) Traffic impedance is not a constant. It is decided by the vehicle characteristicand the current traffic situation.2) The traffic impedance which travelers estimate is random and imprecise.3) Every traveler chooses the path from respective rational path aggregate.Based on the assumptions above, we can use the MPCC model to assign thetraffic volume in the sector of origination-destination couples.2.3 Calculation of path traffic impedanceActually, travelers have different understanding to path traffic impedance, butgenerally, the travel cost, which is mainly made up of forecast travel time, travellength and forecast travel outlay, is considered the traffic impedance. Eq. (2) displaysthis relationship. a a a a F L T C γβα++= (2)Where a C is the traffic impedance of the path section a; a T is the forecast traveltime of the path section a; a L is the travel length of the path section a; a F is theforecast travel outlay of the path section a; α, β, γ are the weight value of that threeelements which impact the traffic impedance. For a certain path section, there aredifferent α, β and γ value for different vehicles. We can get the weighted average of α,β and γ of each path section from the statistic percent of each type of vehicle in thepath section.2.4 Chosen probability in MPCCActually, travelers always want to follow the best path (broad sense shortcut), butbecause of the impact of random factor, travelers just can choose the path which is ofthe smallest traffic impedance they estimate by themselves. It is the key point ofMPCC. According to the random utility theory of economics, if traffic impedance is considered as the negativeutility, the chosen probability rs p of origination-destinationpoints couple (r, s) should follow LOGIT model:∑---=n j jrs rs bC bC p 1)exp()exp( (3) where rs p is the chosen probability of the pathsection (r, s);rs C is the traffic impedance of the path sect-ion (r, s); j C is the trafficimpedance of each path section in the forecast traffic sector; b reflects the travelers’cognition to the traffic impedance of paths in the traffic sector, which has reverseratio to its deviation. If b → ∞ , the deviation of understanding extent of trafficimpedance approaches to 0. In this case, all the travelers will follow the path whichis of the smallest traffic impedance, which equals to the assignment results withShortcut Traffic Assignment. Contrarily, if b → 0, travelers ’ understanding error approaches infinity. In this case, the paths travelers choose are scattered. There is anobjection that b is of dimension in Eq.(3). Because the deviation of b should beknown before, it is difficult to determine the value of b. Therefore, Eq.(3) is improvedas follows:∑---=n j OD j OD rsrs C bC C bC p 1)exp()exp(，∑-=n j j OD C n C 11（4） Where OD C is the average of the traffic impedance of all the as-signed paths; bwhich is of no dimension, just has relationship to the rational path aggregate, ratherthan the traffic impedance. According to actual observation, the range of b which is anexperience value is generally between 3.00 to 4.00. For the more crowded cityinternal roads, b is normally between 3.00 and 3.50.2.5 Flow of MPCCMPCC model combines the idea of multi-ways probability assignment anditerative capacity constraint traffic assignment.Firstly, we can get the geometric information of the road network and OD trafficvolume from related data. Then we determine the rational path aggregate with themethod which is explained in Section 2.1.Secondly, we can calculate the traffic impedance of each path section with Eq.(2),Fig.1 Flowchart of MPCC which is expatiated in Section 2.3.Thirdly, on the foundation of the traffic impedance of each path section, we cancalculate the respective forecast traffic volume of every path section with improvedLOGIT model (Eq.(4)) in Section 2.4, which is the key point of MPCC.Fourthly, through the calculation processabove, we can get the chosen probability andforecast traffic volume of each path section, but itis not the end. We must recalculate the trafficimpedance again in the new traffic volumesituation. As is shown in Fig.1, because of theconsideration of the relationship between trafficimpedance and traffic load, the traffic impedanceand forecast assignment traffic volume of everypath will be continually amended. Using therelationship model between average speed andtraffic volume, we can calculate the travel timeand the traffic impedance of certain path sect-ionunder different traffic volume situation. For theroads with different technical levels, therelationship models between average speeds totraffic volume are as follows: 1) Highway: 1082.049.179AN V = (5) 2) Level 1 Roads: 11433.084.155AN V = (6) 3) Level 2 Roads: 66.091.057.112AN V = (7) 4) Level 3 Roads: 3.132.01.99AN V = (8) 5) Level 4 Roads: 0988.05.70A N V =(9) Where V is the average speed of the path section; A N is the traffic volume of thepath section.At the end, we can repeat assigning traffic volume of path sections with themethod in previous step, which is the idea of iterative capacity constraint assignment,until the traffic volume of every path section is stable.译文智能交通交通量分配预测模型介绍随着城市的可持续化发展、数字化城市的建设以及交通运输业的发展，智能交通系统（ITS）的发展越来越快。

智能交通导论

第一部分中英文翻译ITS：智能交通系统（Intelligent Transport System,简称ITS）GIS：地理信息系统（GIS，Geographic Information System）GPS：是英文Global Positioning System（全球定位系统）AGVS：是（Automated Guided Vehicle System），意即自动导向搬运车系统。

IVS:智能视频监控（Intelligent Video Surveillance）智能视频系统（Intelligent Video System）智能视频服务器（Intelligent Video Server）智能视觉监控（Intelligent Vision Surveillance）智能视觉系统（Intelligent Vision System）智能视觉服务器（Intelligent Vision ServerAHS：自动公路系统，Automated Highway Systems）ETC：电子收费（Electronic Toll Collection）ATMS：先进的交通管理系统（Advanced traffic management system）CVO:商用车辆运营系统（ＣｏｍｍｅｒｃｉａｌＶｅｈｉｃｌｅＯｐｅｒａｔｉｏｎ）ATIS:出行者信息系统（AdｖａｎｃｅｄＴｒａｖｅｌｅｒi nｆｏｒｍａｔｉｏｎＳｙｓｔｅｍ）AVL：自动公交车辆定位APTS：先进公共运输系统概述（Ad vanced ｐｕｂｌｉｃｔｒａｎｓｐｏｒｔａｔｉｏｎｓｙｓｔｅｍ）第二部分1.AGVS （Automated Guided Vehicle System）概念：是一种无人驾驶搬运车，它可以按照监控系统下达的指令，根据预先设计的程序，依照车载传感器确定的位置信息，沿着规定的行驶路线和停靠位置或自动行驶2.自动公路系统AHS概念:日本学者称之为自动驾驶道路系统，是指用现代化的传感技术、通讯技术、计算机技术以及检测技术等装备公路系统，并通过车路通信和车车通信，达到车辆可自动控制方向、速度、车间距等，从而使汽车自动行驶于其上的智能化公路系统以及其他的安装设备。

智能交通外文原文及译文

智能交通外文原文及译文编辑整理：尊敬的读者朋友们：这里是精品文档编辑中心，本文档内容是由我和我的同事精心编辑整理后发布的，发布之前我们对文中内容进行仔细校对，但是难免会有疏漏的地方，但是任然希望（智能交通外文原文及译文）的内容能够给您的工作和学习带来便利。

同时也真诚的希望收到您的建议和反馈，这将是我们进步的源泉，前进的动力。

本文可编辑可修改，如果觉得对您有帮助请收藏以便随时查阅，最后祝您生活愉快业绩进步，以下为智能交通外文原文及译文的全部内容。

北京联合大学毕业设计外文原文及译文题目：基于物联网的智能交通控制系统设计专业: 电子信息工程指导教师：杜欣冯艳娜学院：师范学院学号： 2010020305106班级: 师范电子1101B 姓名：任国翠一、外文原文Internet of Things1。

the definition of connotationThe English name of the Internet of Things The Internet of Things, referred to as：the IOT。

Internet of Things through the pass， radio frequency identification technology, global positioning system technology，real-time acquisition of any monitoring，connectivity, interactive objects or processes， collecting their sound， light， heat，electricity，mechanics, chemistry, biology, the location of a variety of the information you need network access through a variety of possible things and things，objects and people in the Pan-link intelligent perception of items and processes，identification and management. The Internet of Things IntelliSense recognition technology and pervasive computing，ubiquitous network integration application, known as the third wave of the world's information industry development following the computer, the Internet。

Intelligent Transport(智能交通)英文和翻译

湖南科技大学智能控制理论论文姓名：_____________ 学院：_____________ 班级：_____________ 学号：_____________Intelligent Traffic Signal Control Using Wireless SensorNetworksAbstractThe growing vehicle population in all developing and developed countries calls for a major change in the existing traffic signaling systems. The most widely used automated system uses simple timer based operation which is inefficient for non-uniform traffic. Adv anced automated systems in testing use image processing techniques or advanced com munication systems in vehicles to communicate with signals and ask for routing. This mig ht not be implementable in developing countries as they prove to be complex and expens ive. The concept proposed in this paper involves use of wireless sensor networks to sens e presence of traffic near junctions and hence route the traffic based on traffic density in t he desired direction. This system does not require any system in vehicles so can be impl emented in any traffic system easily. This system uses wireless sensor networks technol ogy to sense vehicles and a microcontroller based routing algorithm for traffic managem ent.Keywords:Intelligent traffic signals, intelligent routing, smart signals, wireless sensornetworks.INTRODUCTIONThe traffic density is escalating at an alarming rate in developing countries which c alls for the need of intelligent traffic signals to replace the conventional manual and timer based systems. Experimental systems in existence involve image processing based dens ity identification for routing of traffic which might be inefficient in situations like fog, rain or dust. The other conceptual system which is based on interaction of vehicles with traffic si gnals and each other require hardware modification on each vehicle and cannot be practi cally implemented in countries like India which have almost 100 million vehicles on road[1]. The system proposed here involves localized traffic routing for each intersection based on wireless sensor networks. The proposed system has a central controller at every jun ction which receives data from tiny wireless sensor nodes placed on the road. The sensor nodeshave sensors that can detect the presence of vehicle and the transmitter wirelessly trans mits the traffic density to the central controller. The controller makes use of the proposed algorithm to find ways to regulate traffic efficiently.THE NEED FOR AN ALTERNATE SYSTEMThe most prevalent traffic signaling system in developing countries is the timer based system. This system involves a predefined time setting for each road at an int ersection. While this might prove effective for light traffic, heavy traffic requires an adaptiv e system that will work based on the density of traffic on each road. The first system prop osed for adaptive signaling was based on digital image processing techniques. This syste m works based on the captured visual input from the roads and processing them to find w hich road has dense traffic. This system fails during environmental interaction like rain or fog. Also this system in testing does not prove efficient. The advanced system in testing a t Pittsburgh [2] involves signals communicating with each other and also with the vehicles . The proposed system does not require a network between signals and vehicles and is a standalone system at each intersection.THE PROPOSED SYSTEMThis paper presents the concept of intelligent traffic routing using wireless sensor networks. The primary elements of this system are the sensor nodes or motes consi sting of sensors and a transmitter. The sensors interact with the physical environment while the transmitter pages the sensor’s data to the central controller. This system involves t he 4 x 2 array of sensor nodes in each road. This signifies 4 levels of traffic and 2 lanes i n each road. The sensors are ultrasonic or IR based optical sensors which transmits stat us based on presence of vehicle near it. The sensor nodes transmit at specified time inter vals via ZigBee protocol to the central controller placed at every intersection. The controll er receives the signal and computes which road and which lane has to be given green sig nal based on the density of traffic. The controller makes use of the discussed algorithm to perform the intelligent traffic routing.COMPONENTS INVOLVED IN THE SYSTEMThe proposed system involves wireless sensor networks which are comprised of t hree basic components: the sensor nodes or motes, power source and a central controlle r. The motes in turn are comprised of Sensors and transceiver module. The sensors sens e the vehicles at intersections and transceiver transmit the sensor’s data to the central co ntroller through a wireless medium. The Power source provides the power needed for the sensor nodes and is mostly regenerative. The central controller performs all the computa tions for the sensor networks. The controller receives the input from all sensors and proc esses simultaneously to make the required decisions.A.SensorsSensors are hardware devices that produce a measurable response to a change in a physical condition like temperature or pressure. Sensors measure physical data of the parameter to be monitored. The continual analog signal produced by the sensors is digitized by an analog-to-digital converter and sent to controllers for further processing. A sen sor node should be small in size, consume extremely low energy, operate in high volumet ric densities, be autonomous and operate unattended, and be adaptive to the environme nt. As wireless sensor nodes are typically very small electronic devices, they can only be equipped with a limited power source of less than 0.5-2 ampere-hour and 1.2-3.7 volts. S ensors are classified into three categories: passive Omni-directional sensors; passive nar row-beam sensors; and active sensors [3].The sensors are implemented in this system placed beneath the roads in an intersec tion or on the lane dividers on each road. The sensors are active obstacle detectors that detect the presence of vehicles in their vicinity. The sensors are set in four levels on each road signifying four levels of traffic from starting from the STOP line. The fourth level indi cates high density traffic and signifies higher priority for the road to the controller. The se nsors required for obstacle detection can be either ultrasonic or Infrared LASER based s ensors for better higher efficiency.B. MotesA mote, also known as a sensor node is a node in a wireless sensor network that i s capable of performing some processing, gathering sensory information and communica ting with other connected nodes in the network. The main components of a sensor node are a microcontroller, transceiver, external memory, power source and one or more sens ors [3].C. Need for MotesThe primary responsibility of a Mote is to collect information from the various distrib uted sensors in any area and to transmit the collected information to the central controller for processing. Any type of sensors can be incorporated with these Motes based on the r equirements. It is a completely new paradigm for distributed sensing and it opens up a fa scinating new way to look at sensor networks.D. Advantages of MotesThe core of a mote is a small, low-cost, low-power controller.The controller monitors one or more sensors. It is easy to interface all sorts of sensors, including sensors for temperature, light, sound, position, acceleration, vibrat ion, stress, weight, pressure, humidity, etc. with the mote.The controller connects to the central controller with a radio link. The most comm on radio links allow a mote to transmit at a distance of about 3 to 61 meters. Power cons umption, size and cost are the barriers to longer distances. Since a fundamental concept with motes is tiny size and associated tiny cost, small and low-power radios are normal.As motes shrink in size and power consumption, it is possible to imagine solar power or even something exotic like vibration power to keep them running. It is hard to imagine something as small and innocuous as a mote sparking a revolution, but that's exactly what they have done.Motes are also easy to program, either by using serial or Ethernet cable to conne ctto the programming board or by using Over the Air Programming (OTAP).E. TransceiversSensor nodes often make use of ISM band, which gives free radio, spectrum allocation and global availability. The possible choices of wireless transmission medi a are radio frequency (RF), optical communication and infrared. Lasers require less ener gy, but need line-of-sight for communication and are sensitive to atmospheric conditions. Infrared, like lasers, needs no antenna but it is limited in its broadcasting capacity. Radiofrequency-based communication is the most relevant that fits most ofthe WSN applications. WSNs tend to use license-free communication frequencies: 173, 4 33, 868, and 915 MHz; and 2.4 GHz. The functionality of bothtransmitter and receiver are combined into a single deviceknown as a transceiver [3].To bring about uniqueness in transmitting and receiving toany particular device vari ous protocols/algorithms are devised. The Motes are often are often provided with powerf ul transmitters and receivers collectively known as transceivers for better long range oper ation and also toachieve better quality of transmission/reception in any environmental co nditions.F. Power SourceThe sensor node consumes power for sensing, communicating and dataprocessing. More energy is required for data communication than any other process. Power is stored either in batteries or capacitors. Batteries, both rechargeable and non-re chargeable, are the main source of power supply for sensor nodes. Current sensors are able to renew their energy from solar sources, temperature differences, or vibration. Two power saving policies used are Dynamic Power Management (DPM) and Dynamic Voltag e Scaling (DVS). DPM conserves power by shutting down parts of the sensor node which are not currently used or active. A DVS scheme varies the power levels within the senso r node depending on the non-deterministic workload. By varying the voltage along with th e frequency, it is possible to obtain quadratic reduction in power consumption.G. Tmote SkyTmote Sky is an ultra low power wireless module for use in sensor networks,monitoring applications, and rapid application prototyping. Tmote Sky leverages indu stry standards like USB and IEEE802.15.4 to interoperate seamlessly with other devices. By using industry standards, integrating humidity, temperature, and light sensors, and pr oviding flexible interconnection with peripherals, Tmote Sky enables a wide range of mes h network applications [4]. The TMote is one of the most commonly used motes in wirele ss sensor technology. Any type of sensor can be used in combination with this type of mo te.Tmote Sky features the Chipcon CC2420 radio for wireless communications. The CC2420 is an IEEE 802.15.4 compliant radio providing the PHY and some MAC function s [5]. With sensitivity exceeding the IEEE 802.15.4 specification and low power operation, the CC2420 provides reliable wireless communication. The CC2420 is highly configurabl e for many applications with the default radio settings providing IEEE 802.15.4 complianc e. ZigBee specifications can be implemented using the built-in wireless transmitter in the Tmote Sky.H. Tmote Key Features• 250kbps 2.4GHz IEEE 802.15.4 Chipcon Wireless Transceiver• Interoperability with other IEEE 802.15.4 devices.• 8MHz Texas Instruments MSP430 microcontroller (10k RAM, 48k Flash Memory) • Integrated ADC, DAC, Supply Voltage Supervisor, and DMA Controller • Integrate d onboard antenna with 50m range indoors / 125m range outdoors • Integrated Humidity , Temperature, and Light sensors • Ultra low current consumption • Fast wakeup fromsleep (<6μs)• Hardware link-layer encryption and authentication • Programming and data collec tion via USB• 16-pin expansion support and optional SMA antenna connector• TinyOS support : mesh networking and communication implementation • Compli es with FCC Part 15 and Industry Canada regulations • Environmentally friendly – compl ies with RoHS regulations [4].I. ZigBee Wireless TechnologyZigBee is a specification for a suite of high level communication protocols using small, low-power digital radios based on an IEEE 802.15.4 standard for personal ar ea networks [6] [7]. ZigBee devices are often used in mesh network form to transmit data over longer distances, passing data through intermediate devices to reach more distant o nes.This allows ZigBee networks to be formed ad-hoc, with no centralized control or high -power transmitter/receiver able to reach all of the devices. Any ZigBee device can be tas ked with running the network. ZigBee is targeted at applications that require a low data ra te, long battery life, and secure networking. ZigBee has a defined rate of 250kbps, best s uited for periodic or intermittent data or a single signal transmissionfrom a sensor or input device. Applications include wireless light switches, electrical meters with in-home-displays, traffic management systems, and other consumer and ind ustrial equipment that requires short-range wireless transfer of data at relatively low rates . The technology defined by the ZigBee specification is intended to be simpler and less e xpensive than other WPANs, such as Bluetooth.J. Types of ZigBee Devices ZigBee devices are of three types:ZigBee Coordinator (ZC): The most capable device, the Coordinator forms the root of the network tree and might bridge to other networks. There is exactly one Zig Bee Coordinator in each network since it is the device that started the network originally. It stores information about the network, including acting as the Trust Center & repository for security keys. The ZigBee Coordinator the central controller is in this system.ZigBee Router (ZR): In addition to running an application function, a device can act as an intermediate router, passing on data from other devices.ZigBee End Device (ZED): It contains just enough functionality to talk to theparent node. It cannot relay data from other devices. This relationship allows the no de to be asleep a significant amount of the time thereby giving long battery life. A ZED re quires the least amount of memory, and therefore can be less expensive to manufacture t han a ZR or ZC.K. ZigBee ProtocolsThe protocols build on recent algorithmic research to automatically construct a low-s peed ad-hoc network of nodes. In most large network instances, the network will be a clu ster of clusters. It can also form a mesh or a single cluster. The current ZigBee protocols support beacon and non-beacon enabled networks. In non-beacon-enabled networks, an un-slotted CSMA/CA channel access mechanism is used. In this type of network, ZigBee Routers typically have their receivers continuously active, requiring a more robust power supply. However, this allows for heterogeneous networks in which some devices receive continuously, while others only transmit when an external stimulus is detected. In beacon-enabled networks, the special network nodes called ZigBee Routers transmit periodic be acons to confirm their presence to other network nodes. Nodes may sleep between beac ons, thus lowering their duty cycle and extending their battery life. Beacon intervals depe nd on data rate; they may range from 15.36ms to 251.65824s at 250 kbps. In general, th e ZigBee protocols minimize the time the radio is on, so as to reduce power use. In beac oning networks, nodes only need to be active while a beacon is being transmitted. In non -beacon-enabled networks, power consumption is decidedly asymmetrical: some devices are always active, while others spend most of their time sleeping.V. PROPOSED ALGORITHM A. Basic AlgorithmConsider a left side driving system (followed in UK, Australia, India, Malaysia and 72 other countries). This system can be modified for right side driving system (USA, Canada , UAE, Russia etc.) quite easily. Also consider a junction of four roads numbered as node 1, 2, 3 and 4 respectively. Traffic flows from each node to three other nodes with varied densities. Consider road 1 now given green signal in all directions.1)Free left turn for all roads (free right for right side driving system).2)Check densities at all other nodes and retrieve data from strip sensors.3) Compare the data and compute the highest density.4) Allow the node with highest density for 60sec.5)Allowed node waits for 1 time slot for its turn again and the process is repeated f rom step 3.B. Advanced AlgorithmAssume road three is currently given green to all directions. All left turns are always f ree. No signals/sensors for left lane. Each road is given a time slot of maximum 60 secon ds at a time. This time can be varied depending on the situation of implementation. Consi der 4 levels of sensors Ax, Bx, Cx, Dx with A having highest priority and x representing roads 1 to 4. Also consider 3 lanes of traffic: Left (L), Middle (M) and Right(R) correspondin g to the direction of traffic. Since leftturn is free, Left lanes do not require sensors. So sensors form 4x2 arrays with 4 levels of traffic and 2 lanes and are named MAx, RAx, MBx, RBx and so on and totally 32 sensor s are employed.The following flow represents the sequence of operation done by the sign al.1) Each sensor transmits the status periodically to the controller. 2) Controller recei ves the signals and computes the following3) The sensors Ax from each road having highest priority are compared. 4) If a sin gle road has traffic till Ax, it is given green signal in the next time slot. 5) If multiple road s have traffic till Ax, the road waiting for the longest duration is given the green.6) Once a road is given green, its waiting time is reset and its sensor status is negle cted for that time slot7) If traffic in middle lane, green is given for straight direction, based on traffic, either right side neighbor is given green for right direction, of opposite road is give green for str aight direction.8) If traffic in right lane, green is given for right, and based on traffic, left side neighb or is given green for straight or opposite is given green for right.9) Similar smart decisions are incorporated in the signal based on traffic density and directional traffic can be controlled.C. Implementation and RestrictionsThis system can be implemented by just placing the sensor nodes beneath the road or on lane divider and interfacing the central controller to the existing signal lights and co nnecting the sensor nodes to the controller via the proposed wireless protocol. The only r estriction for implementing the system is taking the pedestrians into consideration. This h as to be visualized for junctions with heavy traffic such as highway intersections and amo unt of pedestrians is very less. Also major intersections have underground or overhead fo otpaths to avoid interaction of pedestrians with heavy traffic.ACKNOWLEDGMENTThe Authors would like to take this opportunity to thank Ms. P. Sasikala, Assistant Pr ofessor, ECE department, Sri Venkateswara College of Engineering, Sriperumbudur, wh o gave the basic insight into the field of Wireless Sensor Networks. We also thank Mrs. G . Padmavathi, Associate Professor, ECE department, Sri Venkateswara College of Engin eering, Sriperumbudur, who with her expertise in the field of networks advised and guide d on practicality of the concept and provided helpful ideas for future modifications. We als o express our gratitude to Dr. S. Ganesh Vaidyanathan, Head of the department of ECE, Sri Venkateswara College of Engineering, Sriperumbudur, who supports us for every inn ovative project and encourages us “think beyond” for better use of technology. And finall y we express our heart filled gratitude to Sri Venkateswara College of Engineering, which has been the knowledge house for our education and introduced us to the field of Engine ering and supports us for working on various academic projects.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 co uple of minutes - in the past. Current adaptive systems often operate on the basis of ada ptive 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 si gnal plan generation tools make rational decisions about signal plans under varying condi tions; but almost none of the current available tools behave pro-actively or have meta-rul es that may change behaviour of the controller incorporated into the system. The next log ical step for traffic control is the inclusion of these meta-rules and pro active and goal-orie nted behaviour. The key aspects of improved control, for which contributions from artificia l intelligence and artificial intelligent agents can be expected, include the capability of dea ling 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 n on-recurrent and unexpected events (Ambrosino et al.., 1994).What are intelligent agentsAgent technology is a new concept within the artificial intelligence (AI). The agent pa radigm in AI is based upon the notion of reactive, autonomous, internally-motivated entiti es that inhabit dynamic, not necessarily fully predictable environments (Weiss, 1999). Aut onomy 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 respo nding to stimuli produced by integrally contained sensors (Ziegler, 1990). Multi-Agent Sys tems can be characterised by the interaction of many agents trying to solve a variety of pr oblems in a co-operative fashion. Besides AI, intelligent agents should have some additio nal attributes to solve problems by itself in real-time; understand information; have goals and intentions; draw distinctions between situations; generalise; synthesise new concept s and / or ideas; model the world they operate in and plan and predict consequences of a ctions and evaluate alternatives. The problem solving component of an intelligent agent c an 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 opt ima in decentralised systems, are not the global optimum. This problem is not easily solv ed. The solution has to be found by tailoring the interaction mechanism or to have a supe rvising 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 importa nt mentioning are: information agents, agents for traffic simulation and traffic control. Curr ently, most applications of intelligent agents are information agents. They collect informati on 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 weath er, traffic jams, public transport, route closures, best routes, etc. to the user via a Person al Travel Assistant. Agent technology can also be used for aggregating data for further di stribution. 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 si milar way as object oriented programs often use objects). The application of agents in (Ur ban) 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 adjoi ning agents. The most promising aspects of agent technology, the flexibility and pro-activ e behaviour, give UTC the possibility of better anticipation of traffic. Current UTC is not th at flexible, it is unable to adjust itself if situations change and can't handle un-programme d situations. Agent technology can also be implemented on several different control layer s. This gives the advantage of being close to current UTC while leaving considerable free dom 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 actuate d traffic controllers and is able to pro actively handle traffic situations and handling the diff erent, 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 im prove current state of the art UTC systems:- Adaptability. Intelligent agents are able to adapt its behaviour and can learn from e arlier 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 abl e to plan ahead.To be acceptable as replacement unit for current traffic control units, the system sho uld perform the same or better than current systems. The agent based UTC will require o n-line and pro-active reaction on changing traffic patterns. An agent based UTC should b e demand responsive as well as adaptive during all stages and times. New methods for tr affic 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 differ ent 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, - abr upt 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 ti me,- abrupt, temporal, changes due to prioritised traffic over a short period of timeOne 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 res ponsible 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 l ower level agents that they can't solve. This represents current traffic control implementat ions and idea's. One final aspect to be mentioned is the robustness of agent based syste ms (if all communication fails the agent runs on, if the agent fails a fixed program can beexecuted.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 seg ments, intersections, corridors), we handle only controlled intersections with detectors (int ensity and speed) at all road segments, we only handle cars and we use simple rule base s for knowledge representation.Types of agents in urban intersection controlAs we divide the system in several, recognisable, parts we define the following 4 typ es of agents:- Roads are represented by special road segment agents (RSA), - Controlled intersections are represented by intersection agents (ITSA), - For specifi c, defined, areas there is an area agent (higher level),- For specific routes there can be route agents, that spans several adjoining road se gments (higher level).We have not chosen for one agent per signal. This may result in a more simple soluti on but available traffic control programs do not fit in that kind of agent. We deliberately ch oose a more complex agent to be able to use standard traffic control design algorithms a nd 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 ta kes 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 s everal ITSA's (InTerSection Agent).,some authority agents (area and route agents) and o。

智能交通系统的设计与实现(英文中文双语版优质文档)

智能交通系统的设计与实现（英文中文双语版优质文档）Intelligent Transportation System (Intelligent Transportation System, ITS) is a traffic management system that integrates information technology, intelligent control technology, sensor technology, communication technology and other technologies. It can improve transportation efficiency, reduce traffic congestion, reduce the incidence of traffic accidents, and at the same time improve the driving experience and provide a better service experience. This paper will discuss the design and implementation of intelligent transportation system from two aspects.1. Design of Intelligent Transportation System1. Functional module designThe functional modules of the intelligent transportation system include data acquisition module, data processing module, decision-making control module and information release module. Among them, the data acquisition module is used to collect traffic information, vehicle information and driving route information; the data processing module is used to process and analyze the collected data, and generate traffic status reports and predictive analysis reports; the decision-making control module is used to process data based on The report generated by the module formulates the optimal route planning and traffic control strategy; the information release module is used to release traffic information and route planning information to drivers and passengers.2. System architecture designThe system architecture of intelligent transportation system includes data acquisition layer, data processing layer, decision-making control layer and information release layer. Among them, the data acquisition layer is mainly composed of sensors and cameras for collecting traffic information and vehicle information; the data processing layer is mainly composed of servers and data processing software for processing and analyzing the collected data; the decision-making control layer is mainly composed of The control center and control software are used to formulate optimal route planning and traffic control strategies; the information release layer is mainly composed of display screens and voice broadcast systems, which are used to release traffic information and route planning information to drivers and passengers.3. Technology selection designThe technologies required by intelligent transportation systems include information technology, intelligent control technology, sensor technology, communication technology, etc. When selecting technology, it is necessary to select the appropriate technology according to the system requirements and technology development status. For example, in terms of sensor technology, you can choose acoustic sensors, image sensors, etc.; in terms of communication technology, you can choose 4G, 5G, etc.; in terms of information technology, you can choose artificial intelligence, big data, etc.2. Realization of Intelligent Transportation System1. Data collection and processingThe data collection of the intelligent transportation system is mainly carried out through sensors and cameras. Sensors can collect data such as traffic flow, vehicle speed, and lane occupancy, and cameras can collect vehicle information and driving route information. The collected data needs to be analyzed and processed by the data processing module to generate traffic status reports and predictive analysis reports. In the data processing module, it is necessary to use data analysis software to clean, process, model and analyze the collected data, such as using machine learning algorithms to predict and analyze the data, and generate traffic congestion prediction reports to provide decision-making information for the decision-making control module. support.2. Route planning and traffic controlThe decision-making control module is one of the most critical modules in the intelligent transportation system. In this module, it is necessary to combine the reports generated by the data processing module and the predictive analysis reports to formulate optimal route planning and traffic control strategies. For example, when traffic is congested, route optimization measures can be taken to avoid congested sections, or traffic signal control measures can be taken to control vehicle speed to reduce congestion. In terms of route planning and traffic control, a decision support system based on artificial intelligence algorithms can be used to achieve optimal route planning and traffic control through data analysis and decision-making models.3. Information release and service experienceThe information release module of the intelligent transportation system is used to release traffic information and route planning information to drivers and passengers. For example, when there is a traffic jam, information about the congestion situation and avoidance routes can be released to drivers and passengers to provide a better driving experience. At the same time, intelligent transportation systems can also provide other service experiences, such as vehicle remote control, vehicle diagnosis and maintenance, etc.Summarize:Intelligent transportation system is a traffic management system that integrates information technology, intelligent control technology, sensor technology, communication technology and other technologies. It can improve transportation efficiency, reduce traffic congestion, reduce the incidence of traffic accidents, and at the same time improve the driving experience and provide a better service experience. The design of intelligent transportation system includes functional module design, system architecture design and technology selection design; the realization of intelligent transportation system includes data collection and processing, route planning and traffic control, information release and service experience, etc. The application of intelligent transportation system will be an important part of the construction of smart cities in the future, and will contribute to the improvement of urban traffic management and public transportation services.智能交通系统（Intelligent Transportation System, ITS）是一种集信息技术、智能控制技术、传感器技术、通讯技术等多种技术于一体的交通管理系统。

智能交通中英文对照外文翻译文献

中英文对照外文翻译文献(文档含英文原文和中文翻译)智能交通的的设计由于我国经济的快速发展，导致大中型城市汽车数量激增，城市交通面临严峻的考验，导致交通问题增加，其主要表现为：交通事故频发，给人类生命安全造成巨大的威胁，造成严重的交通拥堵，出行时间增加，能源消费的增加；空气污染和噪声污染程度加深等，日常交通拥堵成为人们司空见惯而又不得不忍受。

在此背景下，结合实际情况城市道路交通，发展真正适合我们自己的特点的智能信号控制系统已成为主要任务。

前言在国内外实际应用中，根据实际交通信号控制的应用检验，平面独立的交叉口信号控制基本采用了定周期，多时间的设置周期，半感应，全传感器等几种方式。

前两者的控制模式是完全基于平面交叉口的交通流量数据的统计调查，由于交通流量的现在变性和随机性的存在，这两种方法具有交通效率低的缺陷，该方案，老化和半感应和感应两方法在前两种方式的基础上增加了车辆检测器，根据提供的信息来调整周期和车辆的绿色通道，它比随机到达的适应性大，可以使车辆在交通拥挤前先停车，实现对交通流量的影响。

在现代工业生产中，电流、电压、温度、压力、流量、速度、开关量等都是常用的主要被控参数。

例如：在冶金工业、化工药品的生产、电力工程、造纸行业、机械制造和食品加工等诸多领域，人们需要交通的有序控制。

通过单片机控制交通运输，不仅具有方便的控制、配置简单、灵活等优点，而且还可以通过控制量大幅度提高技术指标，从而大大提高了产品的质量和数量。

因此，单片集成电路的交通灯控制问题是一个工业生产中，我们经常遇到的问题。

在工业生产过程中，有很多行业有大量的交通设备，在目前的系统中，大部分的交通控制信号是通过继电器，而继电器的响应时间长、灵敏度低、长期使用后，故障的机会大大增加，相对于单片机控制，远大于继电器的精度、响应时间短，软件可靠性，不会因为工作时间的缘故而降低其性能，相比，该方案具有较高的可行性。

关于AT89C51（1）功能特点说明：AT89C51是一个低功耗，高性能CMOS8位微控制器，具有8K可编程Flash存储器。

智能城市交通系统外文翻译文献

智能城市交通系统外文翻译文献(文档含中英文对照即英文原文和中文翻译)A Multiagent System for Optimizing Urban TrafficJohn France and Ali A. GhorbaniFaculty of Computer ScienceUniversity of New BrunswickFredericton, NB, E3B 5A3, CanadaAbstractFor the purposes of managing an urban traffic system, a hierarchical multiagent system that consists of several locally operating agents each representing an intersection of a traffic system is proposed. Local Traffic Agents (LTAs) are concerned with the optimal performance of their assigned intersection; however, the resulting traffic light patterns may result in the failure of the system when examined at a global level. Therefore, supervision is required and achieved with the use of a Coordinator Traffic Agent (CTA).A CTA provides a means by which the optimal local light pattern can be compared against the global concerns. The pattern can then be slightly modified to accommodate the global environment, while maintaining the local concerns of the intersection.Functionality of the proposed system is examined using two traffic scenarios: traffic accident and morning rush hour. For both scenarios, the proposed multiagent system efficiently managed the gradual congestion of the traffic.1 IntroductionThe 20th century witnessed the worldwide adoption of the automobile as a primary mode of transportation. Coupled with an expanding population, present-day traffic networks are unable to efficiently handle the daily movements of traffic through urban areas. Improvements to road networks are often confined by the boundaries of existing structures. Therefore, the primary focus should be to improve traffic flow without changing the layout or structure of the existing roadways. Any solution to traffic problem must handle three basic criteria, including: dynamically changing traffic patterns, occurrence of unpredictable events, and a non-finite based traffic environment [2]. Multiagent systems provide possible solutions to this problem, while meeting all necessary criteria. Agents are expected to work within a real-time, non-terminating environment. As well, agents can handle dynamically occurring events and may posses several processes to recognize and handle a variety of traffic patterns [3, 5].Although several approaches to developing a multiagent traffic system have been studied, each stresses the importance of finding a balance between the desires of the local optimum against a maintained average at the global level [4]. Unfortunately, systems developed to only examine and optimize local events do not guarantee a global balance[6]. However, local agents are fully capable of determining their own local optimum. Therefore, a more powerful approach involves the creation of a hierarchical structure in which a higher-level agent monitors the local agents, and is able to modify the local optimum to better suit the global concerns [7].The remainder of this paper is organized as follows. Section 2 examines the problems of urban traffic. The design of a hierarchical multiagent model is given in Section 3. The experimental results are presented in Section 4. Finally, the conclusions of the present study are summarized in Section 5.2 Urban Traffic CongestionImprovements to urban traffic congestion must focus on reducing internal bottlenecks to the network, rather than replacing the network itself. Of primary concern is the optimization of the traffic lights, which regulate the movement of traffic through the various intersections within the environment. At present, traffic lights may possess sensors to provide basic information relating to their immediate environment. This includes road and clock sensors, measuring the presence and density of traffic and providing the time of day to the traffic light.A solution to the urban traffic problem using agents is to simply replace all decision-making objects within the system by a corresponding agent. Even the most basic system will consist of several agents, leading to the creation of a multiagent environment. In this case, the traffic environment is broken down into its fundamental components, with one agent for each of the traffic lights within the system. To maintain organization and cooperation between the Local Traffic Agents (LTA), a Coordinator Traffic Agent (CTA) exists to monitor global concerns and maintain order.3 Hierarchical Multiagent Model for Urban TrafficTo achieve a balance between the local and global aspects of an urban traffic system, a multiagent system based on a hierarchical architecture is proposed. LTAs and CTAs make up the fundamental levels of the hierarchy, in which the LTAs meet the needs of the specific intersection, and the CTAs determine if the chosen patterns of a LTA are suited to meet any global concerns. A solitary Global Traffic Agent (GTA) may exist for networks of sufficient size, and an Information Traffic Agent (ITA) provides a central location for the storage of all shared information within the system. For each agent, the variables necessary to organize and maintain the hierarchy are listed.The development of this system, in which several LTAs work under the guidance of a single CTA, represents the backbone to a hierarchical structure of agents within the system. The CTA provides the bonds between itself and the LTAs of the system, requiring that the CTA store a list of the neighboring intersections for each of the LTAs. However, the computational capabilities of a single CTA are limited, and a road network of sufficient size may require the use of multiple CTAs to handle all of the LTAs within the system. In this circumstance, the network will be subdivided into regions controlled by a single CTA, with a top-level Global Traffic Agent (GTA) linking the CTAs together. The GTA is an optional agent, existing only if the network is sufficiently large that it is required.A LTA interacts at a global level by sending a message containing the calculated optimal local light pattern to its supervising CTA. The CTA will find the appropriate neighboring intersections, and then determine what the global optimum for the handled LTA will be. To calculate the global optimum, the CTA will require all information relating to each of the neighboring intersection. The CTA will request the information from the ITA by providing a list of the intersections the CTA is concerned with. Once this information is retrieved, a CTA calculates the global optimum and determines if a variance exists between the local and global traffic light patterns. If a significant difference is found, a balance between the local and global optimums must be negotiated, and then returned to the LTA.4 ImplementationThe proposed urban traffic multiagent system has been implemented using the JACK Development Environment, utilizing JACK Intelligent Agents TM.JACK uses the Belief Desire Intention (BDI) model. Under this framework,“the agent pursues its given goals (desires), adopting appropriate plans (intentions) according to its current set of data (beliefs) about the state of the world.”[1]. Agents created under the JACK environment are event-driven, and can respond to internal or external events occurring within the systemThe first phase of implementing the multiagent system involves the creation of LTAs. Each ofthese agents are tailored to meet the requirements of its corresponding intersection.For the purposes of this project, the traffic network consists of six intersections. Each intersection consists of two roads crossing over one another. Each approaching road posses two lanes, a left-turning lane, and a straight/rightturning lane.The decision-making capabilities of the LTAs is developed in the second phase. The first round of decisions by a LTA are concerned with finding the local optimum, with no consideration for neighboring intersections. A basic expert system divides the sensor inputs into a corresponding light pattern. The resulting light pattern consists of an eight-element array, which can be broken down into two elements for each of the North, East, South and West directions.Odd elements of the array (zero is the first index) specify the duration of the advanced green state for each of the appropriate directions, while even elements indicate the time of the straight/right-turning lanes. This light pattern is always in the same format, and once calculated, stored by the LTA. The values contained within the array consist of strings, indicating the duration of the traffic light. The values of the strings are as follows:Red: Red light, lanes remain in a stopped state.Short: Green light, most frequently occurring, 30-seconds in duration for straight directions, 15 seconds for leftturning lanes.Medium: Green light, often for above average traffic densities,45-seconds in duration for straight directions, 25 seconds for left-turning lanesShort: Green light, indicating a high traffic density, 60-seconds in duration for straight directions, 35 seconds for left-turning lanes.Once the optimal local traffic light pattern is calculated,the LTA sends a message event to the CTA. The traffic light pattern is passed to the CTA, allowing the CTA to adjust the LTA’s ligh t pattern to better meet any global concerns. Stored within the CTA is a vector of neighbors for each LTA within the system. When a CTA receives a message event from a LTA, the CTA gathers all information relating to the neighbors of the currently handled LTA from the ITA. The CTA will use this information within its own expert system, comparing the local optimum light pattern against the current densities of the neighboring intersections. If a significant difference is found between the local optimum and the essence of the global optimum, the traffic light pattern to be implemented is altered to reduce the difference between the two optimums. The new traffic light pattern is returned to the LTA for implementation within the traffic light.4.1 ExperimentsThis sections presents some of the experiments carried out for two fixed state scenarios. In each experiment, a list of variables is provided to initialize the current state of the environment. Once the state of the environment is established, each LTA goes through the process of changing the state of their traffic light to accommodate the other direction. The resulting traffic light pattern for each intersection is recorded, and the number of vehicles passing through the intersection, N, in the available time indicated by the traffic light pattern is calculated as N = T/(α+ε)where αandεrepresent the ideal amount of time required for a vehicle to pass through a traffic intersection and the latency increase to the ideal length of time due to unexpected events, respectively.An advanced form of this calculation would allow the latency value of _ to increase by a constant factor for each additional segment of the waiting vehicles. This can be demonstrated by using βto represent each of the latency groups, imposing a maximum number of vehicles that exist within each latency group. Let the number of vehicles found in latency group k is calculated as,where tβi denotes the amount of time used by the latency group βi The total number of vehicles that could then pass through the intersection would be calculated as N = β1 +β2 + ···+ βm, where m represent the number of latency groups that can make it through the traffic light.In this simulation we set α= 2 and ε= 1. A limit of three was imposed on the value of β0, while no limit was imposed on β1. These values were chosen for simplicity, and the precision in which the three possible values of T could be divided.To display the traffic density of the network, a grayscale image representing the density values within the environment is used (see Figure 1). Each lane of the traffic network is covered with an appropriate grayscale image.Figure 1. Initial densities prior to accident.Figure 2. Densities after six cycles.4.1.1 Traffic Accident ScenarioThe traffic accident scenario involves the occurrence of a traffic accident in the upper-right intersection of the network(see Figure 1).The occurrence of the accident results in the intersection at the upper-right to force all traffic tostop. This is done by implementing an all red traffic light pattern at the intersection faced with the traffic accident. The traffic light patterns of the adjacent intersections (2 and 6), remove their green states for the east and north directions, respectively. Although traffic can still move in all other available directions, those vehicles planning to head towards the stopped directions are forced to wait at the intersection. This results in a gradual increase to the traffic density at the intersections adjacent to the accident. Figure 2 shows the densities after 6 cycles.As the level of congestion increases at intersections 2 and 6, eventually their density values reach a point that leads to the CTA reducing the length of time that the other intersections (1 and 5) allow traffic to proceed. This results in a decrease to the overall congestion at intersections 2 and 6. Although slowed down, the density values will eventually reach their maximum level, at which time the totally congested event occurs. This forces intersections 1 and 5 to stop allowing traffic to move towards intersections 2 and 6. By the 8th cycle, the traffic accident is cleared up. Figure 3Figure 3. Densities five cycles after the accident is cleared up.shows the traffic densities 5 cycles after the accident is completely cleared up.4.1.2 Morning Rush Hour ScenarioTo initialize the morning rush hour scenario, the traffic densities of the network are set to low values. Over the next several cycles, a constant movement of incoming traffic is seen from the unknown directions, and from the suburbs located between intersections 1 and 2. With the addition of traffic from the suburbs, by the end of the second cycle, the east-bound lane of intersection 2 is heavily used.When both east-bound directions for intersections 2 and 5 are fully congested (see Figure 4), traffic heading in those directions will be forced to wait. This will allow the eastbound directions of intersection 2 and 5 to reduce their traffic densities, which will allow traffic to approach these lanes during the next cycle. Until one of the east-bound directions is de-congested, traffic will not be diverted in a north/south direction to travel around the problem.As rush hour passes and the inbound traffic density is reduced, the network is able to clear out the congested intersections. This is done from east to west, as the rush hour traffic is proceeding in an eastward direction.5 ConclusionsThe development of a hierarchical multiagent structure to manage an urban traffic system ispresented in this paper. To test the functionality of the proposed urban traffic multiagent system, two traffic scenarios are considered. For both scenarios (traffic accident and morning rush hour), the multiagent system efficiently managed the gradual congestion of the network. As one roadway becomes more congested, the duration of the traffic lights of neighboring intersections leading towards the congested area are reducedFigure 4. Densities after ten cycles.by the CTA. This redirection proves successful and results in the achievement of a global balance between the roadways of the network. However, when the traffic density continues to build, all roadways heading in a similar direction will eventually become equally congested. The urban traffic multiagent system handles this situation by halting all traffic heading in those directions. This allows the congested roadways to decrease their density values. Although this slows the network down, the congested traffic is handled in a more organized and controlled manner.6 AcknowledgmentsThis work was partially funded through grant RGPIN 227441-00 from the Natural Science and Engineering Research Council of Canada (NSERC) to Dr. Ali Ghorbani.References[1] Jack intelligent agents: User guide. 2002.[2] T. P. M. Baglietto and R. Zoppoli. Distributed-information neural control: The case of dynamic routing intraffic networks.IEEE Transactions on Neural Networks, 3(12), 2001.[3] P. Brumeister, A. Haddadi, and G. Matylis. Application of multiagent systems in traffic and transportation. IEEE Proc.-Soft. Eng., (144), 1997.[4] J. R. Campos and N. R. Jennings. Towards a social level characterization of socially responsible agents. IEEEProc.-Soft.Eng., (144), 1997.[5] K. R. Erol, R. Levy, and J. Wentworth. Application of agent technology to traffic simulation./advance/agent.html, Last access June 2002.[6] C. Ledoux. An urban traffic flow model integrating neural networks. Transportation Research, 5, 1997.[7] D. A. Roozemond. Using intelligent agents for pro-active, real-time urban intersection control. EuropeanJournal of Operational Research, 2001.多智能体系统优化城市交通约翰·法国和阿里 A.Ghorbani计算机科学学院新不伦瑞克大学弗雷德里克顿E3B 5A3 加拿大摘要管理城市交通系统而言，建议由的几个本地经营代理组成，每个代表交叉口的交通系统的分层多智能体系统。

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。

毕业设计论文外文文献翻译智能交通信号灯控制中英文对照

英语原文Intelligent Traffic Light Controlby Marco Wiering The topic I picked for our community project was traffic lights. In a community, people need stop signs and traffic lights to slow down drivers from going too fast. If there were no traffic lights or stop signs, people’s lives would be in danger from drivers going too fast.The urban traffic trends towards the saturation, the rate of increase of the road of big city far lags behind rate of increase of the car.The urban passenger traffic has already become the main part of city traffic day by day and it has used about 80% of the area of road of center district. With the increase of population and industry activity, people's traffic is more and more frequent, which is unavoidable. What means of transportation people adopt produces pressure completely different to city traffic. According to calculating, if it is 1 to adopt the area of road that the public transport needs, bike needs 5-7, car needs 15-25, even to walk is 3 times more than to take public transits. So only by building road can't solve the city traffic problem finally yet. Every large city of the world increases the traffic policy to the first place of the question.For example，according to calculating, when the automobile owning amount of Shanghai reaches 800,000 (outside cars count separately ), if it distributes still as now for example: center district accounts for great proportion, even when several loop-lines and arterial highways have been built up , the traffic cannot be improved more than before and the situation might be even worse. So the traffic policy Shanghai must adopt , or called traffic strategy is that have priority to develop public passenger traffic of city, narrow the scope of using of the bicycle progressively , control the scale of growth of the car traffic in the center district, limit the development of the motorcycle strictly.There are more municipals project under construction in big city. the influence on the traffic is greater.Municipal infrastructure construction is originally a good thing of alleviating the traffic, but in the course of constructing, it unavoidably influence the local traffic. Some road sections are blocked, some change into an one-way lane, thus the vehicle can only take a devious route . The construction makes the road very narrow, forming the bottleneck, which seriously influence the car flow.When having stop signs and traffic lights, people have a tendency to drive slower andlook out for people walking in the middle of streets. To put a traffic light or a stop sign in a community, it takes a lot of work and planning from the community and the city to put one in. It is not cheap to do it either. The community first needs to take a petition around to everyone in the community and have them sign so they can take it to the board when the next city council meeting is. A couple residents will present it to the board, and they will decide weather or not to put it in or not. If not put in a lot of residents might be mad and bad things could happened to that part of the city.When the planning of putting traffic lights and stop signs, you should look at the subdivision plan and figure out where all the buildings and schools are for the protection of students walking and riding home from school. In our plan that we have made, we will need traffic lights next to the school, so people will look out for the students going home. We will need a stop sign next to the park incase kids run out in the street. This will help the protection of the kids having fun. Will need a traffic light separating the mall and the store. This will be the busiest part of the town with people going to the mall and the store. And finally there will need to be a stop sign at the end of the streets so people don’t drive too fast and get in a big accident. If this is down everyone will be safe driving, walking, or riding their bikes.In putting in a traffic light, it takes a lot of planning and money to complete it. A traffic light cost around $40,000 to $125,000 and sometimes more depending on the location. If a business goes in and a traffic light needs to go in, the business or businesses will have to pay some money to pay for it to make sure everyone is safe going from and to that business. Also if there is too many accidents in one particular place in a city, a traffic light will go in to safe people from getting a severe accident and ending their life and maybe someone else’s.The reason I picked this part of our community development report was that traffic is a very important part of a city. If not for traffic lights and stop signs, people’s lives would be in danger every time they walked out their doors. People will be driving extremely fast and people will be hit just trying to have fun with their friends. So having traffic lights and stop signs this will prevent all this from happening.Traffic in a city is very much affected by traffic light controllers. When waiting for a traffic light, the driver looses time and the car uses fuel. Hence, reducing waiting times before traffic lights can save our European society billions of Euros annually. To make traffic light controllers more intelligent, we exploit the emergence of novel technologies such as communication networks and sensor networks, as well as the use of more sophisticated algorithms for setting traffic lights. Intelligent traffic light control does not only mean thattraffic lights are set in order to minimize waiting times of road users, but also that road users receive information about how to drive through a city in order to minimize their waiting times. This means that we are coping with a complex multi-agent system, where communication and coordination play essential roles. Our research has led to a novel system in which traffic light controllers and the behaviour of car drivers are optimized using machine-learning methods.Our idea of setting a traffic light is as follows. Suppose there are a number of cars with their destination address standing before a crossing. All cars communicate to the traffic light their specific place in the queue and their destination address. Now the traffic light has to decide which option (ie, which lanes are to be put on green) is optimal to minimize the long-term average waiting time until all cars have arrived at their destination address. The learning traffic light controllers solve this problem by estimating how long it would take for a car to arrive at its destination address (for which the car may need to pass many different traffic lights) when currently the light would be put on green, and how long it would take if the light would be put on red. The difference between the waiting time for red and the waiting time for green is the gain for the car. Now the traffic light controllers set the lights in such a way to maximize the average gain of all cars standing before the crossing. To estimate the waiting times, we use 'reinforcement learning' which keeps track of the waiting times of individual cars and uses a smart way to compute the long term average waiting times using dynamic programming algorithms. One nice feature is that the system is very fair; it never lets one car wait for a very long time, since then its gain of setting its own light to green becomes very large, and the optimal decision of the traffic light will set his light to green. Furthermore, since we estimate waiting times before traffic lights until the destination of the road user has been reached, the road user can use this information to choose to which next traffic light to go, thereby improving its driving behaviour through a city. Note that we solve the traffic light control problem by using a distributed multi-agent system, where cooperation and coordination are done by communication, learning, and voting mechanisms. To allow for green waves during extremely busy situations, we combine our algorithm with a special bucket algorithm which propagates gains from one traffic light to the next one, inducing stronger voting on the next traffic controller option.We have implemented the 'Green Light District', a traffic simulator in Java in which infrastructures can be edited easily by using the mouse, and different levels of road usage can be simulated. A large number of fixed and learning traffic light controllers have already been tested in the simulator and the resulting average waiting times of cars have been plotted and compared. The results indicate that the learning controllers can reduce average waiting timeswith at least 10% in semi-busy traffic situations, and even much more when high congestion of the traffic occurs.We are currently studying the behaviour of the learning traffic light controllers on many different infrastructures in our simulator. We are also planning to cooperate with other institutes and companies in the Netherlands to apply our system to real world traffic situations. For this, modern technologies such as communicating networks can be brought to use on a very large scale, making the necessary communication between road users and traffic lights possible.中文翻译：智能交通信号灯控制马克·威宁我所选择的社区项目主题是交通灯。

智能车辆中英文对照外文翻译文献

中英文对照翻译附件1：翻译译文智能车辆本世纪初期，在计算机和信息革命的影响下，汽车经历了性能和与驾驶者之间的互动方面最富戏剧性的变革。

1908年，亨利福特T型车的出现体现了汽车设计上的重大突破。

它不仅开创了轻松更换零件和大量生产的先河，而且其“用户友好”的运作方式，让任何人都可以轻松驾驶。

近90年来，类似于福特T型车的简单汽车越来越少，汽车迅速成为了一种复杂的“移动电脑”，扮演着领航者，护航者，甚至第二司机的角色。

这些新特性不仅改变了我们的驾驶方式，还提高了运输服务质量和挽救生命的能力，并对美国工业的竞争力提供了支持。

然而，智能车的表现不仅如此。

相反的，使车辆更加智能的这些组件，如新信息，安全性和自动化技术，是作为零配件抵达市场的，或作为可选设备，或作为售后服务的特殊配件。

为了提高司机的安全性，这些技术不断发展并上市销售。

但是个别的技术还没有得到整合，不能创造出与司机高度协作的完全智能的车辆。

汽车行业已经意识到并解决了潜在的不协调技术的大量涌入问题。

但他们的进步受到技术和经济障碍，不确定的消费者喜好，不完善的标准和准则的阻碍。

此外，无论是传统的汽车制造商或是政府监管机构（除非安全问题非常明显）都不能控制售后的产品的使用，特别是在卡车和公共汽车的使用方面。

然而，还没有一个“以人为本”的智能车辆试图整合和协调各种技术以解决问题。

我们也许不仅仅会失去实现新的车载技术的机遇，甚至可能会在无意中降低行车的安全性和性能。

意识到智能车辆的重要性和汽车设计中人为因素所产生的潜在危险之后，交通部于1997年启动智能车辆倡议（IVI）。

这一举措旨在加快汽车系统的发展和集成，用以帮助汽车，卡车及巴士司机更安全和有效地操作。

20世纪80年代的电视连续剧“霹雳游侠”功能的智能车辆可以跨越颇高的大厦，似乎驾驶超音速本身，对坏人间谍，并有英文用词和管家的个性。

这款车不仅是聪明，但自作聪明。

虽然在现实世界中的智能车辆将无法飞越站在交通，他们将有强大的能力。

有关智能小车的外文文献翻译(原文+中文)-英文文献翻译

Intelligent VehicleOur society is awash in “machine intelligence” of various kinds.Over the last century, we have witnessed more and more of the “drudgery” of daily living being replaced by devices such as washing machines.One remaining area of both drudgery and danger, however, is the daily act ofdriving automobiles. 1.2million people were killed in traffic crashes in 2002, which was 2.1% of all globaldeaths and the 11th ranked cause of death . If this trend continues, an estimated 8.5 million people will be dying every year in road crashes by 2020. in fact, the U.S. Department of Transportation has estimated the overall societal cost of road crashes annually in the United States at greater than $230 billion .when hundreds or thousands of vehicles are sharing the same roads at the same time, leading to the all too familiar experience of congested traffic. Traffic congestion undermines our quality of life in the same way air pollution undermines public health.Around 1990, road transportation professionals began to apply them to traffic and road management. Thus was born the intelligent transportation system (ITS). Starting in the late 1990s, ITS systems were developed and deployed。

有关智能交通相关文献翻译（中文+英文）

智能交通智能交通是一个基于现代电子信息技术面向交通运输的服务系统。

它的突出特点是以信息的收集、处理、发布、交换、分析、利用为主线，为交通参与者提供多样性的服务。

在该系统中，车辆靠自己的智能在道路上自由行驶，公路靠自身的智能将交通流量调整至最佳状态，借助于这个系统，管理人员对道路、车辆的行踪将掌握得一清二楚。

基本信息智能交通系统 (IntelligentTransportationSystem，简称ITS)是未来交通系统的发展方向，它是将先进的信息技术、数据通讯传输技术、电子传感技术、控制技术及计算机技术等有效地集成运用于整个地面交通管理系统而建立的一种在大范围内、全方位发挥作用的，实时、准确、高效的综合交通运输管理系统。

ITS可以有效地利用现有交通设施、减少交通负荷和环境污染、保证交通安全、提高运输效率，因而，日益受到各国的重视。

21世纪将是公路交通智能化的世纪，人们将要采用的智能交通系统，是一种先进的一体化交通综合管理系统。

特点智能交通系统具有以下两个特点：一是着眼于交通信息的广泛应用与服务，二是着眼于提高既有交通设施的运行效率。

与一般技术系统相比。

智能交通系统建设过程中的整体性要求更加严格．这种整体性体现在：（1）跨行业特点。

智能交通系统建设涉及众多行业领域，是社会广泛参与的复杂巨型系统工程，从而造成复杂的行业间协调问题。

（2）技术领域特点。

智能交通系统综合了交通工程、信息工程，通信技术、控制工程、计算机技术等众多科学领域的成果，需要众多领域的技术人员共同协作。

（3）政府、企业、科研单位及高等院校共同参与，恰当的角色定位和任务分担是系统有效展开的重要前提条件。

（4）智能交通系统将主要由移动通信、宽带网、RFID、传感器、云计算等新一代信息技术作支撑，更符合人的应用需求，可信任程度提高并变得“无处不在”。

智能交通专业英文简历范文

智能交通专业英文简历范文English: With a strong passion for utilizing technology to improve transportation systems, I am a dedicated and skilled professional in the field of Intelligent Transportation. My background includes a Bachelor's degree in Civil Engineering with a specialization in Transportation Engineering, along with industry certifications in Intelligent Transportation Systems (ITS). I have hands-on experience in developing and implementing ITS solutions, analyzing traffic patterns, and optimizing signal control systems to enhance traffic flow efficiency. Additionally, I am proficient in using various traffic simulation software and programming languages to model and test transportation scenarios. I possess excellent problem-solving skills, effective communication abilities, and a proven track record of successful project management in the transportation sector.中文翻译:怀着对利用技术改善交通系统的强烈热情，我是智能交通领域的一名敬业和技术娴熟的专业人士。

智慧交通英文作文怎么写

智慧交通英文作文怎么写英文：As someone who has experienced the benefits of smart transportation firsthand, I am a firm believer in the power of technology to transform the way we move around our cities. From intelligent traffic management systems to connected vehicles, there are a myriad of ways in which smart transportation can improve our lives.One of the most exciting developments in this field is the rise of autonomous vehicles. These self-driving cars have the potential to revolutionize the way we commute, making our journeys safer, more efficient, and more enjoyable. Imagine being able to sit back and relax while your car takes you to work, or being able to catch up on emails or read a book during your daily commute. With autonomous vehicles, this could become a reality.Another area where smart transportation is making a bigimpact is in the realm of public transportation. From real-time information displays to contactless payment systems, technology is making it easier than ever for people to use buses, trains, and other forms of public transport. For example, in my city, we have a mobile app that allows us to track the location of buses in real-time, so we know exactly when our bus is going to arrive. This has made using public transport much more convenient and reliable.Of course, there are also challenges that come with implementing smart transportation solutions. One of the biggest is ensuring that these systems are secure and reliable. With so much data being transmitted between vehicles and infrastructure, it is essential that we have robust cybersecurity measures in place to protect against cyberattacks.Overall, I believe that smart transportation has the potential to transform our cities for the better. By embracing technology and innovation, we can create a more sustainable, efficient, and enjoyable transportation system that benefits everyone.中文：作为一个亲身体验过智慧交通带来好处的人，我坚信科技有能力改变我们在城市中移动的方式。

智能交通在教育中的运用英语作文

智能交通在教育中的运用英语作文全文共6篇示例，供读者参考篇1Title: The Use of Smart Transportation in EducationHi everyone! Today I want to talk to you about something really cool - smart transportation in education. Have you ever heard of buses and bikes that are super smart and can help us get to school faster and safer?First of all, let's talk about smart buses. Smart buses are equipped with GPS systems that can help them navigate the roads better. This means that they can avoid traffic jams and get us to school on time. They also have sensors that can detect if there are any obstacles in the way, so we can avoid accidents. How cool is that?Next, let's talk about smart bikes. Smart bikes are also equipped with GPS systems, so we can track our route and know how far we have traveled. They also have lights and signals that can help us stay safe on the road. Plus, they can connect to our phones and give us directions to our destination. It's like having a personal assistant with us wherever we go!In addition to buses and bikes, smart transportation can also include smart traffic lights and signs. These can help us cross the road safely and make sure that cars are following the rules. With all these smart technologies in place, we can feel more confident and secure when we are on the road.So, next time you see a smart bus or bike, remember how they are helping us in our education. Let's embrace the use of smart transportation and make our journeys to school even better! Thank you for listening!篇2Title: The Use of Smart Traffic in EducationHey guys! Today I want to talk about something super cool - smart traffic! Have you ever heard of it? It’s all about using technology to make traffic safer and more efficient. And do you know what's even cooler? Smart traffic is not just for cars and buses, it can also be used in education!So, how can smart traffic help us in school? Well, let me tell you! First of all, smart traffic can help reduce traffic congestion around schools. You know how chaotic it can be when all the cars and buses are trying to drop off students at the same time? Withsmart traffic systems in place, traffic flow can be better regulated, making drop-off and pick-up much smoother and safer.Secondly, smart traffic can help improve the safety of students who walk or bike to school. By installing things like smart crosswalks and traffic lights, students can feel safer when crossing the street. Additionally, smart traffic can also help monitor school zones to make sure drivers are obeying the speed limits and keeping our streets safe.Another way smart traffic can benefit education is by improving the efficiency of school buses. With the help of GPS tracking and real-time traffic information, school buses can optimize their routes to pick up students in the most efficient way possible. This not only saves time but also reduces fuel consumption and carbon emissions, making our planet a better place to live!In conclusion, smart traffic is not just about making our roads safer and reducing traffic jams. It can also play a big role in making our schools safer and more efficient. So next time you see a traffic light or a school bus, remember how cool technology is helping us in our daily lives. Let’s embrace the power of smart traffic for a brighter future!篇3Title: Smart Traffic in EducationHey guys! Today I want to talk to you about something super cool: smart traffic in education! Have you ever wondered how technology can help us get to school faster and safer? Well, that's where smart traffic comes in.First of all, let's talk about what smart traffic is. Smart traffic uses technology like cameras, sensors, and computers to manage traffic flow and make our roads safer. This means that traffic lights can change based on how many cars are on the road, and cameras can help spot traffic jams before they happen.So, how does smart traffic help us in education? Well, imagine a world where buses can adjust their routes based on traffic patterns, so they always get us to school on time. Or where crosswalks have sensors that detect when students are crossing, so cars stop automatically. This could make our journey to school so much easier and safer!But smart traffic isn't just about getting to school on time. It's also about teaching us to be responsible citizens. By understanding how technology can improve traffic flow, we can learn to respect road rules and drive safely when we're older.Plus, by reducing traffic congestion, we're also helping the environment by reducing air pollution.In conclusion, smart traffic is not just about making our lives easier. It's about teaching us valuable lessons about responsibility, safety, and environmental awareness. So let's embrace this amazing technology and make our journey to school a smooth and enjoyable one! Let's make the most of smart traffic in education!篇4Smart transportation is super cool in our education system. It helps us get to school on time, reduces traffic jams, and keeps us safe on the roads. Let me tell you all about it!Firstly, smart transportation uses technology like traffic lights, cameras, and sensors to manage the flow of traffic. This means that buses and cars can travel smoothly without getting stuck in long lines of vehicles. So, we can get to school faster and have more time to play with our friends before class starts. Yay!Secondly, smart transportation helps us stay safe on the roads. It alerts us to any hazards or obstacles that might be in our way, like cars suddenly stopping or pedestrians crossing thestreet. This way, we can avoid accidents and stay out of harm's way. Safety first, always!Moreover, smart transportation is good for our environment. It reduces air pollution by minimizing the amount of time cars spend idling in traffic. This means that the air we breathe is cleaner and healthier for us. It's like having a superpower that protects our planet!In conclusion, smart transportation is an amazing tool that makes our lives easier, safer, and more fun. We are lucky to have this technology in our education system, and we should do our part to support it. So, let's hop on board the smart transportation train and ride into a brighter future together. Let's go!篇5Smart traffic is super cool! It can help us get to school faster and safer. Let me tell you all about how smart traffic is used in education.First of all, smart traffic can make our school buses run more smoothly. With sensors and cameras on the roads, the buses can avoid traffic jams and take the fastest route to school. This means we don't have to wait long for the bus and we can get to school on time.Secondly, smart traffic can keep us safe on the roads. Traffic lights with sensors can detect when there are too many cars on the road and can adjust the lights to help traffic flow better. This means there are fewer accidents and we can walk or bike to school safely.Furthermore, smart traffic can help us learn about the environment. With data from sensors on the roads, we can see how much pollution is being emitted by cars and buses. This can help us understand the impact of transportation on the environment and learn how to reduce our carbon footprint.In conclusion, smart traffic is a great tool for education. It can help us get to school faster, keep us safe on the roads, and teach us about the environment. So let's embrace smart traffic and make our journey to school a smart and fun one!篇6Oh, hi everyone! Today, let's talk about how smart transportation is used in education. Smart transportation is like using technology to make traffic move better and easier. It's super cool!First of all, smart transportation can help us get to school safely and on time. With things like traffic lights that changebased on how many cars are on the road, we can get to school faster and without any accidents. Plus, buses and trains that run on a schedule can make sure we don't miss the bell.Smart transportation can also help us learn about how traffic works. We can use apps and websites to see real-time traffic information and learn about things like congestion and accidents. It's like having a super smart teacher who knows everything about the roads!And guess what? Smart transportation can even teach us about things like sustainability and the environment. Electric buses and bikes can help reduce pollution and make our planet healthier. We can learn about how our choices impact the world around us.So, next time you see a smart traffic light or a self-driving car, remember how it's making our lives better and helping us learn new things. Smart transportation is not just about getting from one place to another – it's also about teaching us important stuff. Cool, right?。

《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。

智能交通英文作文

智能交通英文作文英文：Intelligent transportation system (ITS) is a modern technology that integrates information and communication technologies with transportation infrastructure. It is aimed at improving the safety, efficiency, and sustainability of transportation systems. ITS is a comprehensive system that involves various technologies such as sensors, cameras, communication networks, and software applications.One of the benefits of ITS is that it can reducetraffic congestion. For example, intelligent traffic management systems can detect traffic volumes and adjust traffic signals accordingly to optimize traffic flow. This can reduce the time that drivers spend on the road and decrease fuel consumption and air pollution.Another benefit of ITS is that it can improve roadsafety. For instance, intelligent vehicle safety systems can detect potential accidents and alert drivers to take corrective actions. This can reduce the number of accidents on the road and save lives.Moreover, ITS can also enhance the efficiency of public transportation systems. For example, real-time information systems can provide passengers with accurate information on bus and train schedules, delays, and routes. This can improve the convenience and reliability of public transportation and encourage more people to use it.Overall, ITS has the potential to revolutionize the way we travel and transport goods. It can make transportation systems safer, more efficient, and more sustainable. As the technology continues to evolve, we can expect to see more innovative applications of ITS in the future.中文：智能交通系统（ITS）是一种现代技术，将信息和通信技术与交通基础设施相结合。

智能交通英文作文

智能交通英文作文Smart transportation is revolutionizing the way we travel. With advanced technologies and innovative solutions, it aims to improve efficiency, safety, and sustainabilityin our transportation systems. Imagine a world where cars communicate with each other, traffic lights adjust in real-time, and public transportation is seamlessly integrated. This is the future of transportation, and it is already becoming a reality.In this new era of smart transportation, connected vehicles play a crucial role. These vehicles are equipped with sensors and communication devices that enable them to exchange information with each other and with the surrounding infrastructure. This allows for better coordination and decision-making, leading to smoothertraffic flow and reduced congestion. Moreover, connected vehicles can also provide real-time data on road conditions, helping drivers make informed choices and avoid accidents.Another important aspect of smart transportation is the use of artificial intelligence. AI-powered systems can analyze vast amounts of data and make predictions, enabling more efficient traffic management. For example, AI algorithms can optimize traffic signal timings based on current traffic conditions, reducing waiting times and improving overall traffic flow. Additionally, AI can also help in predicting and preventing accidents by analyzing patterns and identifying potential risks.Public transportation is also being transformed by smart technologies. Integrated ticketing systems allow passengers to seamlessly switch between different modes of transport, making their journeys more convenient and efficient. Furthermore, real-time information about bus and train schedules, delays, and alternative routes can be easily accessed through smartphone apps, ensuring that passengers are always informed and can plan their trips accordingly.In addition to improving efficiency, smart transportation also focuses on sustainability. Electricvehicles are becoming increasingly popular, offering a cleaner and greener alternative to traditional petrol or diesel cars. Charging stations are being installed in cities, making it easier for electric vehicle owners to recharge their vehicles. Moreover, smart transportation systems also promote the use of bicycles and walking, reducing carbon emissions and improving air quality.In conclusion, smart transportation is transforming our cities and revolutionizing the way we travel. Through connected vehicles, artificial intelligence, and sustainable solutions, it aims to create more efficient, safer, and greener transportation systems. As we embrace these technologies, we can look forward to a future where commuting becomes a seamless and enjoyable experience.。

智能交通英文作文

智能交通英文作文下载温馨提示:该文档是我店铺精心编制而成，希望大家下载以后，能够帮助大家解决实际的问题。

文档下载后可定制随意修改，请根据实际需要进行相应的调整和使用，谢谢!并且，本店铺为大家提供各种各样类型的实用资料，如教育随笔、日记赏析、句子摘抄、古诗大全、经典美文、话题作文、工作总结、词语解析、文案摘录、其他资料等等，如想了解不同资料格式和写法，敬请关注!Download tips: This document is carefully compiled by theeditor. I hope that after you download them,they can help yousolve practical problems. The document can be customized andmodified after downloading,please adjust and use it according toactual needs, thank you!In addition, our shop provides you with various types ofpractical materials,such as educational essays, diaryappreciation,sentence excerpts,ancient poems,classic articles,topic composition,work summary,word parsing,copyexcerpts,other materials and so on,want to know different data formats andwriting methods,please pay attention!Smart transportation is revolutionizing the way we travel. With the advancements in technology, our daily commute has become more efficient and convenient. Imagine being able to monitor traffic conditions in real-time and choose the fastest route to your destination. This is now possible with the help of smart traffic management systems.In addition to optimizing traffic flow, smart transportation also focuses on reducing carbon emissions. Electric vehicles are becoming more popular, thanks totheir eco-friendly nature. These vehicles can be charged at designated charging stations, making it easier for people to switch to greener modes of transportation.Another aspect of smart transportation is the integration of public transportation systems. Commuters can now use a single card to access various modes of transportation, such as buses, trains, and even bicycles. This not only simplifies the payment process but alsoencourages people to use public transportation more frequently.Furthermore, smart transportation aims to enhancesafety on the roads. With the use of sensors and cameras, traffic accidents can be detected and responded to promptly. Intelligent systems can also alert drivers of potential hazards, such as pedestrians crossing the road or vehicles changing lanes. These technologies greatly reduce the riskof accidents and improve overall road safety.Moreover, smart transportation promotes the concept of shared mobility. Ride-sharing services have gainedpopularity in recent years, allowing people to share rides and reduce traffic congestion. This not only saves time and money but also helps to reduce the number of vehicles onthe road.Additionally, smart transportation systems provide valuable data that can be used for urban planning and development. By analyzing travel patterns and congestion hotspots, city planners can make informed decisions toimprove transportation infrastructure. This leads to better urban design and a more sustainable future.In conclusion, smart transportation is transforming the way we travel, making our daily commute more efficient,eco-friendly, and safe. With advancements in technology, we can expect further innovations in the field of transportation, ultimately improving the quality of lifefor people around the world.。

1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。

北京联合大学毕业设计外文原文及译文题目：基于物联网的智能交通控制系统设计专业：电子信息工程指导教师：杜欣冯艳娜学院：师范学院学号： 2010020305106班级：师范电子1101B 姓名：任国翠一、外文原文Internet of Things1.the definition of connotationThe English name of the Internet of Things The Internet of Things, referred to as: the IOT.Internet of Things through the pass, radio frequency identification technology, global positioning system technology, real-time acquisition of any monitoring, connectivity, interactive objects or processes, collecting their sound, light, heat, electricity, mechanics, chemistry, biology, the location of a variety of the information you need network access through a variety of possible things and things, objects and people in the Pan-link intelligent perception of items and processes, identification and management. The Internet of Things IntelliSense recognition technology and pervasive computing, ubiquitous network integration application, known as the third wave of the world's information industry development following the computer, the Internet. Not so much the Internet of Things is a network, as Internet of Things services and applications, Internet of Things is also seen as Internet application development. Therefore, the application of innovation is the core of the development of Internet of Things, and 2.0 of the user experience as the core innovation is the soul of Things.2.The meaning of "material"Where the "objects" to meet the following conditions can be included in the scope of the "Internet of Things":1. Receiver have the appropriate information;2. Have a data transmission path;3. Have a certain storage capabilities;4. To have the CPU;5．To have the operating system;6. Have specialized applications;7. Have a data transmitter;8. Follow the communication protocol of Things;9. World Network, a unique number that can be identified.3．changeThe Internet of Things (Internet of Things) the word universally recognized at home and abroad Ashton, Professor of the MIT Auto-ID Center in 1999 first proposed to study RFID. The report of the same name released in 2005, the International Telecommunication Union (ITU), the definition and scope of the Internet of Things has been a change in the coverage of a larger expansion, no longer refers only to the Internet of Things based on RFID technology.Since August 2009, Premier Wen Jiabao put forward the "Experience China" Internet of Things was officially listed as a national one of the five emerging strategic industries, to write the "Government Work Report" Internet of Things in China has been the great concern of the society as a whole degree of concern is unparalleled in the United States, European Union, as well as other countries.The concept of Internet of Things is not so much a foreign concept, as it has been the concept of a "Made in China", his coverage of the times, has gone beyond the scope of the 1999 Ashton professor and the 2005 ITU report referred to, Internet of Things has been labeled a "Chinese style" label.4．PrincipleInternet of Things is on the basis of the computer Internet, RFID, wireless data communications technology, to construct a cover everything in the world's "Internet of Things". In this network, the goods (products) to each other "exchange", without the need for human intervention. Its essence is the use of radio frequency identification (RFID) technology to achieve the interconnection and sharing of the automatic identification of goods (products) and information through the computer Internet.The Internet of Things is a very important technology is radio frequency identification (RFID) technology. RFID is radio frequency identification (Radio Frequency Identification) technology abbreviation, is an automatic identification technology in the 1990s began to rise, the more advanced a non-contact identification technology. The development of RFID technology based on a simple RFID system, combined with existing network technology, database technology, middleware technology, to build a one composed by a large number of networked readers and numerous mobile label, much larger than the Internet of Things trend.RFID, It is able to let items "speak" a technique. In the "Internet of Things" concept,RFID tags are stored in the specification and interoperability information collected automatically by wireless data communications network to a central information system, to achieve the identification of goods (products), and then through the open computer network for information exchange and sharing, items "transparent" management.The information technology revolution in the Internet of Things is referred to as IT mobile Pan of a specific application. Internet of Things through IntelliSense, identification technology and pervasive computing, ubiquitous network convergence applications, breaking the conventional thinking before, human beings can achieve ubiquitous computing and network connectivity [3]. The traditional thinking has been the separation of physical infrastructure and IT infrastructure: on the one hand, airports, roads, buildings, while on the other hand, the data center, PC, broadband. In the era of the "Internet of Things", reinforced concrete, cable with the chip, broadband integration into a unified infrastructure, in this sense, the infrastructure is more like a new site of the Earth, the world really works it, which including economic management, production operation, social and even personal life. "Internet of Things" makes it much more refined and dynamic management of production and life, to manage the future of the city to achieve the status of "wisdom" to improve resource utilization and productivity levels, and improve the relationship between man and nature.5．Agency1, institution-buildingAs the first national Internet of Things industry community organizations - the application of professional Committee of China Electronic Chamber of Things technology products (referred to as: "objects of the IPCC"), the Ministry of Civil Affairs in June 2010, preliminary approved by the Ministry of August being reported that the Ministry of Civil Affairs for final approval.2, the main taskServe as a bridge between business and government to assist the Government of the industry guidance, coordination, consultation and services to help members to reflect the business requirements to the Government; coordinate the relationship between enterprises to strengthen technical cooperation, product distribution, the elimination of vicious competition ; supervision of members the correct implementation of national laws and regulations, to regulate the industry; member of information communication technology products, cooperation, resource sharing, capital operation, and promote the application of Internet of Things technologies and products, and promote the Internet of Things industrialscale , co-development.6．ConstructionInternet of Things in the practical application to carry out requires the involvement of all walks of life, and need the guidance of the national government as well as related regulations and policies to assist the launching of the Internet of Things has the scale, broad participation, management, technical, and material properties, etc. other features, the technical problem is the most crucial issues of Things billion Bo logistics consulting, Internet of Things technology is an integrated technology, a system not yet which company has overall responsibility for network planning and construction of the entire system, theoretical studies have commenced in all walks of life and the practical application is limited to within the industry. The key is on the planning and design and research and development of the Internet of Things research in the field of RFID, sensors, embedded software, and transmission of data calculation. In general, to carry out the steps of the Internet of things mainly as follows:(1) identified the object attributes, properties, including static and dynamic properties of the static property can be stored directly in the label, the dynamic properties need to start with sensors to detect real-time;(2) the need to identify the equipment to complete the reading of object attributes, and information into a data format suitable for network transmission;(3) the object of information transmitted over the network to the information processing center (processing center may be distributed, such as home computers or mobile phones, may also be centralized, such as China Mobile IDC) by the processing center to complete the object communication calculation.7．key areasInternet of Things 4 key areas:(1) RFID;(2) sensor network;(3) The M2M;(4) integration of the two.8.TrendIndustry experts believe that the Internet of things on the one hand can improve economic efficiency and significant cost savings; the other hand, can provide technical impetus to global economic recovery. Currently, the United States, the European Union are all invested heavily in-depth study to explore the Internet of Things. The country is alsohighly concerned about the emphasis of Things, Industry and Information Technology Ministry in conjunction with the relevant departments are conducting research in a new generation of IT to the formation of policies and measures to support the development of a new generation of IT.China Mobile CEO Wang Jianzhou has repeatedly mentioned the Internet of Things will become the focus of future development of China Mobile. He will be invited to Taiwan to produce RFID, sensors and bar code manufacturers and China Mobile. According to him, the use of the Internet of Things technology, Shanghai Mobile has a number of industrial customers tailor the data collection, transmission, processing and business management in one set of wireless application solutions. The latest data show that Shanghai Mobile has more than 100,000 chips mounted on a taxi, bus, various forms of matter networking applications in all walks of prowess, to ensure the orderly operation of the city. During the Shanghai World Expo, "the bus services through" will be fully applied to the Shanghai public transport system, the smooth flow traffic to the most advanced technology to protect Expo area; for logistics transportation management, e-logistics ", will provide users with real-time accurate information of Cargo, vehicle tracking and positioning, the transport path selection, logistics network design and optimization services greatly enhance the comprehensive competitiveness of logistics enterprises.In addition, the popularization of the "Internet of Things" for the number of animals, plants and machinery, sensors and RFID tags of items and related interface devices will greatly exceed the number of mobile phones. The promotion of the Internet of Things will become a drive to promote economic development for the industry to open up a potential development opportunities. According to the current demand on the Internet of Things, in recent years, billions of sensors and electronic tags, which will greatly promote the production of IT components, while increasing the number of job opportunities.According to reports, it is necessary to truly build an effective Internet of things, there are two important factors. First, the scale, only with the scale to make the items of intelligence play a role. For example, a city of one million vehicles, if we only 10000 vehicles installed on the smart system, it is impossible to form an intelligent transportation system; two mobility items are usually not static, but in the state of the movement , we must maintain the items in the state of motion, and even high-speed motion state can at any time for dialogue.FORRESTER of the authority of the U.S. advisory body predicted that 2020, the world of business of the Internet of Things, compared with the business of interpersonalcommunication, will reach 30 to 1, so the "Internet of Things" is known to be the next one trillion communications services.Internet of Things heat wave Why is rapidly growing in China? Internet of Things in China rapid rise thanks to the several advantages of our country in terms of things.In the early 1999 launched the Internet of Things core sensor network technology research, R & D level in the world; the second, sensor network field in the world, China is the standard one of the dominant country, the patent owner; third China is one of the countries to achieve a complete industrial chain of Things; Fourth, China's wireless communications network and broadband coverage provides a solid infrastructure to support the development of the Internet of Things; Fifth, China has become the world's first the three major economies, with strong economic strength to support the development of the Internet of Things.esThings widely used throughout the intelligent transportation, environmental protection, government, public safety, peace at home, smart fire, industrial monitoring, environmental monitoring, elderly care, personal health, floriculture, water monitoring, food traceability, enemy detection and intelligence collection and other fields.International Telecommunication Union in 2005, a report has portrayed the picture of the era of the "Internet of Things": car when the driver operational errors will automatically alarm; briefcase will remind the owner forgot something; clothes will "tell" washing machine color and water temperature requirements. Billion Bo logistics consulting vivid introduction of Things in the logistics field, for example, a logistics company, application of Things truck, when loading overweight, the car will automatically tell you overloaded and overload how many, but the space remaining , the severity of goods with how to tell you; when handling staff unloading a cargo packaging may be shouting "throw you hurt me", or "My dear, you do not get too barbaric, you can?"; when the driver and others gossip, trucks will pretend boss's voice roaring "stupid, the grid!Internet of things to make full use of a new generation of IT technology in all walks of life among, specifically, is embedded sensors and equipment to the power grid, railways, bridges, tunnels, highways, buildings, water systems, dams, oil and gas pipelines, etc.kinds of objects, and then "Internet of Things" with the existing Internet to integrate and realize the integration of human society and the physical system, which in this integrated network, there is the ability to super-powerful central computer cluster, integrated network staff implementation of real-time management and control of the machinery, equipment andinfrastructure, on this basis, the human can be more refined and dynamic management of production and life, to achieve the status of the "wisdom", to improve resource utilization and productivity levels, and improve human the relationship between the natural.There is no doubt that if the "Internet of Things" era, people's daily lives will have seen dramatic changes. However, the talk about privacy and radiation, the single-All items are implanted identification chip that now seems unrealistic. Is moving toward the era of the "Internet of Things", but this process may take a very long time.二、译文物联网1.定义内涵物联网的英文名称为The Internet of Things,简称：IOT。