基于PLC步进编程的交通灯控制设计

交通灯是交通管理中的重要组成部分,可以充分利用PLC进行交通灯的控制设计,不仅能够实现交通灯的自动控制,还可以充分发挥PLC自身的通讯联网功能,统一管理同一条道路上的信号灯组成的局域网,可以大大提升交通灯的控制效率,实现对交通的科学管理,减少车辆在红绿灯的等候时间,并维持交通秩序。本文就基于PLC步进编程交通灯控制设计进行探讨,旨在为人们提供一定的参考。     

用Java编程模拟实现城市交通控制系统

本系统实现车流量数据采集、交通灯的设计与控制、车辆实时分流、交通应急管制四个功能。车流量数据采集可以给交通信号灯时间显示和车辆分流提供依据。交通信号灯的设计采用多线程技术,实现东西方向和南北方向交通灯交替显示。车辆分流作用是在某条路的车流量超出它的最大承载量时给司机提出最佳换行路线。     

论电子信息技术在智能交通信号灯控制中的应用

随着国家现代化以及工业化进程的加快,智能交通信号灯也急需整改和完善。对交通信号灯的研究,主要为了实现减少交通拥挤,减少交通事故等交通优化问题。现代化技术实现控制智能交通灯系统的方法非常多,比如PLC或者单片机、虚拟仪器等方法。本文研究在现代电子信息技术下,智能交通信号灯控制方法,依据具体情况进行实际调整。     

基于视频识别的智能交通灯控制器设计

目前我国大部分城市的交通灯控制仍然采用定时控制,无法有效利用道路资源。本文重点介绍了一种基于可编程控制器的智能交通灯控制器的设计,通过视频识别获取车流量信息,从而控制交通灯的红绿灯时间,更大限度地缩减车辆等待时间,缓解交通压力。     

基于图像处理和PLC的交通信号灯控制系统

应用图像处理技术,研究了PLC交通信号灯控制系统,发现交通信号灯亮的时间长度可以通过检测到的车辆运行信息控制,这表明将传统的路口四相位扩展到十二相位,能够充分利用传统信号灯控制系统中的空等待时间,在不改变路况的现有条件下,有效提高路口车辆的通行效率。     

基于FPGA的交通信号灯控制系统设计

为了使交通信号灯系统针对车流量变化做出有效应对,设计了一种智能交通信号灯控制系统。该系统结合道路传感器反馈的车流信息,采用有限状态机实现了交通信号灯全感应自适应控制方案,得到最优信号灯转化和时间分配。该系统采用FPGA设计,结合成都科华北路复杂交通路口车辆统计信息,对该系统进行仿真和验证。结果表明,该系统能减少17.550%的车辆平均延误时间,保障交通顺畅,提高了效率。     

单片机智能交通灯设计

本设计的目的在于设计出一个具有实用价值的、性价比较高的智能交通灯的控制系统。在对目前交通控制进行深入分析的基础上,采用检测传感、实时调整智能化控制的实现技术。系统包括直行、左转、右转、以及基本的交通灯的功能,能够根据十字路口双车道车流量的情况控制交通信号灯按特定的规律变化。实现自动控制和在紧急情况下能够手动切换信号灯让特殊车辆优先通行等。     

PLC应用于交通信号灯控制系统

如何应用PLC实现十字路口交通信号灯自动控制,通过分析对交通信号灯的控制要求,对PLC控制系统进行软、硬设计.同时将PLC的逻辑控制、数据运算、数据比较、数据传送通过程序有机的结合起来,既控制交通灯的变化,还有时间显示.     

基于PLC的智能交通信号灯控制系统设计

文中基于边缘计算等高端技术,提出设备信息的本区域化路口智能交通灯IoT方案,以此完成路口设备的边缘连接与信息化管理。通过对系统商品模块的设计研发语言路口的具体检测方式,验证电力线载波物联与边缘智能管控的可行性,为完成智慧路口的信息互通互联与管控提供可参考依据。另外,针对我国城市交通堵塞的情况,对传统的固定用时下的交通状况进行改善,提出一种多元化的作业模式下的PLC智能交通灯的控制系统,通过预埋传感设备对路段上车流量实施监督与控制,根据车流量的改变情况来控制交通灯。结果表明,通过声音检测设备对特殊车辆实施检测,可实现车辆的迅速通信。通过对PLC交通灯进行控制,能够减少车辆的等待时间,并大幅度提升十字路口的通行能力。     

基于单片机的智能交通灯控制系统设计

本文采用AT89C52单片机设计了一款智能交通灯控制系统,该系统通过检测和比较南北方向、东西方向车流量的大小,灵活地调节交通灯的通行时间,达到对交通灯自动实时控制的目的。系统不但在传统模式下能够正常工作,还可以实现根据车流量自动调节交通信号灯的智能模式,以及特殊车辆到来时的紧急模式,有效地缓解了车辆拥堵情况,提高了车行效率和道路利用率。     

An efficient dynamic traffic light scheduling algorithm considering emergency vehicles for intelligent transportation systems

Traffic lights have been installed throughout road networks to control competing traffic flows at road intersections. These traffic lights are primarily intended to enhance vehicle safety while crossing road intersections, by scheduling conflicting traffic flows. However, traffic lights decrease vehicles’ efficiency over road networks. This reduction occurs because vehicles must wait for the green phase of the traffic light to pass through the intersection. The reduction in traffic efficiency becomes more severe in the presence of emergency vehicles. Emergency vehicles always take priority over all other vehicles when proceeding through any signalized road intersection, even during the red phase of the traffic light. Inexperienced or careless drivers may cause an accident if they take inappropriate action during these scenarios. In this paper, we aim to design a dynamic and efficient traffic light scheduling algorithm that adjusts the best green phase time of each traffic flow, based on the real-time traffic distribution around the signalized road intersection. This proposed algorithm has also considered the presence of emergency vehicles, allowing them to pass through the signalized intersection as soon as possible. The phases of each traffic light are set to allow any emergency vehicle approaching the signalized intersection to pass smoothly. Furthermore, scenarios in which multiple emergency vehicles approach the signalized intersection have been investigated to select the most efficient and suitable schedule. Finally, an extensive set of experiments have been utilized to evaluate the performance of the proposed algorithm.     

EPO: An Optimization technique for Urban Traffic Management While Limiting the Pollution using WSN

In the world, the vehicular traffic is endlessly expanding all over the place and at the point of intersection can cause terrible traffic congestion. Today, the vast majority of the traffic lights is fixed green light system; therefore, it is resolved without considering the incidence of vehicles emergency. The vehicles of emergency like fire trucks and ambulances are need to reach their destinations at the time. Many people face danger situation when they spent lot of time in traffic. To resolve the above mentioned problem, this paper proposed an optimization technique (Emperor Penguin Optimizer) for urban traffic organisation while limiting the pollution using wireless sensor network. At first, the basic parameters are explained like headway, throughput, density, flow, volume, and waiting time. After that, find the traffic pollutions and calculate the emergency vehicle based on the priority. Lastly, based on the above conditions, the traffic light will be displayed. The proposed work will be evaluated by using MATLAB in terms of latency (32 s), buffer (30 KB/s/vehicle), packet delivery ratio (99%), delay (0.7 s), overhead (20%), packet loss ratio (1%), throughput (99%), and time. Proposed work can also be compared with other recent techniques for the research evaluation.     

<Emphasis Type="Italic">EIAS-CP:</Emphasis> new efficient identity-based authentication scheme with conditional privacy-preserving for VANETs

In VANETs, vehicles broadcast traffic-related messages periodically according to Dedicated Short Range Communication protocol. To ensure the reliability and integrity of messages, authentication schemes are involved in VANETs. As traffic-related messages are time-sensitive, they must be verified and processed timely, or it may cause inestimable harm to the traffic system. However, the OBUs and the RSUs are limited in computation ability and cannot afford vast messages’ verification. Recently, some identity-based authentication schemes using bilinear pairing have been proposed to improve the efficiency of message verification for VANETs. Nevertheless, the bilinear pairing is not suited for VANETs due to its complex operations. The design of an efficient and secure authentication scheme with low computation cost for VANETs still is a rewarding challenge. To settle this challenge, a new efficient identity-based authentication scheme is proposed in this paper. The proposed scheme ensures reliability and integrity of messages and provides conditional privacy-preserving. Compared with the most recent proposed authentication schemes for VANETs, the computation costs of the message signing and verification in the proposed scheme reduce by 88 and 93 % respectively, while security analysis demonstrates that our proposed scheme satisfies all security and privacy requirements for VANETs.     

New vehicle sequencing algorithms with vehicular infrastructure integration for an isolated intersection

Traffic congestion at intersections is one of the main issues to be addressed by today??s traffic management schemes. Countless efforts have been made directed toward efficiently improving the traffic situation at intersections. In this paper, we present a new traffic control strategy for an isolated intersection, in which there are no more traffic lights. Instead, vehicles embedded with In-Vehicle Information Systems communicate with the center Infrastructure to obtain their access time to the intersection. We mainly focus on the vehicle sequencing algorithms with the analysis of received information. A Branch and Bound algorithm and a heuristic are proposed to evacuate the approaching vehicles as soon as possible. Structural properties of the problem are carefully investigated to simplify the search procedure of an optimal passing sequence. Computational experiments and simulations in evacuation time, average waiting time and average queue size demonstrate the performance gain obtained when using the proposed schemes.     

车载网络中的数据分发策略

通过车载网络(VAETNs)能够有效提高交通管理系统(TMS)的数据传输。然而,由于通信距离短以及车辆的移动,完成VANETs中的数据传输是一项挑战任务。为此,提出基于复杂网络指标的数据传输(MCDD)策略。MCDD策略依据二跳邻居的信息,并通过介数中心性和度中心性两项性能指标选择转发节点,进而降低开销和缩短传输时延。仿真结果表明,相比于基于区划分的全-分布式流量管理系统(FTMS),MCDD策略的交通拥塞时间缩短了约48.95%,平均行驶速度提高了约8%。     

Autonomic Navigation System Based on Predicted Traffic and VANETs

To avoid an expected traffic jam, drivers make detours based on limited information; however, the majority following the alike routes may result in an unexpected congestion. Conventional navigation approaches are unable to respond to the unexpected congestion because these approaches do not consider the routes taken by other vehicles. Navigation systems that utilize global traffic information can improve gas consumption, CO₂ emissions and travel time. Therefore, in this paper, the authors propose an autonomic navigation system (ANS) operating over vehicular ad-hoc networks (VANETs). The proposed ANS adopts a hierarchical algorithm to plan vehicle routes. The proposed ANS imitates the human nervous system when managing the navigation system, in which vehicles monitor traffic via VANETs. Moreover, this paper proposes a time-dependent routing algorithm that uses a novel traffic prediction method based on the routes of vehicles. This paper adopts EstiNet as simulator tool that dominates hundreds or thousands of VANET-based vehicles routing in two maps, Manhattan area, and Taipei city. The results show that the proposed ANS improves the average speed by 60.02 % when compared with the shortest path first (SPF) algorithm and by 15.49 % when compared with the distributed method of a traffic simulation in the Manhattan area. The proposed ANS also improves the average speed by 30.5 % when compared with the SPF algorithm and by 15.8 % when compared with the distributed method of a traffic simulation in the Taipei area. Furthermore, to emulate real environments, there is a scenario in which only a portion of the vehicles complies with the proposed ANS.     

SafeAnon: a safe location privacy scheme for vehicular networks

In most safety applications within vehicle ad-hoc networks (VANETs), vehicles need to periodically broadcast messages with information of their precise positions to others. These broadcast messages, however, make it easy to track vehicles and will likely lead to violations of personal privacy. Unfortunately, most of the current location privacy enhancement methodologies in VANETs suffer some shortcomings and do not take driving safety into consideration. In this paper, we propose a safe distance based location privacy scheme called SafeAnon, which can significantly enhance location privacy as well as traffic safety. By simulating vehicular mobility in a cropped Manhattan map, we evaluate the performance of the proposed scheme under various conditions. The mean entropy, warning broadcast ratio, and mean silent period of SafeAnon scheme are increasing 58%, 281%, and 50% respectively than the random silent period (RSP) scheme. The total broadcast ratio is also 33% less than that in the RSP scheme.     

A study on traffic signal control at signalized intersections in vehicular ad hoc networks

The Seoul metropolitan government has been operating a traffic signal control system with the name of COSMOS (Cycle, Offset, Split MOdel for Seoul) since 2001. COSMOS analyzes the degrees of saturation and congestion which are calculated by installing loop detectors. At present, subterranean inductive loop detectors are generally used for detecting vehicles but their maintenance is inconvenient and costly. In addition, the estimated queue length might be influenced by errors in measuring speed, because the detectors only consider the speed of passing vehicles. Instead, we proposed a traffic signal control algorithm which enables smooth traffic flow at intersections. The proposed algorithm assigns vehicles to the group of each lane and calculates traffic volume and congestion degree using the traffic information of each group through inter-vehicle communication in Vehicular Ad-hoc Networks (VANETs). This does not require the installation of additional devices such as cameras, sensors or image processing units. In this paper, the algorithm we suggest is verified for AJWT (Average Junction Waiting Time) and TQL (Total Queue Length) under a single intersection model based on the GLD (Green Light District) simulator. The results are better than random control method and best-first control method. For a generalization of the real-time control method with VANETs, this research suggests that the technology of traffic control in signalized intersections using wireless communication will be highly useful.     

A roadside unit‐based localization scheme for vehicular ad hoc networks

Vehicular Ad Hoc Networks (VANETs), designed to ensure the safety and comfort of passengers via the exchange of information amongst nearby vehicles or between the vehicles and Roadside Units (RSUs), have attracted particular attention. However, the success of many VANET applications depends on their ability to estimate the vehicle position with a high degree of precision, and thus, many vehicle localization schemes have been proposed. Many of these schemes are based on vehicle‐mounted Global Positioning System (GPS) receivers. However, the GPS signals are easily disturbed or obstructed. Although this problem can be resolved by vehicle‐to‐vehicle communication schemes, such schemes are effective only in VANETs with a high traffic density. Accordingly, this paper presents a VANET localization scheme in which each vehicle estimates its location on the basis of beacon messages broadcast periodically by pairs of RSUs deployed on either side of the road. In addition, three enhancements to the proposed scheme are presented for the RSU deployment, RSU beacon collisions, and RSU failures. Overall, the ns‐2 simulation results show that the localization scheme achieves a lower localization error than existing solutions on the basis of vehicle‐to‐vehicle communications and is robust toward changes in the traffic density and the vehicle speed. Copyright © 2012 John Wiley & Sons, Ltd.     

Road traffic and geography topology based opportunistic routing for VANETs

The message delivery .ratio and transmission delay is affected deeply by road traffic flow in vehicular ad hoc networks （VANETs）. An opportunistic routing based on geography and road traffic flow for VANETs （ORRIS） was proposed. ORRIS leverages the knowledge of geography positions, motion vectors and road traffic flows. In order to estimate the traffic flow density, the history of encounter number of the vehicles in the opposite direction is considered in ORRIS. The forwarding decisions are made by distributed vehicles based on the geography topology and the road traffic flow. The real map based simulation results show that ORRIS has a better performance than other algorithms, especially when the road traffic is busy or the traffic flow rates have great differences between roads.