基于二元饱和度的信号交叉口延误分析

为提高信号交叉口通行能力,利用二元饱和度方法,对交叉口单相位的车辆做延误分析,推导了适用于任意交通情况的路口延误模型,并对该模型进行算例分析。通过基于传统饱和度与二元饱和度控制约束条件下仿真对比验证,本延误模型计算简单易实现、在较高饱和度下路口车辆排队长度比传统饱和度控制方式短,另外时延也得到一定改善。     

信号交叉口微观仿真系统评价指标分析

对仿真系统的交通运行评价可以反映仿真系统模拟的准确性和控制结果的有效性.通过对交叉口车辆运行评价指标的关联性分析,建立了行车延误、平均排队长度、平均停车次数、二次排队率等4个相对独立有效的交叉口仿真系统运行评价指标.在对各评价指标的仿真属性分析的基础上提出了系统中评价指标的计算方法与具体实现原理.     

基于独立交叉口的自适应交通控制系统仿真研究

为实现城市道路资源优化配置,在LabVIEW软件平台上对基于独立交叉口的自适应交通控制系统进行了仿真研究。该系统以交通信号灯对车辆的行与停进行管制,同时根据各路段实时车流量与道路饱和率进行自适应变化,调整交通信号灯的运行周期,并修正各交通方向上绿信比,以提高交叉口单位时间通车率。测试结果表明,该仿真系统运行稳定,满足仿真研究的设计需求,可以为城市交通监测控制提供理论参考和城市交通组织管理提供决策依据。     

基于电子车牌的感应式干道协调控制方法研究

针对传统协调控制不能适应交叉口交通流的随机变化,传统感应式干道协调控制在高饱和流量时控制策略会失效等局限。该文改变传统感应控制理论以车辆间时间间隔作为控制依据,提出利用电子车牌以车辆密度作为感应控制绿灯是否延长的控制依据,当车辆密度高于设定的阈值则绿灯延续,反之,切换相位。通过利用VISSIM仿真对比分析表明,改进后的感应控制策略不仅可以克服高饱和流量下感应控制失效,而且可以有效减少交叉口的平均延误提高绿灯的利用率。     

城市交通区域协调的模糊控制研究

城市交通区域协调控制是智能交通重要的研究方向之一,其目的为了避免区域交通的拥塞。本文提出一种区域协调的模糊控制方法,结合相邻交叉口之间路段的饱和度及各交叉口相位方向的排队长度,建立了模糊控制规则,以对区域交通进行协调控制。采用典型四交叉口组成的区域对文中所提算法进行验证,结果显示该方法能够降低区域内路段的饱和度和交叉口平均延误。     

基于NiosⅡ的单点自适应控制器设计研究

为了提高道路交叉口通行能力,设计了一种单点交叉口自适应控制系统。系统采用SOPC方案,利用具有NiosⅡ软核的FPGA芯片设计了控制器的硬件,并利用遗传算法建立了信号配时优化模型、VHDL语言进行了遗传算法的硬件化、C语言编写了单点自适应控制器的程序。以成都市温江区南熏-光华大道路口的实测数据为例,进行软硬件系统联调的仿真实验,获得了交叉路口的信号配时优化方案。仿真结果表明,通过采用优化的方案进行交叉口信号配时后,各进口的车辆排队为零。验证了基于NiosⅡ单点在线自适应控制器的设计是有效的。     

一种城市单路口交通两级模糊控制方法

依据单路口4个方向车流信息,提出一种单路口交通两级模糊控制方法,采用模糊控制技术,无需建立精确的教学模型,对两相位的交叉路口,是一种基于车辆等待长度的单点信号交叉口交通实时模糊控制方法.根据城市交通实际状况,在考虑每个相位的关键车流和非关键车流的车辆到达交叉口信息的基础上,提出更有效的单路口交通实时模糊控制方法,并时该控制器进行仿真研究,仿真结果达到预期要求.     

基于强化学习的交叉口交通低排放信号控制研究

交叉口车辆排放较为复杂,尤其是在考虑初始排队长度的情况下,更是难以建立明确的数学模型。Q学习是一种无模型的强化学习算法,通过与环境的试错交互学习最优控制策略。本文提出了一种基于Q学习的交通排放信号控制方案。利用仿真平台USTCMTS2.0,通过不断地试错学习找到在不同相位排队长度下最优配时。在Q学习中添加了模糊初始化Q函数的方法以改进Q学习的收敛速度,加速了学习过程。仿真实验结果表明:强化学习算法取得较好的效果。相比较Hideki的方法,在车流量较高时,车辆平均排放量减少了13.9%,并且对Q函数值的模糊初始化大大加速了Q函数收敛的过程。     

基于通行优先的单交叉口感应控制优化设计

感应控制适用于一些交通流量较小,随机波动性较大的路口。在经典感应控制的基础上,引入一个通行优先权的概念,利用检测器进行数据采集,对于车辆的排队长度和车辆延误进行计算,通过权值计算来确定各个交通方向的交通需求,最后设置优先级来进行交通信号相位的顺序控制。该方法可以有效提高经典感应信号控制的效率,并在仿真实验结果中得到证实。     

基于云计算的车辆自动放行系统研究

针对现有车辆放行系统的局限性,文章提出了基于云计算的车辆自动放行系统。该系统将图像识别、网络和单片机、传感器等技术相结合,利用已有的网络服务,通过摄像头和低成本的硬件设施搭建一个车辆自动放行系统,将计算机串口与网络模块相连,通过云端服务器对车辆放行系统进行控制,利用手机APP和车辆放行管理系统相结合进行车辆自动放行。     

Real time analysis for traffic controller using 8085 based simulator

This paper presents the implementation of a traffic controller based on 8085 microcomputer simulator. This is a real time software traffic controller used for an isolated intersection, which gives a more comprehensive evaluation of system behaviour. Therefore, the average delay per vehicle in all arms of the intersection is minimized and the maximum vehicle queue length in each arm of the ‘halt’ phase is limited and the queue length is controlled. In order to accomplish these criteria, an algorithm has been constructed utilizing vehicle actuated signals. From this algorithm the real traffic control period is controlled in accordance with the vehicle queue situated in each arm of the intersection; dealing with different situations interactively and successfully. The simulator has been implemented in Fortran IV and runs successfully on Honeywell 66/10.     

单点自适应控制的配时方法研究

针对交通饱和期间车辆滞留的问题,提出了一种信号机单点自适应控制的配时方法。考虑到道路车辆密度、流量检测方法等因素对交通流量的影响,改进了交通流量检测方法,并对实时检测的交通流量进行补偿修正,同时结合F-B配时方法,对周期时长和绿信时间进行优化,从而加快滞留车辆的消散速度,有效地缓解车辆滞留情况。     

多信道无线通信网混合业务接入控制的离散排队分析

基于无线通信网的运行机制、实时性和非实时性混合业务对无线通信网络不同服务质量(QoS)要求,设计了实时性业务优先接入控制策略,建立了无线通信网络的混合业务带有优先接入控制的多服务台离散时间排队模型Geo1 Geo2/Geo1,Geo2/s,s(PP)。并且应用矩阵几何解方法,对该排队模型进行精确分析,得到了系统的主要性能指标:实时性业务和非实时性业务的平均队长、实时性业务的阻塞概率、系统信道利用率等结果。     

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.     

一种实时单向绿波的柔性控制研究

传统的定时绿波控制难以适应动态的交通流,本文提出了一种单向绿波的柔性控制策略,通过动态调整相位差实现对干线交通流变化的实时响应,同时,考虑了驾驶员的心理特性,进行相位差的小步长调整,实现柔性控制。实验结果证明,算法优于传统的定时控制方法,可以在保证绿波的前提下,使驾驶员的情感平滑地进行过渡。     

Performance analysis of rate control scheme considering queue dynamics

In high-speed networks with a large bandwidth-delay product, it is very important to effectively control outstanding packets at the source to avoid network breakdown due to buffer overflows. We propose a new rate-based flow control scheme that aims at control of best-effort traffic instead of guaranteed traffic. Our scheme directly controls the rate at which the source can send packets based on feedback information determined by both the average queue length and queue dynamics (queue increase or decrease). We show through analysis and simulation that the rate and queue fluctuations of the proposed scheme can be made much smaller than those of the conventional scheme, based on binary feedback determined by the average queue length. Therefore, efficient network resource utilization and better throughput/delay performance can be easily achieved.     

Using adaptive linear prediction to support real-time VBR videounder RCBR network service model

A dynamic bandwidth allocation strategy to support variable bit rate (VBR) video traffic is proposed. This strategy predicts the bandwidth requirements for future frames using adaptive linear prediction that minimizes the mean square error. The adaptive technique does not require any prior knowledge of the traffic statistics nor assume stationarity. Analyses using six one-half-hour video tracts indicate that prediction errors for the bandwidth required for the next frames and group of pictures (GOP) are almost white noise or short memory. The performance of the strategy is studied using renegotiated constant bit rate (RCBR) network service model and methods that control the tradeoff between the number of renegotiations and network utilization are proposed. Simulation results using MPEG-I video traces for predicting GOP rates show that the queue size is reduced by a factor of 15-160 and the network utilization is increased between 190%-300% as compared to a fixed service rate. Results also show that even when renegotiations occur on the average in tens of seconds, the queue size is reduced by a factor between 16-30