Adaptive signal control and coordination for urban traffic control in a connected vehicle environment: A review

Existing signal control systems for urban traffic are usually based on traffic flow data from fixed location detectors.Because of rapid advances in emerging vehicular communication,connected vehicle(CV)-based signal control demonstrates significant improvements over existing conventional signal control systems.Though various CV-based signal control systems have been investigated in the past decades,these approaches still have many issues and drawbacks to overcome.We summarize typical components and structures of these existing CV-based urban traffic signal control systems and digest several important issues from the summarized vital concepts.Last,future research directions are discussed with some suggestions.We hope this survey can facilitate the connected and automated vehicle and transportation research community to efficiently approach next-generation urban traffic signal control methods and systems.

Traffic Signals Control with Adaptive Fuzzy Controller in Urban Road Network

An adaptive fuzzy logic controller (AFC) is presented for the signal control of the urban traffic network. The AFC is composed of the signal control system-oriented control level and the signal controller-oriented fuzzy rules regulation level. The control level decides the signal timings in an intersection with a fuzzy logic controller. The regulation level optimizes the fuzzy rules by the Adaptive Rule Module in AFC according to both the system performance index in current control period and the traffic flows in the last one. Consequently the system performances are improved. A weight coefficient controller (WCC) is also developed to describe the interactions of traffic flow among the adjacent intersections. So the AFC combined with the WCC can be applied in a road network for signal timings. Simulations of the AFC on a real traffic scenario have been conducted. Simulation results indicate that the adaptive controller for traffic control shows better performance than the actuated one.

Research on an Urban Traffic Control System Based on DGPS

The basic principles of GPS (Global Positioning System) and DGPS (Differential GPS) are described. The principle and structure of vehicle navigation systems, and its application to the urban traffic flow guidance are analyzed. Then, an area coordinated adaptive control system based on DGPS and a traffic flow guidance information system based on DGPS are put forward, and their working principles and functions are researched. This is to provides a new way for the development of urban road traffic control systems.

Research on Deformation Control Indicators and Standard of Urban Traffic Tunnel Construction Adjacent to High-rise Building

The biggest environmental problem caused by the construction of tunnels adjacent to high-rise buildings is the settlement of buildings.The paper analyzes the influence of tunnel excavation on the deformation of the superstructure and the deformation mode of the superstructure.It introduces the indicators and standards for the construction control of tunnel adjacent to the building at home and abroad.Combined with the Yuzhong tunnel project under construction in Chongqing,the main monitoring indicators and control standards of the Yuzhong Tunnel passing through the main buildings are given after comprehensive analysis and considerations,which provide a reference for the deformation control indicators of similar urban traffic tunnels adjacent to high-rise buildings.

基于城市交通流自组织性的UTCS与UTFGS协同理论分析

以协同学理论框架分析城市交通流系统的自组织演化,对UTCS与UTFGS役使城市交通流系统自组织有序化进行分析。在分析城市交通流、UTCS与UTFGS的时空特性及两者关联关系的基础上,从子系统功能整合与功能互补的角度,提出UTCS与UTFGS协同研究体系结构和3项主要内容:信息协同、策略协同和协同实施,为UTCS与UTFGS协同的具体研究与实际应用提供理论指导。

基于Multi-Agent和“递阶集散”的UTCS与UTFGS协同实施研究

提出基于Multi-Agent技术和“递阶集散”的UTCS与UTFGS协同实施研究思路及UTCS与UTFGS的递阶集散体系结构,建立Agent的内部结构,采用博弈模型进行Agent间协同与全局优化,为UTCS与UTFGS协同的最终实现提供理论指导和方法依据。

Evolvement regularity of signal control parameters of urban road in cold region

In snow-icy road environment, the survey data indicate that the largest decrease in traffic flow running characters occurs when snow and ice begin to accumulate on the road surface. Saturation flow is decreased by 16% , speed is decreased by 30% , and start-up lost time is increased by 27%. Based on the signal control theory of HCM and Webster, the character values of traffic flow in different urban road environments were investigated, and the evolvement regularity of signal control parameters such as cycle, split, green time, offset, yellow time and red time in snow-icy road environment was analyzed. The impact factors and the changes in the scope of signal control parameters were achieved. Simulation results and practical application show that the signal control plan of road enviromnent without snow and ice will increase the vehicle delay, stop length and traffic congestion in snow-icy road environment. Thus, the traffic signal control system should address a suitable signal control plan based on different road environments.

Fuzzy Rules to Improve Traffic Light Decisions in Urban Roads

Many researchers around the world are looking for developing techniques or technologies that cover traditional and recent constraints in urban traffic con-trol. Normally, such traffic devices are facing with a large scale of input data when they must to response in a reliable, suitable and fast way. Because of such statement, the paper is devoted to introduce a proposal for enhancing the traffic light decisions. The principal goal is that a semaphore can provide a correct and fluent vehicular mobility. However, the traditional semaphore operative ways are outdated. We present in a previous contribution the development of a methodology capable of improving the vehicular mobility by proposing a new green light interval based on road conditions with a CBR approach. However, this proposal should include whether it is needed to modify such light duration. To do this, the paper proposes the adaptation of a fuzzy inference system helping to decide when the semaphore should try to fix the green light interval according to specific road requirements. Some experiments are conducted in a simulated environment to evaluate the pertinence of implementing a decision-making before the CBR methodology. For example, using a fuzzy inference approach the decisions of the system improve almost 18% in a set of 10,000 experiments. Finally, some conclusions are drawn to emphasize the benefits of including this technique in a methodology to implement intelligent semaphores.

Improving Vehicular Mobility in Urban Traffic Using Ubiquitous Computing

The paper introduces a novel paradigm to use ubiquitous computing in urban traffic control as a methodology to include the benefits of considering physical elements implicated in the environment. This promising idea arises from previous results in the literature, where ubiquitous computing achieves significant and promising results in diverse scenarios. Some works in the state-of- the-art clearly state that traditional traffic light signals are not capable of offering higher service levels when they should control the vehicular mobility because of different constraints. In this sense, the paper proposes an adaptation of the main ideas of ubiquitous computing as a metaphor to facilitate the interaction between users and traffic infrastructures in order to improve the users’ experience on the road.

基于主线密度预测的快速路入口匝道控制方法

针对快速路入口匝道区域拥堵问题,本文提出一种基于交通密度预测的入口匝道控制方法。通过分析快速路匝道区域的交通特性,定义交通流缓行状态,利用经典宏观交通流模型对快速路主线的历史密度进行统计,基于速度、密度参数进行聚类分析量化缓行状态交通参数特征。基于城市交通流的日变化特性,利用时间序列模型对交通密度进行短期预测,基于预测结果识别缓行状态。针对交通缓行状态,提出一种快速路主线交通密度与入口匝道排队长度的协同控制模型,通过控制入口匝道进而控制主线下游密度不超过临界密度,利用PSO-PID(Particle Swarm Optimization-Proportional Integral Derivative Control)算法对控制模型进行求解。以南昌市洪都大道快速路为例,对晚高峰缓行时段进行仿真分析,并与经典的匝道控制方案进行对比分析。结果表明:本文模型相较ALINEA模型,将匝道调节率提高11.0%,匝道平均排队长度和平均延误分别降低了14.8%和13.5%。

基于Stackelberg博弈的停车场管理策略

为了解决城市停车难问题,基于Stackelberg博弈论提出了停车场运营者与交通管理者共同决策的城市停车场管理策略。针对停车者、停车场运营者和交通管理者的交互关系,从博弈论角度分析了这三方参与者之间的影响,并建立了这三方参与者的相应效用函数;以交通管理者与停车场运营者利益主体矛盾最小化为目标,基于Stackelberg博弈建立了这三方的博弈模型,确定了实时停车场进出管理原则;基于数值仿真将差分进化算法与Kriging代理模型进行联立对博弈模型进行求解,得到相应停车预约管理方案及三方效用;通过数值仿真将基于Stackelberg博弈得到的方案与停车场运营者利益最大化方案进行对比分析。研究结果表明:在主线流量大、中、小三种情景下,基于Stackelberg博弈方案是各方利益矛盾最小的方案。

不同降雨量下基于宏观基本图的边界控制策略

在雨雪等不利天气条件下,城市交通拥堵加剧,北京、天津等大城市在降雨条件下经常发生多路段区域性交通拥堵。因此,根据天津市中心城区和市郊区域路网实际交通数据,以路网交通流宏观基本图模型为研究基础,对比不同降雨量以及不同路网的路网交通流时序和宏观基本图变化规律,分析不同降雨量对天津市中心城区和市郊区域路网交通状态的影响。基于不同降雨量下中心城区和市郊区域路网宏观交通流的变化规律,分别构建路网动态演化模型,并对模型的参数进行标定和有效性验证。针对降雨条件下路网发生的区域性拥堵问题,基于宏观基本图的边界控制分别设计了不同降雨量下中心城区和市郊区域路网控制策略,通过仿真实验分析验证了不同控制策略的效果,并给出了能够缓解中心城区和市郊区域路网拥堵的可行策略。结果表明:在小雨天气条件下,将从市郊区域向中心城区的交通流量的转移比例减小量控制在9%~50%范围之内时,中心城区与市郊区域交通状态更加均衡,路网调控效果更好;在大雨天气条件下,将从市郊区域向中心城区的交通流量的转移比例减小量控制在23%~50%范围之内时,中心城区与市郊区域交通状态更加均衡,路网调控效果更好。这表明该控制策略能够缓解中心城区和市郊区域路网的交通拥堵,保障路网交通系统的稳定运行。

高速公路出入口与邻接城市道路协同控制方法研究

针对高峰时期高速公路出入口及周边区域交通需求过大和交通负荷分布不均而引起的区域交通拥堵问题,研究了高速公路出入口与邻接城市道路协同控制方法。首先通过研究高速公路出入口区域内各节点之间进出的交通需求和通行能力关系,以收费站及其衔接交叉口通行量最大为控制目标,构建高速公路出入口交通协同控制模型。其次,研究了城市道路区域边界节点与高速公路出入口之间进出的交通需求和通行能力关系,结合红波协调控制思想,构建城市路段交通信号协调控制模型。最后以南宁市石埠高速公路出入口及周边区域为例,通过开展VISSIM仿真试验验证方法的有效性和可行性。仿真结果表明:虽然协调区域上的边界节点交通负荷有所增加,但高速公路出入口衔接节点平均排队长度和平均延误分别降低了22.36%和13.10%,其他节点总的平均排队长度降低了18.54%,从区域路网的角度考虑,仿真结果表明了本文方法能有效缓解高速公路出入口及周边的区域性交通拥堵问题。

基于时间自动机的无信号交叉口车路协同系统建模与验证

车路协同系统(cooperative vehicle infrastructure system,CVIS)是提高交叉口车辆通行安全的重要解决方案之一。针对CVIS现有技术规范和标准未明确系统对象状态交互的动态时序及迁移过程,无法有效保障系统的通行控制逻辑安全问题,采用形式化语言对无信号交叉口车路协同系统功能逻辑进行描述,验证系统对象的状态交互和控制逻辑安全,提高无信号交叉口的车辆通行安全性。以单车无冲突、双车冲突和多车冲突场景分别进行仿真,明确状态交互和使能迁移路径;结合工具和需求规范语句进行系统安全属性验证,证明了控制逻辑的可靠性和安全性,为研发高安全架构的车路协同系统提供了可信依据。

基于YOLOv5车辆识别和北斗定位的城市拥堵解决方案

为有效缓解城市交通拥堵,基于YOLOv5车辆识别和北斗定位技术构建了城市拥堵解决方案,实现了车辆运行信息实时采集、道路流量预测和智能交通控制等功能。YOLOv5车辆识别技术采集流量、车速等交通运行特征数据结合北斗定位技术采集的车辆运行特征数据,为智能交通控制决策与用户路线规划的数据支撑;智能控制终端分析采集到的数据,预测道路流量;数据传输模块完成采集输入并上传至智能控制终端和预测结果输出至智能交通控制设施,调节潮汐车道,实现智能信控;同时向用户反馈道路拥堵状况、提供路径选择建议。仿真运行结果表明,该解决方案面对两种不同的道路网可以使平均停车延误分别降低了9.0%、6.0%,总行驶时间分别降低了4.5%、6.3%,能够缓解交通拥堵。

基于UTC/SCOOT的城市交通控制管理平台设计与应用

首先分析了UTC/SCOOT系统产生数据类型和城市交通管理中存在的主要问题,在此基础上结合现代城市交通控制管理需求,以提高SCOOT系统综合利用率、充分发挥SCOOT系统效益、提高交通控制管理水平、丰富交通控制信息来源和节省建设资金为目的,设计了一种基于UTC/SCOOT的城市交通信号控制平台。最后给出此平台在北京市城市交通控制管理上的初步应用。

城市干线信号控制策略综合评估体系

城市干线信号交叉口是路网交通流汇合和分离的节点,是保障城市交通顺畅通行的关键所在。面对信号控制策略评估方法单一的问题,构建了一种面向交通效率、交通安全和交通环境的综合指标体系,并利用组合赋权-模糊综合评价(fuzzy comprehensive evaluation,FCE)模型对城市干线信号控制方案展开综合评估。最后以太原市兴华街干线的三种信控方案为例,借助VISSIM软件和间接安全模型,获取所需的评价指标值,计算综合得分。结果表明,在城市干线中使用信号联控方案最优,能有效提高干线的综合水平,其评估结果与实际结果较为一致,验证了评估体系的有效性。研究结果为城市干线信号系统的规划与管理提供了理论依据与技术支撑。

基于模型偏差学习的交通信号自适应优化方法

城市交通信号配时优化是保证交通系统整体运行效率的前提条件。传统基于模型的信号控制方法往往基于历史统计数据,并且底层交通流模型不可避免地存在模型偏差,影响控制方案的科学性及其实际应用效果。考虑模型与数据融合驱动,提出一种基于模型偏差学习的交通信号控制自适应优化方法,以最小化路网行程时间为目标,建立信号控制最优化模型。首先,针对交通流预测模型的模型偏差,引入偏差函数表示预测模型与实际交通流状态间的误差;其次,建立基于径向基函数(RBF)神经网络的偏差函数,结合实际交通流数据对模型偏差进行学习,提高偏差函数的拟合效果;在此基础上,提出考虑模型偏差信息的自适应优化方法,以提高信号控制方法的控制性能。以小型测试路网与实际路网为例进行算例分析,基于SUMO仿真对本文提出的模型偏差学习方法进行验证,考虑不同交通流量条件,与固定配时、模型预测控制进行比较,分析其控制性能指标。结果表明,模型与数据融合驱动的信号控制自适应优化方法能有效提高预测模型的准确性,降低路网行程时间,与基于模型的控制和模型预测控制方法相比路网累积行程时间平均减少了38.3%和25.6%,提升了路网的实际运行效果。最后在宣城实际路网的仿真验证了方法的有效性。

基于非线性交通流模型的交通子区边界控制策略研究

城市交通流具有复杂的非线性动态特征,用简化的线性交通流模型无法准确描述交通流的非线性特征。因此,在考虑扰动对子区边界控制影响的基础上,首先建立了考虑扰动的非线性城市宏观交通流模型,该模型能够更好地描述实际交通流的运行情况。其次,结合城市交通流运行的周期性特点,设计了基于迭代学习控制的子区边界控制策略,并利用Lipschitz条件和偏导数分析了迭代学习控制律的收敛性。最后,通过仿真案例验证了基于非线性交通流模型的交通子区边界控制策略的有效性。

考虑群体行为异质性的深港跨界口岸交通需求模型

口岸跨界交通是推动对外交流合作、经贸往来的重要支撑,精细化的跨界口岸交通需求分析和预测有助于提升口岸规划和治理水平、完善口岸基础设施服务质量。以深圳和香港地区之间的跨界客流为例,针对多元跨界群体在政策敏感性、目的地选择偏好、口岸选择偏好等方面的异质性,提出总量预测、客流分布、口岸选择“三阶段”跨界口岸交通需求模型框架。在方法上,以引力模型和离散选择模型为基础,充分考虑各类基础数据的现实局限性进行合理建模,使其兼具方法论行为基础和可用性。该模型框架从跨界群体出行行为异质性的角度为跨界口岸交通模型提供新视角,并为其他重大对外基础设施的交通需求建模提供参考。