基于交通灯配置的车辆诱导机制研究
发布时间：2018-07-18 08:03
【摘要】：随着社会的高速发展,交通拥堵问题严重的影响了国家城市化的进程。智能交通系统作为一门新兴的研究课题,为解决城市交通拥堵问题提供了新的解决方案。交通控制和车辆诱导作为智能交通系统的两个重要组成部分,在解决城市交通拥堵问题上越来越受到关注和重视。在现有的智能交通系统研究中,主要利用交通控制子系统对路况进行处理,而车辆诱导子系统完成对车辆的路径规划,大多偏重于对交通灯控制和车辆诱导的分开研究。但是在实际的城市交通路网中,通过将交通灯控制与车辆诱导进行集成,能够进一步促进道路拥堵的疏散,且有助于提高出行者的行车效率。本文针对交通灯控制与车辆诱导的集成进行了研究,针对车辆诱导的具体实现场景,提出了基于交通灯配置的车辆诱导机制,该车辆诱导机制主要通过两个步骤来完成对路网中道路拥堵的消散以及车辆的诱导调度,这两个步骤分别是:(1)路网流量均衡策略:根据交通的动态路况自动配置交通灯的绿信比,完成对拥堵道路的疏散;(2)路网流量优化分配策略:对全网车辆进行诱导分配,达到整个路网中车辆总行驶时间最少。通过MATLAB仿真工具,对基于交通灯配置的车辆诱导机制进行了仿真,并比较分析了车辆诱导前后路网中平均饱和度、饱和度方差、全网车辆行驶时间等参数变化情况,实验结果表明,通过基于交通灯配置的车辆诱导机制能够有效地降低路网中的平均饱和度及饱和度方差,均衡整个路网的交通流量,同时能够降低全网车辆的总行驶时间,提高了路网的通行能力。此外,本文将交通灯调整时间作为车辆诱导算法中的一个时间因子,进一步提出了基于交通灯配置的车辆诱导算法ED*算法,通过车辆ED*诱导算法完成对路网中的车辆个体进行诱导,完成对其出行路径的动态规划,以达到使微观车辆个体行驶时间最少的目的。通过VC++6.0完成了对ED*车辆诱导算法的计算及仿真,并与A*算法、D*Lite算法进行比较,实验结果表明,在路况信息发生变化后,ED*算法在重新规划路径的计算速度上具有显著的提高,有助于提高路网中车辆的行驶效率,适用于城市动态交通路网。
[Abstract]:With the rapid development of society, traffic congestion has seriously affected the process of urbanization. As a new research subject, Intelligent Transportation system (its) provides a new solution to the problem of urban traffic congestion. Traffic control and vehicle guidance, as two important components of intelligent transportation system, have been paid more and more attention to in solving the problem of urban traffic congestion. In the existing research of Intelligent Transportation system, the traffic control subsystem is mainly used to deal with the road conditions, while the vehicle guidance subsystem completes the path planning of vehicles, most of which focus on the separate study of traffic light control and vehicle guidance. But in the actual urban traffic network, by integrating traffic light control with vehicle guidance, the evacuation of traffic congestion can be further promoted, and the efficiency of travelers can be improved. In this paper, the integration of traffic light control and vehicle guidance is studied, and the vehicle guidance mechanism based on traffic light configuration is proposed. The vehicle induction mechanism mainly completes the dissipation of road congestion and the induced scheduling of vehicles in the road network through two steps. The two steps are as follows: (1) the strategy of road network flow balance: according to the dynamic traffic conditions, the green signal ratio of traffic lights is automatically configured to complete the evacuation of congested roads; (2) the optimal allocation strategy of road network flow: the inductive allocation of the whole network vehicles, The total vehicle travel time is the least in the whole road network. Through MATLAB simulation tool, the vehicle guidance mechanism based on traffic light configuration is simulated, and the variation of average saturation, saturation variance, vehicle travel time and so on in the road network before and after vehicle guidance are compared and analyzed. The experimental results show that the vehicle guidance mechanism based on traffic light configuration can effectively reduce the average saturation and saturation variance in the road network, balance the traffic flow of the whole network, and reduce the total travel time of the whole network vehicle at the same time. The capacity of the road network has been improved. In addition, the traffic light adjustment time is taken as a time factor in the vehicle guidance algorithm, and an ED* algorithm based on traffic light configuration is proposed. In order to achieve the goal of minimizing the driving time of individual vehicles in the road network, an ED* guidance algorithm is used to guide the individual vehicles in the road network and to complete the dynamic planning of their travel paths. Through VC 6.0, the calculation and simulation of ED* vehicle guidance algorithm are completed, and compared with the A* algorithm, the experimental results show that after the change of road condition information, the calculation speed of ED* algorithm is significantly improved in re-planning the path. It is helpful to improve the driving efficiency of vehicles in the road network and is suitable for the urban dynamic traffic network.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495
本文编号：2131264
[Abstract]:With the rapid development of society, traffic congestion has seriously affected the process of urbanization. As a new research subject, Intelligent Transportation system (its) provides a new solution to the problem of urban traffic congestion. Traffic control and vehicle guidance, as two important components of intelligent transportation system, have been paid more and more attention to in solving the problem of urban traffic congestion. In the existing research of Intelligent Transportation system, the traffic control subsystem is mainly used to deal with the road conditions, while the vehicle guidance subsystem completes the path planning of vehicles, most of which focus on the separate study of traffic light control and vehicle guidance. But in the actual urban traffic network, by integrating traffic light control with vehicle guidance, the evacuation of traffic congestion can be further promoted, and the efficiency of travelers can be improved. In this paper, the integration of traffic light control and vehicle guidance is studied, and the vehicle guidance mechanism based on traffic light configuration is proposed. The vehicle induction mechanism mainly completes the dissipation of road congestion and the induced scheduling of vehicles in the road network through two steps. The two steps are as follows: (1) the strategy of road network flow balance: according to the dynamic traffic conditions, the green signal ratio of traffic lights is automatically configured to complete the evacuation of congested roads; (2) the optimal allocation strategy of road network flow: the inductive allocation of the whole network vehicles, The total vehicle travel time is the least in the whole road network. Through MATLAB simulation tool, the vehicle guidance mechanism based on traffic light configuration is simulated, and the variation of average saturation, saturation variance, vehicle travel time and so on in the road network before and after vehicle guidance are compared and analyzed. The experimental results show that the vehicle guidance mechanism based on traffic light configuration can effectively reduce the average saturation and saturation variance in the road network, balance the traffic flow of the whole network, and reduce the total travel time of the whole network vehicle at the same time. The capacity of the road network has been improved. In addition, the traffic light adjustment time is taken as a time factor in the vehicle guidance algorithm, and an ED* algorithm based on traffic light configuration is proposed. In order to achieve the goal of minimizing the driving time of individual vehicles in the road network, an ED* guidance algorithm is used to guide the individual vehicles in the road network and to complete the dynamic planning of their travel paths. Through VC 6.0, the calculation and simulation of ED* vehicle guidance algorithm are completed, and compared with the A* algorithm, the experimental results show that after the change of road condition information, the calculation speed of ED* algorithm is significantly improved in re-planning the path. It is helpful to improve the driving efficiency of vehicles in the road network and is suitable for the urban dynamic traffic network.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495
【参考文献】
相关硕士学位论文 前1条
1 刘宁;城市道路阻抗模型的研究与应用[D];大连理工大学;2012年
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