时段交通限行的时空动态建模与路径优化方法

Time and space dynamic modeling and route optimization method of time-dependent traffic restriction

针对现有道路网数据模型无法对不同车型、不同时段的动态网络拓扑进行有效建模与表达,传统路径规划方法缺乏对时段交通限行信息的支持,无法满足基本日常出行需求的问题,对时段交通限行中时段、车型(车号尾数)、限行信息的道路动态网络拓扑描述进行研究,提出不同时段交通限行下的道路动态网络拓扑模型,以实现不同车型(车号尾数)、不同时段复杂城市交通路网连通拓扑的动态建模;同时在Dijkstra算法的基础上,结合时段交通限行道路网络模型的特点,加入节点连通性判断,改进判断车道间及车道的车型、时间、转向限制等算法,构建了一种基于时段交通限行信息的路径优化方法,并以武汉市路网、武汉长江大桥和武汉长江二桥的时段交通限行信息为试验数据,完成不同车型、不同时段的跨江交通限行路径规划试验,以验证所提出模型的可行性。研究结果表明:基于时段交通限行的道路动态网络拓扑模型与基于时段交通限行信息的路径优化方法完善了当前交通数据模型与路径规划方法的不足,可满足在全新路网数据下的日常出行需求。

Aiming at the problem that the existing road network data model cannot make effective modeling and expression of dynamic network topology for different types and different time periods, and the traditional path planning method lacked the support of time-dependent traffic restriction information, which cannot meet the basic daily traffic demands, the dynamic network topology of time interval, vehicle type （number of mantissa） and restriction information in the time-dependent traffic restriction was analyzed. The dynamic road network topology model under different time-dependent traffic restrictions was proposed so as to achieve the dynamic modeling of the complex city traffic network connectivity topology for different vehicle types （number of mantissa） and different time intervals. Meanwhile, based on the Dijkstra algorithm, and combined with characteristics of network model of time-dependent traffic restriction road and other algorithms, such as judgment of nodes connectivity and improvement of judgment of vehicle type, time, steering limit, a route planning optimization method was constructed on the basis of time-dependent traffic restriction information. Taken the time-dependent traffic restriction information of Wuhan City road network, Wuhan Yangtze River Bridge and Wuhan Yangtze River Second Bridge as test data, the traffic restriction route planning experiment of different vehicle types and different periods was carried out to verify the feasibility of this model. The results show that the dynamic road network topology model and route optimization method on the basis of time-dependent traffic restriction perfect the deficiencies of the current traffic data model and route planning method, and also satisfy the daily travel demands under the new road network data. 2 tabs, 10 figs, 17 refs.