随机时变特征下基于行程时间的路径选择算法

基于南京市实测数据分析了道路交通流实际随机、时变特征,证实现有行程时间最短路径算法相关研究中对道路交通流的随机、时变特征的假设与实际不符.以反例论证道路交通流实际随机、时变特征下,自适应算法(Adaptive Routing Policy)在求解行程时间最短路径方面的无效性.针对交通模式时段内道路交通流随机、时间无关的特征,以及路段行程过程中行程时间的确切概率分布难以知晓的实际情况,提出基于历史概率分布的历史期望行程时间最短k路径基础上的考虑风险衡量及当前道路实际交通流状况的路径选择算法.

Path Choosing Algorithm Based on Travel Time under Stochastic Time-varying Characteristics

Based on the road traffic flow data of Nanjing City, this paper analyzed and summarized the actual stochastic time-varying characteristics of travel time of road segment, and draw a conclusion that the stochastic time- varying characteristics adopted by most current researches are inconsistent with the actual characteristics of the real traffic flow. This paper then demonstrated with counterexamples that the current adaptive routing policies is invalid in solving the shortest travel time problem under the actual characteristics of the real traffic flow. According to the stochastic and time independent characteristics of traffic flow during a certain traffic mode and the fact that the exact probability distribution of the current travel time of each road segment is difficult to know, this paper proposes a path selection algorithm which based on the k- th shortest expected travel time paths derived from historic probability distribution, incorporating risk measurement and the influences of current traffic status.