基于公共交通的高精度时空可达模型与算法

High-Resolution Spatio-Temporal Modeling and Algorithm of Public Transit Accessibility

公共交通作为我国城市居民的主要出行方式,对其可达性的研究具有非常重要的价值和意义.然而,由于站点位置、固定线路、时刻表等条件的限制,使得公共交通可达性的研究具有一定的特殊性.针对已有研究存在的可达精度不高或者无法进行大规模可达分析等问题,基于路网、公交网络、地铁网络和时刻表信息建立高精度时空网络模型,设计时间依赖条件下枢纽站点和A*算法相结合的快速公交换乘算法.以武汉市为例,对其进行大规模高精度时空可达分析,证明了模型的可靠性和算法的高效性.

Public transit system plays the central role for traveling in cities of China. Therefore, it is important to study the accessibility provided by public transit. However, public transit influences accessibility in unique ways, which depends significantly on the routes, schedule, location of the users as well as the time of day the trip is made. Existing researches scarcely establish high-resolution spatio-temporal models, calculate travel time accurately, consider the time constraint, or achieve large-scale accessibility analysis. This paper establishes a high-resolution spatio-temporal model based on road network, bus network, metro network and schedule information, designs an efficient time-dependent transfer algorithm combining Hub with A＊ Algorithm. To demonstrate the reliability of the model and the efficiency of the algorithm, a case study is presented with respect to mapping accessibility of public transit in Wuhan.