基于出租车经验路径的城市可达性计算方法

可达性计算中,始发地-目的地(Origin-Destination, 简称OD)间的路径规划是一个很重要的问题。传统基于最短路径算法的路径规划存在与现实不符的可能,因此考虑出租车载客的经验路径,更符合现实的出行。本文基于潜能模型,综合考虑了人口分布、交通路网特征,兴趣点分布等因素,提出了城市可达性的计算方法,其中OD间行程时间采用出租车经验路径行程时间。然后以广州市中心城区为研究区域,进行网格划分,不同的网格分别作为OD;并采用一个月的广州出租车GPS数据,从中提取大量的载客经验路径,建立出租车经验路径数据库,将OD间的经验路径行程时间计算出来,最后完成了广州中心城区的可达性计算和分析。结果表明,广州中心城区可达性符合典型的势能分布,城市可达性在中心区最高,然后逐步向郊区递减。该结果验证了城市可达性计算方法具有较好的实用性和可计算性。

A Computational Algorithm of Urban Accessibility Based on Experiential Taxi Path

Path search between OD is a main factor in urban accessibility calculation.The traditional shortest path search algorithm does not match the reality,so taking experiential path of taxi as travel path is considered more reasonable.Based on potential model,this paper proposes a computational algorithm of urban accessibility,which takes into account the distribution of population,the characteristics of traffic network and the distribution of POI,and it takes the travel time of experiential path as the time cost between OD.Then it chooses Guangzhou city as the study area,and divides urban areas into cells,and the OD is composed by different cells.At the same time,GPS data of Guangzhou taxi in a month was explored,and mass experiential paths were abstracted and stored in database,travel time of each experiential path was computed.Finally,urban accessibility of Guangzhou city was computed and analyzed.As the result shows,urban accessibility of Guangzhou city was a typical potential distribution,its value in central area is the highest,then it decreases as getting closer to suburban areas.The result also proves the computational algorithm’s practicability and its calculability.