引用本文: 李佳怡, 张锦, 张静文, 王琪, 彭冬平. 城市公交乘客下车站点推算方法和有效性评价[J]. 武汉大学学报 ( 信息科学版), 2018, 43(8): 1172-1177.
LI Jiayi, ZHANG Jin, ZHANG Jingwen, WANG Qi, PENG Dongping. An Algorithm to Identify Passengers' Alighting Stations and the Effectiveness Evaluation[J]. Geomatics and Information Science of Wuhan University, 2018, 43(8): 1172-1177.
 Citation: LI Jiayi, ZHANG Jin, ZHANG Jingwen, WANG Qi, PENG Dongping. An Algorithm to Identify Passengers' Alighting Stations and the Effectiveness Evaluation[J]. Geomatics and Information Science of Wuhan University, 2018, 43(8): 1172-1177.

## An Algorithm to Identify Passengers' Alighting Stations and the Effectiveness Evaluation

• 摘要: 特大型城市的公交车上普遍安装了自动售票（auto fare collection，AFC）系统和车载GPS导航定位设备，记录了乘客出行与行车轨迹、时间等数据，连续运行的公交车和众多的出行乘客形成了城市公共交通运行和出行大数据。如何高效、准确地从公交大数据中识别公交乘客下车站点，对于提高交通运行效率、科学布局组织交通具有重要的意义和作用。基于深圳市公交车AFC和GPS数据，利用时间匹配和基于带噪声空间密度聚类的方法判别上车站点；在仅有的公交数据基础上，通过分析乘客出行行为，根据乘客多天的出行以及各站点的上车频率，利用乘客高频站点和下游站点吸引权，提出一种推算方法，实现乘客下车站点的推断。算法模型的检验和实例分析表明该方法的有效性。

Abstract: The construction of intelligent public transport system is an effective way to solve the pro-blem of urban traffic and to facilitate the residents to travel. Auto fare collection (AFC) system and vehicle GPS, which records passengers' trip and bus track data, are widely used in hyper-megalopolis. Using the bus big data efficiently to identify passengers' alighting stations is very important for urban transportation operations and organization. Based on AFC and GPS data, this paper presents an algorithm to identify passengers' alighting stations. We use the time matching method and density clustering to identify the bus stops. Considering the passengers' trip-chain and trip-section, this paper proposes an algorithm that combines the high frequency sites and site heat to identify the location of passengers' alighting stations possibility. The distance between the actual stations and the weight of the estimated points determines the accuracy of the forecast. The results illustrate the effectiveness and usefulness of the proposed method in identifying the passengers' alighting stations.

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