考虑轨迹相似度的综合客运枢纽 出租车合乘方法研究  

Taxi Pooling Method of Urban Integrated Passenger Transport Hub with Trajectory Similarity

作　　者：吴玥琳 袁振洲[1] 陈秋芳 肖清榆 王文成 魏来[1] WU Yue-lin;YUAN Zhen-zhou;CHEN Qiu-fang;XIAO Qing-yu;WANGWen-cheng;WEI Lai(Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China;University of Transportation and Communication Viet Nam,Hanoi 100803,Vietnam)

机构地区：[1]北京交通大学综合交通运输大数据应用技术交通运输行业重点实验室,北京100044 [2]越南河内交通大学工程学院,越南河内100803

出　　处：《交通运输系统工程与信息》2020年第2期188-195,共8页Journal of Transportation Systems Engineering and Information Technology

基　　金：国家重点基础研究发展计划(2012CB725403).

摘　　要：针对综合客运枢纽出租车停靠点乘客滞留问题,提出一种考虑轨迹相似度的枢纽出租车合乘模型.以车辆数最小与总里程最短为目标,基于包围面积的轨迹相似度指标在形态上约束合乘后车辆的行驶轨迹.设计两阶段算法求解此NP-hard问题,第1阶段利用kmedoids方法对乘客需求聚类,第2阶段设计蚁群算法求解得到乘客匹配方案及合乘行驶路径.实测数据实验证明:该方法能较好优化车辆数和总里程,减少乘客等待时间;轨迹相似性度量约束能有效提高合乘后路径的JAC值,满足乘客希望合乘路径与原始路径差异最小化的心理.For the problem of passenger queue stranded in integrated passenger transport hubs,a taxi pooling model considering trajectory similarity is proposed in this paper.The objectives are to minimize the number of taxis and the total mileage.A trajectory similarity indicator based on boundary area is introduced to morphologically restrict the driving trajectory after taxi pooling.A two-phase algorithm is designed to solve this NP-hard problem.In the first phase,the k-medoids is used to clustering the demands;and in the second phase,the ant colony algorithm is designed to obtain the passenger matching schemes and driving routes.Finally,the results based on survey data prove that the method can decrease the number of taxis and mileage and reduce the waiting time of passengers.Besides,the JAC value of route after taxi pooling is improved because of the trajectory similarity constraint,which satisfies the passengers'expectations of the least difference between the taxi pooling route and the original route.

关 键 词：交通工程 枢纽出租车合乘 轨迹相似性度量 双目标优化 蚁群算法 聚类 

分 类 号：U469.12[机械工程—车辆工程]