文献类型：期刊文献

英文题名：Dynamic Travel Matching of Shared Autonomous Vehicles Considering Vehicle Power and Ridesharing

作者：Huo, Yueying[1,2]; Zhang, Yue[1]; Chen, Guoqing[2]; Li, Xiaojuan[3]

第一作者：Huo, Yueying

机构：[1] Transportation Institute, Inner Mongolia University, Inner Mongolia, Hohhot, China; [2] School of Mathematical Sciences, Inner Mongolia University, Inner Mongolia, Hohhot, China; [3] College of Urban Rail Transit and Logistics, Beijing Union University, Beijing, China

第一机构：Transportation Institute, Inner Mongolia University, Inner Mongolia, Hohhot, China

年份：2024

外文期刊名：SSRN

收录：EI(收录号：20240231773)

语种：英文

外文关键词：Efficiency - Fleet operations - Secondary batteries

摘要：The era of autonomous driving is coming, and Shared Autonomous Vehicles (SAVs) travel will be deployed in large numbers in major cities as a sustainable travel mode. This paper conducts method research and system development on SAVs dynamic travel matching considering vehicle power and ridesharing, aiming to provide a practical solution for SAVs travel matching. In this paper, the SAVs dynamic matching system and model are constructed to clarify the framework and operation rules of SAVs dynamic travel matching. The inputs of the system are road network data, SAVs data (location, passenger status, etc.), battery swapping station data (location, queuing length, etc.), and traveler data (origin, destination, etc.), and the outputs of the system are matching results and vehicle paths. To achieve the matching function of the system, the SAVs travel matching model is established, including the path model and the matching model. The path model is modeled with the objective of shortest vehicle path, which can obtain the shortest vehicle path for any idle SAVs to travel to or not to any battery swapping station when it provides service for any two travelers to be ridesharing; the matching model is modeled with the consideration of travelers' service quality and operator's benefits, as well as the vehicle's power consumption, which can obtain the optimal matching scheme, i.e., the optimal SAVs matching, optimal ridesharing matching, and optimal battery swapping station matching. The numerical experiment proves that the proposed system and model have high efficiency and stability. Meanwhile, comparative experiments of zone division or not are carried out to prove that the zone division method proposed in this paper can improve the operation efficiency of the system; comparative experiments of different fleet sizes and comparative experiments of vehicle swapping battery and different charging powers are carried out to explore the changes of each system index in different situations. ? 2024, The Authors. All rights reserved.