Dynamic Ridesharing Matching of Shared Autonomous Vehicles as Connection to Metro

被引：0
|
作者：
Huo Y.-Y. [1 ,2 ]
Zhang Y. [1 ]
Li X.-J. [3 ]
Chen G.-Q. [2 ]
机构：
[1] Transportation Institute, Inner Mongolia University, Inner Mongolia, Hohhot
[2] School of Mathematical Sciences, Inner Mongolia University, Inner Mongolia, Hohhot
[3] College of Urban Rail Transit and Logistics, Beijing Union University, Beijing
来源：
Zhongguo Gonglu Xuebao/China Journal of Highway and Transport | 2024年 / 37卷 / 06期
基金：
中国国家自然科学基金;
关键词：
dynamic ridesharing matching; metro connection; path selection; shared autonomous vehicles; traffic engineering;
D O I：
10.19721/j.cnki.1001-7372.2024.06.024
中图分类号：
学科分类号：
摘要：
To integrate shared autonomous vehicles (SAV) with the metro, this study proposes the use of SAV as the connection of the metro's first mile (FM) and last mile (LM). A dynamic ridesharing matching system was constructed to clarify the framework and operating rules of SAV connected to the metro. The system inputs arc the road network data, SAV data (location, passenger status, etc.), and traveler data (origin, destination, etc.), and the outputs are the matching results and travel paths. Travel path and travel matching models were developed to realize the ridesharing matching function of the system. The travel path model considers the minimization of the detour time of travelers, which can output the travel path of any two travelers when ridesharing, and was used for the parameter calculation of the travel matching model. The travel matching model considers the traveler service quality and operator benefits as well as the joint optimization of SAV and metro schedules to obtain the optimal travel matching scheme, including the matching of travelers to SAV and travelers to travelers. The metro in Manhattan, New York was selected for a case study at four travel demand scales (2 160, 4 320, 6 480, and 8 640 trips • h_1). The results show that for FM and LM travels with travel demands of 2 160 and 4 320 trips • h_1, as well as for LM travel with a travel demand of 6 480 trips • h_1, the maximum mean waiting time for travelers is 1. 06 min; the maximum mean detour time for travelers is 1. 11 min; the maximum mean matching time for travelers is 46. 09 s; the maximum vehicle distance saved for the operator is 877. 24 km • h_1; the maximum matching rate is 61.67%; and the maximum mean solution time for the system is 2. 09 s. These results demonstrate the efficiency and stability of the system and model. © 2024 Chang'an University. All rights reserved.
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页码：288 / 301
页数：13
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