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Solving the first‐mile ridesharing problem using autonomous vehicles
Author(s) -
Chen Shukai,
Wang Hua,
Meng Qiang
Publication year - 2020
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12461
Subject(s) - computer science , mile , last mile (transportation) , integer programming , operator (biology) , transport engineering , linear programming , operations research , mathematical optimization , computation , vehicle routing problem , routing (electronic design automation) , computer network , engineering , algorithm , mathematics , biochemistry , chemistry , physics , repressor , astronomy , transcription factor , gene
Autonomous vehicles (AVs) are paving a way to reshape the operation and management of urban transportation systems by improving travel mobility. In this study, we propose to use AVs for solving the first‐mile (FM) problem that aims to transport passengers from their homes to metro stations. Passengers submit travel requests in advance and a fleet operator dispatches AVs and arranges ridesharing in a rolling horizon framework. The ridesharing is implemented by assigning one AV to serve several requests subject to the vehicle capacity, the maximum travel time, and the accessibility constraints. A mixed integer linear programming (MILP) model is formulated to determine the AV dispatch and ridesharing schemes for the minimum operational costs. Then, another MILP model with the objective of the maximum user satisfaction is formulated for the purpose of comparison. A cluster‐based solution method is designed to deal with the large‐scale FM problem. Extensive numerical experiments are conducted to demonstrate the application of the proposed method. Results show that ridesharing can reduce both required AV fleet size and vehicle traveled miles. The proposed solution method is able to solve the problem efficiently and fulfil the requirement of online computation.