Optimal Vehicle Scheduling and Charging Infrastructure Planning for Autonomous Modular Transit System

Ande Chang (), Yuan Cong, Chunguang Wang () and Yiming Bie
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Ande Chang: College of Forensic Sciences, Criminal Investigation Police University of China, Shenyang 110035, China
Yuan Cong: School of Transportation, Jilin University, Changchun 130022, China
Chunguang Wang: State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Yiming Bie: School of Transportation, Jilin University, Changchun 130022, China

Sustainability, 2024, vol. 16, issue 8, 1-16

Abstract: Prioritizing the development of public transport is an effective way to improve the sustainability of the transport system. In recent years, bus passenger flow has been declining in many cities. How to reform the operating mode of the public transportation system is an important issue that needs to be solved. An autonomous modular bus (AMB) is capable of physical coupling and uncoupling to flexibly adjust vehicle capacity as well as provide high-quality service under unbalanced passenger demand conditions. To promote AMB adoption and reduce the operating cost of the bus route, this paper presents a joint optimization method to simultaneously determine the AMB dispatching plan, charging plan, and charging infrastructure configuration scheme. Then, a mixed-integer programming model is formulated to minimize the operating costs of the bus route. A hybrid intelligent algorithm combining enumeration, cloning algorithm, and particle swarm optimization algorithm is designed to resolve the formulated model. Subsequently, an actual bus route is taken as an example to validate the proposed method. Results indicate that the developed method in this paper can reduce the operating costs and operational energy consumption of the route compared with the real route operating plan. Specifically, the reduction ratio of the former is 23.85%, and the reduction ratio of the latter is 5.92%. The results of this study validate the feasibility and advantages of autonomous modular transit service, contributing positively to the sustainable development of the urban public transportation system.

Keywords: autonomous modular bus; vehicle scheduling; charging infrastructure configuration; collaborative optimization; public transportation sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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