A simulation‐based optimization model for infrastructure planning for electric autonomous vehicle sharing. (13th November 2019)

• Record Type: Journal Article
• Authors: Zhao, Dongfang; Li, Xiaopeng; Cui, Jianxun
• Other Names: Qu Xiaobo guestEditor.; van Arem Bart guestEditor.
• Is Part Of: Computer-aided civil and infrastructure engineering. Volume 36:Number 7(2021)
• Page Start: 858
• Page End: 876
• Publication Date: 2019-11-13
• Subjects: Civil engineering -- Data processing -- Periodicals; Computer-aided engineering -- Periodicals; 624.0285
• DOI: 10.1111/mice.12506
• Languages: English
• ISSNs: 1093-9687

Abstract

Abstract: New transportation technologies (e.g., electric autonomous vehicles [EAVs]) and operation paradigms (e.g., car sharing) are discussed, researched, and to a small degree also deployed in recent years in response to rising energy crises and aggravating traffic congestions. In this research, we present a station‐based car‐sharing service system that integrates both EAV technologies and car‐sharing operations. Based on the simulation model, a dynamic and time‐continuous optimization model seeking a near‐optimum design of charging station location and EAV deployment is developed. By discretizing the model, we proposed a Monte Carlo simulation model to evaluate the total system cost for a given location and vehicle deployment design. A heuristic approach based on the genetic algorithm is developed to solve the system design of station location and vehicle deployment. A numerical test in Yantai City, China, is conducted to illustrate the effectiveness of the proposed model and to draw managerial insights into how the key parameters affect the system design.