A simulation-based optimization model for infrastructure planning for electric autonomous vehicle sharing

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.