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A platform for research: civil engineering, architecture and urbanism
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.
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.
A simulation‐based optimization model for infrastructure planning for electric autonomous vehicle sharing
Zhao, Dongfang (author) / Li, Xiaopeng (author) / Cui, Jianxun (author)
Computer‐Aided Civil and Infrastructure Engineering ; 36 ; 858-876
2021-07-01
19 pages
Article (Journal)
Electronic Resource
English
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