Adoption of autonomous and electric vehicles in private and shared mobility systems

被引:24
作者
Singh, Harprinderjot [1 ]
Kavianipour, Mohammadreza [1 ]
Ghamami, Mehrnaz [1 ]
Zockaie, Ali [1 ]
机构
[1] Michigan State Univ, 428 S Shaw Lane, E Lansing, MI 48824 USA
关键词
Autonomous Vehicles; Electric Vehicles; Shared Mobility System; Metaheuristic Algorithms; Fleet Optimization; High -Performance Computing; CHARGING INFRASTRUCTURE; AUTOMATED VEHICLES; OPERATIONS; IMPACTS; DEMAND; MODEL;
D O I
10.1016/j.trd.2022.103561
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Autonomous vehicles (AVs) and electric vehicles (EVs) will trigger disruptive changes to trans-portation systems via efficient driving, efficient use of travel time, reduced emissions and improved safety, mobility, roadway capacity, etc. However, these technologies might increase vehicle miles traveled (VMT), travel times, and ownership costs. Shared mobility systems can alleviate the high price of these technologies, but they will result in users' waiting time, incon-venience, and increased VMT. This study captures a variety of trade-offs in developing a fleet optimization multiclass user (with different value of travel time (VOTT)) problem considering AVs and EVs in both private and shared mobility systems. Two metaheuristic algorithms are developed and compared to solve the computationally complex large-scale non-linear optimiza-tion problem defined in this study. The case study (Ann Arbor, Michigan) results are sensitive to trip lengths, VOTT, emissions and travel time savings (in AVs). The proposed framework provide valuable insights for planning of emerging technologies.
引用
收藏
页数:26
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