Eco-Mobility-on-Demand Fleet Control With Ride-Sharing

• Main Authors: Auld, J.A (Author), Huang, X. (Author), Li, B. (Author), Peng, H. (Author), Sokolov, V.O (Author)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Subjects: Automated vehicles; Connected automated vehicle; Cost reduction; data-driven model; Data-driven model; Energy conservation; Energy consumption and cost; Energy utilization; Energy-savings; Fleet control; Fleet operations; fuel consumption; Fuel consumption; Fuels; mobility-on-demand; Mobility-on-demand; On demands; Reduce energy consumption; ride-sharing; Ride-sharing; Travel time
• Online Access: View Fulltext in Publisher
• ISBN: 15249050 (ISSN)
• DOI: 10.1109/TITS.2020.3032473

Shared Mobility-on-Demand using automated vehicles can reduce energy consumption and cost for future mobility. However, its full potential in energy saving has not been fully explored. An algorithm to minimize fleet fuel consumption while satisfying customers' travel time constraints is developed in this article. Numerical simulations with realistic travel demand and route choice are performed, showing that if fuel consumption is not considered, the Mobility-on-demand (MOD) service can increase fleet fuel consumption due to increased empty vehicle mileage. With fuel consumption as part of the cost function, we can reduce total fuel consumption by 7% while maintaining a high level of mobility service. © 2000-2011 IEEE.