Economic and environmental benefits of automated electric vehicle ride-hailing services in New York City

Author:

Zeng Teng,Zhang Hongcai,Moura Scott J.,Shen Zuo-Jun M.

Abstract

AbstractA precise, scalable, and computationally efficient mathematical framework is proposed for region-wide autonomous electric vehicle (AEV) fleet management, sizing and infrastructure planning for urban ride-hailing services. A comprehensive techno-economic analysis in New York City is conducted not only to calculate the societal costs but also to quantify the environmental and health benefits resulting from reduced emissions. The results reveal that strategic fleet management can reduce fleet size and unnecessary cruising mileage by up to 40% and 70%, respectively. This alleviates traffic congestion, saves travel time, and further reduces fleet sizes. Besides, neither large-battery-size AEVs nor high-power charging infrastructure is necessary to achieve efficient service. This effectively alleviates financial and operational burdens on fleet operators and power systems. Moreover, the reduced travel time and emissions resulting from efficient fleet autonomy create an economic value that exceeds the total capital investment and operational costs of fleet services.

Funder

National Natural Science Foundation of China

Science and Technology Development Fund, Macau SAR

Publisher

Springer Science and Business Media LLC

Reference49 articles.

1. International Energy Agency. Global EV outlook 2023. https://www.iea.org/reports/global-ev-outlook-2023 (2023). (Accessed 1 May 2023).

2. Statista. Ride-hailing & taxi - worldwide. https://www.statista.com/outlook/mmo/shared-mobility/shared-rides/ride-hailing-taxi/worldwide (2023). (Accessed 26 July 2023).

3. Abhay, S. & Sonia, M. Autonomous vehicle market by level of automation (level 1, level 2, level 3, level 4, and level 5), application (civil, defense, transportation & logistics, and construction), drive type (semi-autonomous and fully autonomous), and vehicle type (passenger car and commercial vehicle): Global opportunity analysis and industry forecast, 2021–2030. https://www.alliedmarketresearch.com/autonomous-vehicle-market (2020). (Accessed 26 July 2023).

4. Bösch, P. M., Becker, F., Becker, H. & Axhausen, K. W. Cost-based analysis of autonomous mobility services. Transp. Policy 64, 76–91. https://doi.org/10.1016/j.tranpol.2017.09.005 (2018).

5. Greenblatt, J. B. & Saxena, S. Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles. Nat. Clim. Change 5, 860–863 (2015).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3