A framework for integrated dispatching and charging management of an autonomous electric vehicle ride-hailing fleet

Yi, Zonggen; Smart, John G.

doi:10.1016/j.trd.2021.102822

Title: A framework for integrated dispatching and charging management of an autonomous electric vehicle ride-hailing fleet

Journal Article · Wed Apr 28 00:00:00 EDT 2021 · Transportation Research. Part D, Transport and Environment

DOI:https://doi.org/10.1016/j.trd.2021.102822· OSTI ID:1779826

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Idaho National Lab. (INL), Idaho Falls, ID (United States)

The convergence of electrification and automated driving will introduce opportunities to improve the operation and energy-efficiency of transportation systems. This paper discusses the challenges of dispatching autonomous electric vehicles (AEVs) in a ride-hailing fleet and their interactions with charging infrastructure. An integrated decision-making framework for dispatching and charging has been proposed using system optimization approaches. An agent-based platform has been developed for simulating and testing the proposed methods. A case study using New York City taxi data has been performed with different fleet sizes, dispatching strategies, and charging networks. Advantages of optimization-based approaches for AEV fleet management have been studied and demonstrated, for example, for a fleet of 1,750 AEVs to meet 100,000 daily requests, optimization-based centralized fleet management would result in 14% more ride requests satisfied and 43% fewer zero-occupancy miles traveled than if AEVs make independent decisions based on heuristic strategy. Benefits on reducing fleet size and charging downtime from optimization approaches are also comprehensively illustrated.

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Research Organization:: Idaho National Laboratory (INL), Idaho Falls, ID (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC07-05ID14517

OSTI ID:: 1779826

Alternate ID(s):: OSTI ID: 1780513

Report Number(s):: INL/JOU-19-56960-Rev000; TRN: US2209704

Journal Information:: Transportation Research. Part D, Transport and Environment, Vol. 95; ISSN 1361-9209

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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