Real Time Operation of High-Capacity Electric Vehicle Ridesharing Fleets

TL;DR

This paper explores the real-time management of large electric vehicle ride-sharing fleets, proposing algorithms for efficient scheduling and charging to ensure service availability in high-capacity, online systems.

Contribution

It introduces a mixed integer linear program and a scalable algorithm for electric vehicle fleet management, emphasizing the importance of demand forecasting in online ridepooling.

Findings

Proposed algorithms effectively schedule charging and vehicle deployment.

Scalable algorithm performs comparably to more complex models.

Demand estimation improves fleet availability in real-time operations.

Abstract

We study the feasibility of using electric vehicles in online, high-capacity ridepooling systems. Prior work has shown that online algorithms perform well for centrally-controlled, high-capacity ridepool systems. First, we propose a mixed integer linear program to expand past algorithms on ridepooling to electric vehicles fleets with the objective of scheduling vehicle charging to maintain sufficient fleet sizes at various times of day. Then we show a faster, scalable algorithm with similar performance that is practical for full-scale systems. Our contributions show the importance of having knowledge and estimates of future demand even when operating in the online setting.