Incentivized self-rebalancing fleet in electric vehicle sharing

Abstract

With the rising need for efficient and flexible short-distance urban transportation, more vehicle sharing companies are offering one-way car-sharing services. Electrified vehicle sharing systems are even more effective in terms of reducing fuel consumption and carbon emission. In this article, we investigate a dynamic fleet management problem for an Electric Vehicle (EV) sharing system that faces time-varying random demand and electricity price. Demand is elastic in each time period, reacting to the announced price. To maximize the revenue, the EV fleet optimizes trip pricing and EV dispatching decisions dynamically. We develop a new value function approximation with input convex neural networks to generate high-quality solutions. Through a New York City case study, we compare it with standard dynamic programming methods and develop insights regarding the interaction between the EV fleet and the power grid.

Keywords:

• Dynamic programming
• revenue management
• vehicle sharing
• electric vehicle
• value function approximation

Acknowledgments

The authors gratefully acknowledge the valuable comments from the editors and three anonymous reviewers that helped improve the paper.

Additional information

Funding

This research is supported by the U.S. National Science Foundation through Grants CNS# 1637772.

Notes on contributors

Yuguang Wu

Yuguang Wu is a PhD Candidate in the Department of Industrial and Systems Engineering, University of Wisconsin-Madison (UW-Madison). He obtained the MS degree in computer science at UW-Madison (2020) and a BS degree in mathematics and physics at Tsinghua University, China (2016).

Minmin Chen

Minmin Chen currently works for Amazon as a Software Engineer. She obtained an MS degree in industrial engineering at UW-Madison (2018) and a BM degree in engineering management at the University of Science and Technology Beijing, China (2017).

Xin Wang

Xin Wang received a PhD degree in Civil and Environmental Engineering from the University of Illinois at Urbana-Champaign (UIUC) in 2015. He also obtained an MS degree in applied math (2012) and civil and environmental engineering in UIUC (2014), a BS degree in automation engineering from Tsinghua University, China (2010). He is currently an assistant professor in the Department of Industrial and System Engineering, University of Wisconsin-Madison, and also affiliated with the Department of Civil and Environmental Engineering, Grainger Institute for Engineering.