It's All in the Mix: Technology Choice between Driverless and Human-Driven Vehicles in Sharing Systems

28 Pages Posted: 22 Aug 2022 Last revised: 30 Jan 2024

See all articles by Layla Martin

Layla Martin

Eindhoven University of Technology (TUE) - Department of Industrial Engineering and Innovation Sciences

Stefan Minner

Technische Universität München (TUM) - TUM School of Management

Marco Pavone

Stanford University

Maximilian Schiffer

Technische Universität München (TUM)

Date Written: May 2, 2021

Abstract

Operators of vehicle-sharing systems such as carsharing or ride-hailing can benefit from integrating driverless vehicles into their fleet. In this context, we study the impact of optimal fleet size and composition on an operator's profitability, which entails a non-trivial tradeoff between operational benefits and higher upfront investment for driverless vehicles.

We analyze a strategic fleet sizing and composition problem, integrating a rebalancing problem, which we formalize as a Markov decision process. We incorporate the rebalancing problem with a time-dependent fluid approximation to devise a scalable linear programming solution approach, which we improve by state-dependent emergency rebalancing.

We present a numerical study on artificial and real-world instances that reveals significant profit improvement potential of driverless and mixed fleets compared to human-driven fleets. For real-world instances, the profit improvement amounts up to 20.4% over exclusively human-driven fleets. If both vehicle types incur equal operational costs, operators optimally mix a small number of driverless vehicles with a large number of human-driven vehicles. Mixed fleets are particularly beneficial if demand varies over time, and operators consequently shift rebalancing to lower-demand periods.

Keywords: driverless vehicles, fleet sizing and composition, Markov decision process

JEL Classification: C44

Suggested Citation

Martin, Layla and Minner, Stefan and Pavone, Marco and Schiffer, Maximilian, It's All in the Mix: Technology Choice between Driverless and Human-Driven Vehicles in Sharing Systems (May 2, 2021). Available at SSRN: https://ssrn.com/abstract=4190991 or http://dx.doi.org/10.2139/ssrn.4190991

Layla Martin (Contact Author)

Eindhoven University of Technology (TUE) - Department of Industrial Engineering and Innovation Sciences ( email )

Den Dolech 2
Eindhoven
Netherlands

Stefan Minner

Technische Universität München (TUM) - TUM School of Management ( email )

Arcisstrasse 21
München, 80333
Germany

HOME PAGE: http://www.log.wi.tum.de

Marco Pavone

Stanford University ( email )

Stanford, CA 94305
United States

Maximilian Schiffer

Technische Universität München (TUM) ( email )

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
57
Abstract Views
426
Rank
659,215
PlumX Metrics