Eco-Mobility-on-Demand Fleet Control with Ride-Sharing

TL;DR

This paper presents an algorithm for fleet control in shared mobility-on-demand with ride-sharing, aiming to minimize fuel consumption while maintaining service quality, demonstrating a 7% reduction in fuel use through simulations.

Contribution

The paper introduces a novel fleet control algorithm that incorporates fuel consumption into the optimization, enhancing energy efficiency in mobility-on-demand services.

Findings

Fuel-aware control reduces total fuel consumption by 7%.

Ignoring fuel costs can lead to increased empty vehicle mileage.

The algorithm maintains high mobility service levels.

Abstract

Shared Mobility-on-Demand using automated vehicles can reduce energy consumption and cost for future mobility. However, its full potential in energy saving has not been fully explored. An algorithm to minimize fleet fuel consumption while satisfying customers travel time constraints is developed in this paper. Numerical simulations with realistic travel demand and route choice are performed, showing that if fuel consumption is not considered, the MOD service can increase fleet fuel consumption due to increased empty vehicle mileage. With fuel consumption as part of the cost function, we can reduce total fuel consumption by 7 percent while maintaining a high level of mobility service.