On Re-Balancing Self-Interested Agents in Ride-Sourcing Transportation Networks

TL;DR

This paper investigates methods to influence self-interested ride-sourcing drivers' locations to reduce customer wait times, proposing two indirect control strategies and algorithms to optimize driver distribution.

Contribution

It introduces two novel indirect control methods for driver location management and provides algorithms for near-optimal solutions in ride-sourcing networks.

Findings

Achieved 20% to 80% reduction in expected wait times

Demonstrated effectiveness of control methods on real-world data

Showed NP-hardness of optimal control problem

Abstract

This paper focuses on the problem of controlling self-interested drivers in ride-sourcing applications. Each driver has the objective of maximizing its profit, while the ride-sourcing company focuses on customer experience by seeking to minimizing the expected wait time for pick-up. These objectives are not usually aligned, and the company has no direct control on the waiting locations of the drivers. In this paper, we provide two indirect control methods to optimize the set of waiting locations of the drivers, thereby minimizing the expected wait time of the customers: 1) sharing the location of all drivers with a subset of drivers, and 2) paying the drivers to relocate. We show that finding the optimal control for each method is NP-hard and we provide algorithms to find near-optimal control in each case. We evaluate the performance of the proposed control methods on real-world data and show that we can achieve between 20% to 80% improvement in the expected response.