Capturing Travel Mode Adoption in Designing On-demand Multimodal Transit Systems

TL;DR

This paper introduces a bilevel optimization model for designing on-demand multimodal transit systems that effectively captures rider preferences and adoption, leading to improved accessibility and efficiency.

Contribution

It develops an exact decomposition method with computational enhancements for optimizing ODMTS design considering rider choice behavior.

Findings

High rider adoption rates achieved in case study

Significant reduction in trip durations compared to existing systems

Enhanced computational efficiency of the optimization method

Abstract

This paper studies how to integrate rider mode preferences into the design of On-Demand Multimodal Transit Systems (ODMTS). It is motivated by a common worry in transit agencies that an ODMTS may be poorly designed if the latent demand, i.e., new riders adopting the system, is not captured. The paper proposes a bilevel optimization model to address this challenge, in which the leader problem determines the ODMTS design, and the follower problems identify the most cost efficient and convenient route for riders under the chosen design. The leader model contains a choice model for every potential rider that determines whether the rider adopts the ODMTS given her proposed route. To solve the bilevel optimization model, the paper proposes an exact decomposition method that includes Benders optimal cuts and nogood cuts to ensure the consistency of the rider choices in the leader and follower problems. Moreover, to improve computational efficiency, the paper proposes upper bounds on trip durations for the follower problems and valid inequalities that strenghten the nogood cuts. The proposed method is validated using an extensive computational study on a real data set from AAATA, the transit agency for the broader Ann Arbor and Ypsilanti region in Michigan. The study considers the impact of a number of factors, including the price of on-demand shuttles, the number of hubs, and accessibility criteria. The designed ODMTS feature high adoption rates and significantly shorter trip durations compared to the existing transit system and highlight the benefits in accessibility for low-income riders. Finally, the computational study demonstrates the efficiency of the decomposition method for the case study and the benefits of computational enhancements that improve the baseline method by several orders of magnitude.