Design of Transit-Centric Multimodal Urban Mobility System with Autonomous Mobility-on-Demand

TL;DR

This paper presents a novel optimization framework for designing and managing a multimodal urban mobility system that integrates public transit and autonomous mobility-on-demand, aiming to minimize passenger disutility in growing cities.

Contribution

It introduces the first joint optimization model for transit network design, fleet sizing, and pricing that incorporates passenger mode and route choices in an urban setting.

Findings

Optimized transit and AMoD system in Chicago case study

Demonstrated potential for improved urban mobility across demand scenarios

First to jointly optimize transit design, fleet, and pricing with passenger choices

Abstract

This paper addresses the pressing challenge of urban mobility in the context of growing urban populations, changing demand patterns for urban mobility, and emerging technologies like Mobility-on-Demand (MoD) platforms and Autonomous Vehicle (AV). As urban areas swell and demand pattern changes, the integration of Autonomous Mobility-on-Demand (AMoD) systems with existing public transit (PT) networks presents great opportunities to enhancing urban mobility. We propose a novel optimization framework for solving the Transit-Centric Multimodal Urban Mobility with Autonomous Mobility-on-Demand (TCMUM-AMoD) at scale. The system operator (public transit agency) determines the network design and frequency settings of the PT network, fleet sizing and allocations of AMoD system, and the pricing for using the multimodal system with the goal of minimizing passenger disutility. Passengers' mode and route choice behaviors are modeled explicitly using discrete choice models. A first-order approximation algorithm is introduced to solve the problem at scale. Using a case study in Chicago, we showcase the potential to optimize urban mobility across different demand scenarios. To our knowledge, ours is the first paper to jointly optimize transit network design, fleet sizing, and pricing for the multimodal mobility system while considering passengers' mode and route choices.