[Paper Review] On the Interaction between Autonomous Mobility-on-Demand and Public Transportation Systems

Mauro Salazar, Federico Rossi+3 more|arXiv (Cornell University)|Apr 30, 2018

Transportation and Mobility Innovations4 citations

TL;DR

This paper proposes a network flow model for intermodal Autonomous Mobility-on-Demand (I-AMoD) systems that coordinates self-driving vehicles with public transit to maximize social welfare. By integrating pricing and tolling mechanisms, the model steers selfish agents toward the social optimum, reducing travel time, emissions, and costs—especially under congestion, as shown in a New York City case study where I-AMoD cut emissions by nearly 30% and tolls by 200% compared to isolated AMoD systems.

ABSTRACT

In this paper we study models and coordination policies for intermodal Autonomous Mobility-on-Demand (AMoD), wherein a fleet of self-driving vehicles provides on-demand mobility jointly with public transit. Specifically, we first present a network flow model for intermodal AMoD, where we capture the coupling between AMoD and public transit and the goal is to maximize social welfare. Second, leveraging such a model, we design a pricing and tolling scheme that allows to achieve the social optimum under the assumption of a perfect market with selfish agents. Finally, we present a real-world case study for New York City. Our results show that the coordination between AMoD fleets and public transit can yield significant benefits compared to an AMoD system operating in isolation.

Motivation & Objective

• To model the interaction between autonomous mobility-on-demand (AMoD) fleets and public transportation systems to improve urban mobility efficiency.
• To design a pricing and tolling scheme that aligns individual agent behavior with the social optimum in a perfect market.
• To quantify the benefits of intermodal coordination in reducing travel time, emissions, and operational costs compared to isolated AMoD systems.
• To evaluate the performance of the I-AMoD model in a real-world urban setting using New York City as a case study.

Proposed method

• Formulates a multi-commodity network flow model that captures the coupling between AMoD vehicles, public transit, and pedestrian networks in a digraph-based urban infrastructure.
• Introduces a pricing and tolling mechanism that internalizes externalities and incentivizes agents to adopt socially optimal routes.
• Uses a variational inequality formulation to prove that the proposed pricing scheme achieves the social optimum under selfish agent behavior.
• Applies the model to a real-world case study of Manhattan, using actual transit and road network data to simulate performance under varying congestion levels.
• Computes optimal tolls and route assignments using a mixed-integer linear programming formulation to minimize total system cost.
• Compares the I-AMoD system with an isolated AMoD system by setting public transit capacity to zero, isolating the impact of intermodal coordination.

Experimental results

Research questions

• RQ1 How can AMoD fleets be optimally coordinated with public transit to maximize social welfare in urban environments?
• RQ2 What pricing and tolling mechanisms can steer selfish agents toward the system-wide social optimum in intermodal mobility systems?
• RQ3 What are the quantitative benefits of intermodal coordination in terms of travel time, emissions, and cost reduction under congestion?
• RQ4 How do optimal tolls in the I-AMoD system compare to those in an isolated AMoD system, especially under high road usage?
• RQ5 To what extent does intermodal coordination reduce vehicle miles traveled and emissions compared to standalone AMoD operations?

Key findings

• The I-AMoD system reduces average travel time by over 40% compared to isolated AMoD under high congestion, due to efficient routing and mode-sharing.
• CO2 emissions are reduced by nearly 30% in the I-AMoD system compared to isolated AMoD when road capacity is constrained.
• Optimal road tolls in the I-AMoD system are approximately 200% lower than in the isolated AMoD system, with an average surcharge of nearly 6 USD per trip in the latter.
• The I-AMoD system achieves a 40% or greater reduction in monetary costs and travel time under high road usage, demonstrating strong synergy between AMoD and public transit.
• The pricing scheme successfully induces selfish agents to adopt socially optimal routes, proving the theoretical convergence to the social optimum under perfect market assumptions.
• Even under full road saturation, the I-AMoD system maintains feasibility and efficiency through pedestrian and transit mode usage, unlike isolated AMoD which fails to serve all requests.