Route-cost-assignment with joint user and operator behavior as a many-to-one stable matching assignment game

TL;DR

This paper introduces a generalized market equilibrium model for transportation systems that finds stable pricing and matching between users and operators, allowing for flexible policy design and outcome analysis.

Contribution

The paper presents a convex, assignment game-based model that generates a set of stable outcomes for transportation planning, incorporating joint user and operator behaviors.

Findings

Model produces convex sets of stable outcomes.

Case study demonstrates policy evaluation for shared taxis in NYC.

Unique user- and operator-optimal solutions can be derived.

Abstract

We propose a generalized market equilibrium model using assignment game criteria for evaluating transportation systems that consist of both operators' and users' decisions. The model finds stable pricing, in terms of generalized costs, and matches between user populations in a network to set of routes with line capacities. The proposed model gives a set of stable outcomes instead of single point pricing that allows operators to design ticket pricing, routes/schedules that impact access/egress, shared policies that impact wait/transfer costs, etc., based on a desired mechanism or policy. The set of stable outcomes is proven to be convex from which assignment-dependent unique user-optimal and operator-optimal outcomes can be obtained. Different user groups can benefit from using this model in a prescriptive manner or within a sequential design process. We look at several different examples to test our model: small examples of fixed transit routes and a case study using a small subset of taxi data in NYC. The case study illustrates how one can use the model to evaluate a policy that can require passengers to walk up to 1 block away to meet with a shared taxi without turning away passengers.