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

Saeid Rasulkhani, Joseph Ying Jun Chow

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)60-81
Number of pages22
JournalTransportation Research Part B: Methodological
Volume124
DOIs
StatePublished - Jun 1 2019

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costs
pricing
Costs
market equilibrium
equilibrium model
transportation system
Group

Keywords

  • Assignment game
  • Mobility-as-a-service
  • Service network design
  • Stable matching
  • Transportation network assignment

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation

Cite this

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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.",
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