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Network Equilibrium under Cumulative Prospect Theory and Endogenous Stochastic Demand and Supply

  • Agachai Sumalee
  • Richard D. Connors
  • Paramet Luathep
Chapter

Abstract

In this paper we consider a network whose travel demands and road capacities are endogenously considered to be random variables. With stochastic demand and supply the route travel times are also random variables. In this scenario travelers choose their routes under travel time uncertainties. Several evidences suggest that the decision making process under uncertainty is significantly different from that without uncertainty. Therefore, the paper applies the decision framework of cumulative prospect theory (CPT) to capture this difference. We first formulate a stochastic network model whose travel demands and link capacities follow lognormal distributions. The stochastic travel times can then be derived under a given route choice modeling framework. For the route choice, we consider a modeling framework where the perceived value and perceived probabilities of travel time outcomes are obtained via transformations following CPT. We then formulate an equilibrium condition similar to that of User Equilibrium in which travelers choose the routes that maximizes their perceived utility values in the face of transformed stochastic travel times. Conditions are established guaranteeing existence (but not uniqueness) of this equilibrium. The paper then proposes a solution algorithm for the proposed model which is then tested with a test network.

Keywords

Route Choice Network Equilibrium Transportation Research Part Cumulative Prospect Theory Probability Weighting Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgments

This research was partially supported by a grant from the Research Committee of the Hong Kong Polytechnic University (Project No. A-PH65) and a General Research Fund from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project No. PolyU 5271/08E).

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Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  • Agachai Sumalee
    • 1
  • Richard D. Connors
    • 2
  • Paramet Luathep
    • 3
  1. 1.The Hong Kong Polytechnic UniversityHong KongChina
  2. 2.University of LeedsBritainU.K
  3. 3.The Hong Kong Polytechnic UniversityHong KongChina

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