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Multiple equilibrium behaviors and advanced traveler information systems with endogenous market penetration

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  • Yang, Hai
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Abstract

We consider a specific advanced traveler information system (ATIS) whose objective is to reduce drivers' time uncertainty with recurrent network congestion through provision of traffic information to drivers. Suppose drivers equipped with an ATIS will receive complete information and hence be able to find the minimum travel time routes in a user-optimal manner, while drivers not equipped with an ATIS will have only incomplete information and hence may take longer travel time routes in a stochastic manner. We propose a convex programming model and an algorithm to solve this mixed behavior equilibrium problem for any given level of the market penetration of ATIS. Furthermore, suppose that the information benefit received by a driver who buys an ATIS is measured as the travel time saving (stochastic mean travel time minus deterministic minimum travel time in a mixed behavior equilibrium over a common network), and the market penetration of ATIS is determined by a continuous increasing function of the information benefit, then we have a variable, mixed behavior equilibrium model with endogenous market penetration in an ATIS environment. We establish the existence, uniqueness and stability of this performance and demand equilibrium of ATIS, and propose an iterative procedure to calculate the ATIS market penetration and the resulting equilibrium network flow pattern.

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Bibliographic Info

Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

Volume (Year): 32 (1998)
Issue (Month): 3 (April)
Pages: 205-218

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Handle: RePEc:eee:transb:v:32:y:1998:i:3:p:205-218

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  1. Bennett, Lloyd D., 1993. "The existence of equivalent mathematical programs for certain mixed equilibrium traffic assignment problems," European Journal of Operational Research, Elsevier, vol. 71(2), pages 177-187, December.
  2. Mingyuan Chen & Attahiru Sule Alfa, 1991. "Algorithms for solving fisk's stochastic traffic assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 25(6), pages 405-412, December.
  3. Yang, Reddy H & Vaughn, K M & Abdel-Aty, M A & Kitamura, R & Jovanis, P P, 1995. "Design of an Artificial Simulator for Analyzing Route Choice Behavior in the Presence of Information System," Institute of Transportation Studies, Working Paper Series qt93x4h7pp, Institute of Transportation Studies, UC Davis.
  4. Kanafani, A. & Al-Deek, H., 1991. "A simple model for route guidance benefits," Transportation Research Part B: Methodological, Elsevier, vol. 25(4), pages 191-201, August.
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Cited by:
  1. Lo, Hong K. & Szeto, W. Y., 2004. "Modeling advanced traveler information services: static versus dynamic paradigms," Transportation Research Part B: Methodological, Elsevier, vol. 38(6), pages 495-515, July.
  2. Yin, Yafeng & Yang, Hai, 2003. "Simultaneous determination of the equilibrium market penetration and compliance rate of advanced traveler information systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(2), pages 165-181, February.
  3. Yamada, Tadashi & Imai, Koji & Nakamura, Takamasa & Taniguchi, Eiichi, 2011. "A supply chain-transport supernetwork equilibrium model with the behaviour of freight carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 887-907.
  4. Lam, William H. K. & Zhou, Jing & Sheng, Zhao-han, 2002. "A capacity restraint transit assignment with elastic line frequency," Transportation Research Part B: Methodological, Elsevier, vol. 36(10), pages 919-938, December.
  5. Yang, Hai & Meng, Qiang, 2001. "Modeling user adoption of advanced traveler information systems: dynamic evolution and stationary equilibrium," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(10), pages 895-912, December.
  6. Zhang, Rong & Verhoef, Erik T., 2006. "A monopolistic market for advanced traveller information systems and road use efficiency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(5), pages 424-443, June.
  7. Arthur Huang & David Levinson, 2009. "Modeling phase changes of road networks," Working Papers 000061, University of Minnesota: Nexus Research Group.
  8. Lo, Hong K. & Szeto, W. Y., 2002. "A methodology for sustainable traveler information services," Transportation Research Part B: Methodological, Elsevier, vol. 36(2), pages 113-130, February.
  9. Lei Zhang & David Levinson, 2006. "Determinants of Route Choice and the Value of Traveler Information," Working Papers 200808, University of Minnesota: Nexus Research Group.
  10. André De Palma & Robin Lindsey & Nathalie Picard, 2008. "Risk aversion, the value of information and traffic equilibrium," Working Papers hal-00349492, HAL.
  11. Enrique Fernández L., J. & de Cea Ch, Joaquín & Germán Valverde, G., 2009. "Effect of advanced traveler information systems and road pricing in a network with non-recurrent congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(5), pages 481-499, June.
  12. Hai-Jun Huang & Tian-Liang Liu & Xiaolei Guo & Hai Yang, 2011. "Inefficiency of Logit-Based Stochastic User Equilibrium in a Traffic Network Under ATIS," Networks and Spatial Economics, Springer, vol. 11(2), pages 255-269, June.
  13. Hai Yang, 1999. "Evaluating the benefits of a combined route guidance and road pricing system in a traffic network with recurrent congestion," Transportation, Springer, vol. 26(3), pages 299-322, August.
  14. Huang, Hai-Jun & Li, Zhi-Chun, 2007. "A multiclass, multicriteria logit-based traffic equilibrium assignment model under ATIS," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1464-1477, February.
  15. Yang, Hai & Zhang, Xiaoning & Meng, Qiang, 2007. "Stackelberg games and multiple equilibrium behaviors on networks," Transportation Research Part B: Methodological, Elsevier, vol. 41(8), pages 841-861, October.

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