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Modeling advanced traveler information services: static versus dynamic paradigms

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  • Lo, Hong K.
  • Szeto, W. Y.

Abstract

This paper develops a cell-based variational inequality formulation of the dynamic traffic assignment (DTA) problem to evaluate the impact of advanced traveler information systems (ATIS) services. It considers two classes of drivers: those with ATIS and those without. Both classes are modeled to follow the stochastic dynamic user optimal conditions, with the equipped drivers having a lower perception variation of the network travel time due to the availability of better information. The model represents traffic dynamics according to the cell-transmission model, including such physical effects as queue spillback, shockwaves, etc. One objective of this study is to compare and contrast the static versus the dynamic modeling paradigms for this problem. The numerical study indicates that some aspects of the results from these two paradigms could be diametrical. The discrepancy is mainly attributed to the fundamental characteristic of a model--how traffic is represented. It appears that simplifications from the physical queue representation are inadequate in producing correct results, especially for already congested networks wherein junction blockage is common.

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  • 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.
    • Handle: RePEc:eee:transb:v:38:y:2004:i:6:p:495-515
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    References listed on IDEAS

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    2. Qixiu Cheng & Zhiyuan Liu & Feifei Liu & Ruo Jia, 2017. "Urban dynamic congestion pricing: an overview and emerging research needs," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 21(0), pages 3-18, August.
    3. W. Szeto & Y. Jiang & D. Wang & A. Sumalee, 2015. "A Sustainable Road Network Design Problem with Land Use Transportation Interaction over Time," Networks and Spatial Economics, Springer, vol. 15(3), pages 791-822, September.
    4. Lei Zhang & David Levinson, 2006. "Determinants of Route Choice and the Value of Traveler Information," Working Papers 200808, University of Minnesota: Nexus Research Group.
    5. Yu, Xiaojuan & van den Berg, Vincent A.C. & Li, Zhi-Chun, 2023. "Congestion pricing and information provision under uncertainty: Responsive versus habitual pricing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
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    7. 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.
    8. Luan, Jianlin & Polak, John & Krishnan, Rajesh, 2019. "The structure of public-private sector collaboration in travel information markets: A game theoretic analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 19-38.
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    10. Bifulco, Gennaro N. & Cantarella, Giulio E. & Simonelli, Fulvio & Velonà, Pietro, 2016. "Advanced traveller information systems under recurrent traffic conditions: Network equilibrium and stability," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 73-87.
    11. Qi Zhong & Lixin Miao, 2024. "Reliability-Based Mixed Traffic Equilibrium Problem Under Endogenous Market Penetration of Connected Autonomous Vehicles and Uncertainty in Supply," Networks and Spatial Economics, Springer, vol. 24(2), pages 461-505, June.
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