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Information-based network control strategies consistent with estimated driver behavior

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  • Paz, Alexander
  • Peeta, Srinivas

Abstract

This study proposes a fuzzy control based methodology to determine information-based network control strategies that are consistent with the controller's objectives and its estimation of driver response behavior. It is the core of the broader problem where the objective is to enhance the performance of a vehicular traffic system through real-time information-based network control strategies. The controller seeks behavior consistency by solving a fixed-point problem that estimates drivers' likely reactions to the controller-proposed information strategies while determining them. Experiments are performed to evaluate the effectiveness of the proposed methodology. The results suggest the importance of using a behavior-consistent approach to determine the information-based network control strategies. That is, the effects of driver response behavior to information provision may require more meaningful strategies than those provided under the traditional dynamic traffic assignment models to reliably estimate or control system performance. Information strategies that are not behavior-consistent can potentially deteriorate system performance.

Suggested Citation

  • Paz, Alexander & Peeta, Srinivas, 2009. "Information-based network control strategies consistent with estimated driver behavior," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 73-96, January.
    • Handle: RePEc:eee:transb:v:43:y:2009:i:1:p:73-96
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    References listed on IDEAS

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    1. Shlomo Bekhor & Moshe Ben-Akiva & M. Ramming, 2006. "Evaluation of choice set generation algorithms for route choice models," Annals of Operations Research, Springer, vol. 144(1), pages 235-247, April.
    2. Yannis Pavlis & Markos Papageorgiou, 1999. "Simple Decentralized Feedback Strategies for Route Guidance in Traffic Networks," Transportation Science, INFORMS, vol. 33(3), pages 264-278, August.
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    Cited by:

    1. Lianzhen Wang & Han Zhang & Lingyun Shi & Qingling He & Huizhi Xu, 2021. "Optimization Model of Regional Traffic Signs for Inducement at Road Works," Sustainability, MDPI, vol. 13(13), pages 1-14, June.
    2. Sheu, Jiuh-Biing & Wu, Hsi-Jen, 2015. "Driver perception uncertainty in perceived relative speed and reaction time in car following – A quantum optical flow perspective," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 257-274.
    3. Yu-Ting Hsu & Srinivas Peeta, 2013. "An aggregate approach to model evacuee behavior for no-notice evacuation operations," Transportation, Springer, vol. 40(3), pages 671-696, May.
    4. Assemi, Behrang & Baker, Douglas & Paz, Alexander, 2020. "Searching for on-street parking: An empirical investigation of the factors influencing cruise time," Transport Policy, Elsevier, vol. 97(C), pages 186-196.
    5. Paz, Alexander & Peeta, Srinivas, 2009. "On-line calibration of behavior parameters for behavior-consistent route guidance," Transportation Research Part B: Methodological, Elsevier, vol. 43(4), pages 403-421, May.

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