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A Stochastic Optimal Control Approach to Real-time, Incident-Responsive Traffic Signal Control at Isolated Intersections

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  • Jiuh-Biing Sheu

    (Institute of Traffic and Transportation, National Chiao Tung University, 4F 114 Chung Hsiao W. Road, Sec. 1, Taipei 10012, Taiwan)

Abstract

Real-time, incident-responsive traffic control and management is vital to development of advanced incident management systems in ITS. More importantly, it provides, from an academic point of view, the linkages between incident detection, incident management, and traffic signal control. This study explores the application of a stochastic optimal control approach to real-time, incident-responsive traffic control at isolated intersections. In the methodology development, time-varying lane traffic state variables and control variables are specified to characterize sectionwide interlane and intralane traffic states under conditions of lane-blocking incidents. Following specification of system states, we formulated a discrete-time nonlinear stochastic model that comprises four types of equations, namely (1) recursive equations, (2) measurement equations, (3) incident-induced delay equations, and (4) boundary constraints. From the proposed stochastic model we then developed a stochastic optimal control algorithm to update the time-varying control variables and lane traffic state variables in real-time with lane-blocking incidents at isolated intersections. To generate traffic data used in model tests efficiently, we employed an advanced microscopic traffic simulator, Paramics, Version 3.0, which is developed to model and analyze ITS traffic flow conditions. The preliminary test results indicate that the proposed method can accomplish the goal of real-time, incident-responsive traffic signal control. In addition to proposing a new methodology, we hope that this study can initiate investigation into real-time, incident-responsive traffic control and management to achieve the final goal of networkwide incident-responsive, traffic-optimal control for incident management.

Suggested Citation

  • Jiuh-Biing Sheu, 2002. "A Stochastic Optimal Control Approach to Real-time, Incident-Responsive Traffic Signal Control at Isolated Intersections," Transportation Science, INFORMS, vol. 36(4), pages 418-434, November.
    • Handle: RePEc:inm:ortrsc:v:36:y:2002:i:4:p:418-434
    DOI: 10.1287/trsc.36.4.418.550
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    References listed on IDEAS

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    1. Sheu, Jiuh-Biing & Chou, Yi-Hwa & Shen, Liang-Jen, 2001. "A stochastic estimation approach to real-time prediction of incident effects on freeway traffic congestion," Transportation Research Part B: Methodological, Elsevier, vol. 35(6), pages 575-592, July.
    2. Abdulhai, Baher & Sheu, Jiuh-Biing & Recker, Will, 1999. "Simulation of ITS on the Irvine FOT Area Using "Paramics 1.5" Scalable Microscopic Traffic Simulator: Phase I: Model Calibration and Validation," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2ks86938, Institute of Transportation Studies, UC Berkeley.
    3. Jiuh-Biing Sheu, 2003. "A Stochastic Modeling Approach to Real-Time Prediction of Queue Overflows," Transportation Science, INFORMS, vol. 37(1), pages 97-119, February.
    4. Jiuh-Biing Sheu, 2003. "Erratum: A Stochastic Modeling Approach to Real-Time Prediction of Queue Overflows," Transportation Science, INFORMS, vol. 37(2), pages 230-252, May.
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    Cited by:

    1. Sheu, Jiuh-Biing, 2005. "A multi-layer demand-responsive logistics control methodology for alleviating the bullwhip effect of supply chains," European Journal of Operational Research, Elsevier, vol. 161(3), pages 797-811, March.
    2. Sheu, Jiuh-Biing & Yang, Hai, 2008. "An integrated toll and ramp control methodology for dynamic freeway congestion management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4327-4348.
    3. Sheu, Jiuh-Biing, 2007. "Microscopic modeling and control logic for incident-responsive automatic vehicle movements in single-automated-lane highway systems," European Journal of Operational Research, Elsevier, vol. 182(2), pages 640-662, October.
    4. Jiuh‐Biing Sheu & Tsan‐Ming Choi, 2023. "Can we work more safely and healthily with robot partners? A human‐friendly robot–human‐coordinated order fulfillment scheme," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 794-812, March.
    5. Simone Baldi & Iakovos Michailidis & Vasiliki Ntampasi & Elias Kosmatopoulos & Ioannis Papamichail & Markos Papageorgiou, 2019. "A Simulation-Based Traffic Signal Control for Congested Urban Traffic Networks," Service Science, INFORMS, vol. 53(1), pages 6-20, February.

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