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Utility optimization framework for a distributed traffic control of urban road networks

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Listed:
  • Le, Tung
  • Vu, Hai L.
  • Walton, Neil
  • Hoogendoorn, Serge P.
  • Kovács, Péter
  • Queija, Rudesindo N.

Abstract

Route choice behavior has been recognized as an important factor in the traffic management and control strategy design. State-of-the-art research in this field (e.g. anticipatory traffic control approaches) often formulates this as a bi-level optimization problem where users’ reactions to changes in signal control are taken into account in the design of the control policies. Solving such a combined optimization problem is possible but difficult and complex which often involves the determination of the dynamic user equilibrium (UE). Nevertheless, anticipatory control inherently aims to optimize the signal control that anticipates or reacts to the users’ route choice and thus is a reactive control. Furthermore, the approaches used in anticipatory control are based on the coupling between control and traffic assignment where the route choice behavior of road users is unrealistically assumed to be in equilibrium.

Suggested Citation

  • Le, Tung & Vu, Hai L. & Walton, Neil & Hoogendoorn, Serge P. & Kovács, Péter & Queija, Rudesindo N., 2017. "Utility optimization framework for a distributed traffic control of urban road networks," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 539-558.
    • Handle: RePEc:eee:transb:v:105:y:2017:i:c:p:539-558
    DOI: 10.1016/j.trb.2017.10.004
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    References listed on IDEAS

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    Cited by:

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    3. Vinayak Dixit & Divya Jayakumar Nair & Sai Chand & Michael W Levin, 2020. "A simple crowdsourced delay-based traffic signal control," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-12, April.
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    6. Vandana Singh & Sudip Kumar Sahana & Vandana Bhattacharjee, 2022. "Nature-Inspired Cloud–Crowd Computing for Intelligent Transportation System," Sustainability, MDPI, vol. 14(23), pages 1-13, December.

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