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Models and algorithms for the optimization of signal settings on urban networks with stochastic assignment models

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  • Ennio Cascetta
  • Mariano Gallo
  • Bruno Montella

Abstract

In this paper models and algorithms for the optimization of signal settings on urban networks are proposed. Two different approaches to the solution of the problem may be identified: a global approach (optimization of intersection signal settings on the whole network) and a local approach (optimization of signal settings intersection by intersection). For each approach a different optimization model and some solution algorithms are proposed; both models and algorithms are based on the assumptions of within-day static system and stochastic user equilibrium assignment models. The paper includes numerical results on test networks and a comparison between the two approaches. Copyright Springer Science+Business Media, LLC 2006

Suggested Citation

  • Ennio Cascetta & Mariano Gallo & Bruno Montella, 2006. "Models and algorithms for the optimization of signal settings on urban networks with stochastic assignment models," Annals of Operations Research, Springer, vol. 144(1), pages 301-328, April.
    • Handle: RePEc:spr:annopr:v:144:y:2006:i:1:p:301-328:10.1007/s10479-006-0008-9
    DOI: 10.1007/s10479-006-0008-9
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    3. Gallo, Mariano & D'Acierno, Luca & Montella, Bruno, 2010. "A meta-heuristic approach for solving the Urban Network Design Problem," European Journal of Operational Research, Elsevier, vol. 201(1), pages 144-157, February.
    4. Farahani, Reza Zanjirani & Miandoabchi, Elnaz & Szeto, W.Y. & Rashidi, Hannaneh, 2013. "A review of urban transportation network design problems," European Journal of Operational Research, Elsevier, vol. 229(2), pages 281-302.
    5. Castillo González, Rodrigo & Clempner, Julio B. & Poznyak, Alexander S., 2019. "Solving traffic queues at controlled-signalized intersections in continuous-time Markov games," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 166(C), pages 283-297.
    6. Smith, M.J. & Liu, R. & Mounce, R., 2015. "Traffic control and route choice: Capacity maximisation and stability," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 863-885.
    7. Yu, Chunhui & Ma, Wanjing & Han, Ke & Yang, Xiaoguang, 2017. "Optimization of vehicle and pedestrian signals at isolated intersections," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 135-153.
    8. Li, Tongfei & Cao, Yaning & Xu, Min & Sun, Huijun, 2023. "Optimal intersection design and signal setting in a transportation network with mixed HVs and CAVs," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    9. Fusco, G. & Bielli, M. & Cipriani, E. & Gori, S. & Nigro, M., 2013. "Signal settings synchronization and dynamic traffic modelling," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 53, pages 1-7.
    10. Wei Huang & Yang Hu & Xuanyu Zhang, 2022. "Enhancing Model-Based Anticipatory Traffic Signal Control with Metamodeling and Adaptive Optimization," Mathematics, MDPI, vol. 10(15), pages 1-18, July.
    11. Sujeet Kumar Singh & Shiv Prasad Yadav, 2018. "Intuitionistic fuzzy multi-objective linear programming problem with various membership functions," Annals of Operations Research, Springer, vol. 269(1), pages 693-707, October.
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    13. Sujeet Kumar Singh & Shiv Prasad Yadav, 2016. "A new approach for solving intuitionistic fuzzy transportation problem of type-2," Annals of Operations Research, Springer, vol. 243(1), pages 349-363, August.

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