Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 21

Proceedings of the 2020 Federated Conference on Computer Science and Information Systems

Bi-level Optimization Application for Urban Traffic Management


DOI: http://dx.doi.org/10.15439/2020F18

Citation: Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 21, pages 327336 ()

Full text

Abstract. A bi-level modeling for traffic lights optimization is presented. The bi-level modeling allows increasing the set of control influences, the number of constraints and applies two goal functions in hierarchical order. The bi-level formalism allows integration of small optimization problems in hierarchical order to a complex interconnected and complicated optimization problem. These features have been applied for optimal control of traffic lights in urban network. The bi-level problem formulation allows to minimize the queue lengths of vehicles and to maximize the outgoing flows from arterial direction. Both control influences of the green light durations and time cycles are evaluated as optimal bi-level control influences.


  1. B. Park and J. D. Schneeberger, Evaluation of Traffic Signal Timing Optimization Methods Using a Stochastic and Microscopic Simulation Program, Virginia Transportation Research Council, 2003.
  2. W. H. Kraft, W. S. Homburger, and J. L. Pline, Traffic Engineering Handbook, Washington USA, Institute of Transportation Engineers, 2009.
  3. P. Koonce, L. Rodegerdts, K. Lee, S. Quayle, S. Beaird, C. Braud, J. Bonneson, P. Tarnoff, and T. Urbanik, Traffic Signal Timing Manual. Washington: Federal Highway Administration, 2008.
  4. K. Han, Y. Sun, H. Liu, T. L. Friesz, and T. Yao, “A bi-level model of dynamic traffic signal control with continuum approximation,” Transportation Research Part C, vol.55, pp. 409-431, 2015, http://www.sciencedirect.com/science/article/pii/S0968090X15001266, https://www.academia.edu/12549962/A_bi-level_model_of_dynamic_traffic_signal_control_with_continuum_approximation
  5. L. Li, D. Wen, and D. Yao, “A survey of traffic control with vehicular communications,” IEEE Transactions on Intelligent Transportation Systems, vol.15, no 1, pp. 425-432, 2014,. http://dx.doi.org/10.1109/TITS.2013.2277737 https://www.researchgate.net/publication/260720276_A_Survey_of_Traffic_Control_With_Vehicular_Communications
  6. R. P. Roess, E. S. Prassas, and W. R. McShane, Traffic Engineering, 5th ed. Hoboken, NJ Pearson Education, 2019, ISBN-10:0-13-459971-3, ISBN-13:978-0-13-459971-7, https://www.pearsonhighered.com/assets/preface/0/1/3/4/0134599713.pdf
  7. H. Wei, G. Zheng, V. Gayah, and Z. Li, A survey on traffic signal control methods. Cornell University, 2020, https://arxiv.org/pdf/1904.08117.pdf,
  8. M. Papageorgiou, C. Diakaki, V. Dinopoulou, A. Kotsialos, and Y. Wang, Review of road traffic control strategies, in Proc. IEEE 91, 12, pp. 2043–2067, 2003.
  9. E. Eriskin, S. Karahancer, S. Terzi, and M. Saltan, Optimization of traffic signal timing at oversaturated intersections using elimination pairing system. 10th International Scientific Conference Transbaltica, Transportation Science and Technology, Procedia Engineering 187, pp. 295 – 300, 2017, http://dx.doi.org/10.1016/j.proeng.2017.04.378 , https://www.sciencedirect.com/science/article/pii/S1877705817319082
  10. Y. Wang , X. Yang, H. Liang , and Y. Liu, “A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment,” J. of Advanced Transportation, vol. 2018, Article ID 1096123, 12 pages, https://doi.org/10.1155/2018/1096123
  11. T. Tettamanti, I. Varga, and T. Peni, “MPC in urban traffic management,” Model predictive control, Ed.T. Zheng, IntechOpen, 2010 http://dx.doi.org/10.5772/9922. Available from: https://www.intechopen.com/books/model-predictive-control/mpc-in-urban-traffic-management
  12. K. Aboudolas, M. Papageorgiou, and E. Kosmatopoulos, “Store-and-forward based methods for the signal control problem in large-scale congested urban road networks,” Transportation Research Part C, vol.1, pp. 163–174, 2009, http://dx.doi.org/10.1016/j.trc.2008.10.002
  13. R. Scheffle and M. Strehler, “Optimizing Traffic Signal Settings for Public Transport Priority,” 17th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS), 2017. G. D’Angelo and T. Dollevoet; Eds, Article No. 9; pp. 9:1–9:15, http://dx.doi.org/10.4230/OASIcs.ATMOS.2017.9
  14. V. Ivanov, “Monitoring of urban road transport,”.Proc. of Intern conf Аutomatics and Informatics, 2017, pp. 135-141, ISSN:1313-1850.
  15. K. N. Hewage and J. Y. Ruwanpura, „Optimization of traffic signal light timing using simulation”, in Proc. 2004 Winter Simulation Conference, R. G. Ingalls, M. D. Rossetti, J. S. Smith, and B. A. Peters, Eds, 2004, pp.1428-1433, http://dx.doi.org/10.1109/WSC.2004.1371482 ·
  16. A. Jamal, M. T. Rahman, H. M. Al-Ahmadi, I. Ullah, and M. Zahid. Intelligent intersection control for delay optimization: using meta-heuristic search algorithms. 2020, https://www.mdpi.com/2071-1050/12/5/1896/pdf
  17. L. N. Vicente and P. H. Calamai, “Bilevel and multilevel programming: A bibliography review,” J Glob Optim, vol. 5, pp. 291–306, 1994, https://doi.org/10.1007/BF01096458
  18. B. Colson, P. Marcotte, and G. Savard, “An overview of bilevel optimization,” J. Ann Oper Res vol. 153, pp. 235–256, 2007, DOI 10.1007/s10479-007-0176-2, https://www.iro.umontreal.ca/~marcotte/ARTIPS/AOR2007.pdf
  19. S. A. Khandelwal and M. C. Puri, “Bilevel time minimizing transportation problem,” J. Discrete Optimization, volume 5, no 4, pp. 714-723, November 2008, https://doi.org/10.1016/j.disopt.2008.04.004
  20. H. Sun, Z. Gao, and J. Wu, “A bi-level programming model and solution algorithm for the location of logistics distribution centers,” J. Applied Mathematical Modelling, vol. 32, no 4, pp. 610-616, April 2008, https://doi.org/10.1016/j.apm.2007.02.007
  21. A. Arizti, A. Mauttone, and M. E. Urquhart, “A bilevel approach to frequency optimization in public transportation systems,” in 18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2018), .65, pp. 7:1-7:13, ISBN 978-3-95977-096-5, ISSN 2190-6807, http://dx.doi.org/10.4230/OASIcs.ATMOS.2018.7, http://drops.dagstuhl.de/opus/volltexte/2018/9712/
  22. J. Hao, X. Liu, X. Shen, and N. Feng, “Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints,” in Discrete Optimization for Dynamic Systems of Operations Management in Data-Driven Society, 2019, https://doi.org/10.1155/2019/2930502,
  23. M. Patriksson, “Robust bi-level optimization models in transportation science,” Philosophical transactions of royal Society A, vol. 366, no 1872, pp. 1931-1940, 2008, http://doi.org/10.1098/rsta.2008.0007
  24. R. Z. Farahania, E. Miandoabchib, W. Y. Szetoc, and H. Rashidid, “A review of urban transportation network design problems,” European Journal of Operational Research, vol. 229, no 2, September 2013, Pages 281-302, https://doi.org/10.1016/j.ejor.2013.01.001, http://dx.doi.org/10.1016/j.ejor.2013.01.001
  25. X. Jia, R. He, C. Zhang, and H. Chai, "A Bi-Level Programming Model of Liquefied Petroleum Gas Transportation Operation for Urban Road Network by Period-Security," Sustainability, MDPI, Open Access Journal, vol. 10, no 12, pp. 1-20, December 2018, https://ideas.repec.org/a/gam/jsusta/v10y2018i12p4714-d189583.html
  26. K. Moad, J. François , J. P. Bourrières , L. Lebel, and M. Vuillermo, “A bi-level decision model for timber transport planning”, 6th Int conf Information systems, logistics and supply chain, 2016 Bordeaux, http://ils2016conference.com/wp-content/uploads/2015/03/ILS2016_TD02_3.pdf
  27. C. Tawfik, S. Limbourg, “Bilevel optimization in the context of intermodal pricing: state of art,” Transportation Research Procedia, vol. 10, pp. 634 – 643, 2015, https://orbi.uliege.be/bitstream/2268/185274/1/1-s2.0-S2352146515002045-main.pdf , http://dx.doi.org/10.1016/j.trpro.2015.09.017
  28. A. Sinha, P. Malo, and K. Deb, Transportation Policy Formulation as a Multi-objective Bilevel Optimization Problem, 2015, https://www.egr.msu.edu/~kdeb/papers/c2015009.pdf
  29. C. Lu, S. Yan, H. Ko and H. Chen, "A bilevel model with a solution algorithm for locating weigh-in-motion stations," in IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 2, pp. 380-389, Feb. 2018, https://ieeexplore.ieee.org/document/7922613
  30. R. G. Ródenas, M. L. L.García, M. T. S. Rico, and J. A. L. Gómez, “A bilevel approach to enhance prefixed traffic signal optimization,” J. Engineering Applications of Artificial Intelligence, vol. 84, pp. 51-65, September 2019, https://doi.org/10.1016/j.engappai.2019.05.017
  31. S. Goel, S. F. Bush, and C. Gershenson, Self-Organization in Traffic Lights: Evolution of Signal Control w ith Advances in Sensors and Communications, June 2017, https://www.researchgate.net/publication/319271996_Self-Organization_in_Traffic_Lights_Evolution_of_Signal_Control_with_Advances_in_Sensors_and_Communications
  32. https://yalmip.github.io/