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Coupling Statistical and Agent-Based Models in the Optimization of Traffic Signal Control

  • Dang-Truong Thinh
  • Hoang-Van Dong
  • Nguyen-Ngoc Doanh
  • Nguyen-Thi-Ngoc AnhEmail author
Conference paper
  • 578 Downloads
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 221)

Abstract

There have been two directions to target to the problem of Traffic Signal Control (TSC): macroscopic and microscopic. On one hand, macroscopic help to find the optimal solution with an assumption of homogenization (both for vehicles and environment). On the other hand, microscopic one can take into account heterogeneity in vehicles as well as in environment. Therefore, it is very important to couple the two directions in the study of TSC. In this paper, we proposed to couple statistical and agent-based models for TSC problem in one intersection. The experiment results indicated that the proposed model is sufficient good in comparison with some others TSC strategies.

Keywords

Traffic Signal Control (TSC) Agent-based Model Light Aging Vehicle Agent Yellow State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Khamis, M.A., Gomaa, W.: Adaptive multi-objective reinforcement learning with hybrid exploration for traffic signal control based on cooperative multi-agent framework. Eng. Appl. Artif. Intell. 29, 134–151 (2014)CrossRefGoogle Scholar
  2. 2.
    Favorskaya, M., Kazmiruk, E., Popov, A.: Distributed system for crossroads traffic surveillance with prediction of incidents. Procedia Comput. Sci. 35, 851–860 (2014)CrossRefGoogle Scholar
  3. 3.
    Antoniou, C., Koutsopoulos, H.N., Yannis, G.: Dynamic data-driven local traffic state estimation and prediction. Transp. Res. Part Emerg. Technol. 34, 89–107 (2013)CrossRefGoogle Scholar
  4. 4.
    Cipriano, F.R.A.: Agent-based model predictive control for the holding problem in a metro system. IFAC Proc. Vol. 46(9), 1666–1671 (2013). ISSN 1474-6670CrossRefGoogle Scholar
  5. 5.
    Nguyen, M.H., Ho, T.V., Nguyen, T.H.: On the dynamic optimization of traffic lights. In: Asian Simulation and Modeling, pp. 35–43. Mahidol University (2013)Google Scholar
  6. 6.
    Nguyen, T.N.A., Chevaleyre, Y., Zucker, J.D.: Optimizing the placement of evacuation signs on road network with time and casualties in case of a Tsunami, enabling technologies. In: 2012 IEEE 21st International Workshop on Infrastructure for Collaborative Enterprises (WETICE), pp. 394–396. IEEE (2012)Google Scholar
  7. 7.
    Anh, N.T.N., Daniel, Z.J., Du, N.H., Drogoul, A., An, V.D.: A hybrid macro-micro pedestrians evacuation model to speed up simulation in road networks. In: Dechesne, F., Hattori, H., ter Mors, A., Such, J.M., Weyns, D., Dignum, F. (eds.) AAMAS 2011. LNCS (LNAI), vol. 7068, pp. 371–383. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-27216-5_28 CrossRefGoogle Scholar
  8. 8.
    Drogoul, A., Amouroux, E., Caillou, P., Gaudou, B., Grignard, A., Marilleau, N., Taillandier, P., Vavasseur, M., Vo, D.-A., Zucker, J.-D.: Gama: multi-level and complex environment for agent-based models and simulations. In: Proceedings of the 2013 International Conference on Autonomous Agents and Multi-Agent Systems, pp. 1361–1362. International Foundation for Autonomous Agents and Multiagent Systems (2013)Google Scholar
  9. 9.
    Li, B., Der Kiureghian, A.: Operational modal identification using variational Bayes. Mech. Syst. Signal Process. 88, 377–398 (2017).  https://doi.org/10.1016/j.ymssp.2016.11.007. ISSN 0888-3270CrossRefGoogle Scholar
  10. 10.
    Park, J., Abdel-Aty, M., Lee, J.: Use of empirical and full Bayes beforeafter approaches to estimate the safety effects of roadside barriers with different crash conditions. J. Saf. Res. 58, 31–40 (2016).  https://doi.org/10.1016/j.jsr.2016.06.002. ISSN 0022-4375CrossRefGoogle Scholar
  11. 11.
    Zhang, T., De Grande, R.E., Boukerche, A.: Design and analysis of stochastic traffic flow models for vehicular clouds. Ad Hoc Netw. 52, 39–49 (2016). ISSN 1570-8705CrossRefGoogle Scholar
  12. 12.
    Chow, A.H.F., Li, S., Zhong, R.: Multi-objective optimal control formulations for bus service reliability with traffic signals. Transp. Res. Part B Methodol. 103, 248–268 (2017). Available online 15 March 2017CrossRefGoogle Scholar
  13. 13.
    Yan, F., Tian, F., Shi, Z.: An extended signal control strategy for urban network traffic flow. Phys. A Stat. Mech. Appl. 445, 117–127 (2016)MathSciNetCrossRefGoogle Scholar
  14. 14.
    He, Z., Hua, Y., Wang, L.: Steady-state traffic signal control with variable phase combinations and sequences. IFAC-PapersOnLine 49(3), 11–18 (2016)CrossRefGoogle Scholar
  15. 15.
    Smith, M.: Traffic signal control and route choice: a new assignment and control model which designs signal timings. Transp. Res. Part C Emerg. Technol. 58, 451–473 (2015)CrossRefGoogle Scholar
  16. 16.
    He, Q., Kamineni, R., Zhang, Z.: Traffic signal control with partial grade separation for oversaturated conditions. Transp. Res. Part C Emerg. Technol. 71, 267–283 (2016)CrossRefGoogle Scholar
  17. 17.
    Fang, F.C., Xu, W.L., Lin, K.C., Alam, F., Potgieter, J.: Matsuoka neuronal oscillator for traffic signal control using agent-based simulation. Procedia Comput. Sci. 19, 389–395 (2013)CrossRefGoogle Scholar
  18. 18.
    Stroeve, S.H., Everdij, M.H.C.: Agent-based modelling and mental simulation for resilience engineering in air transport. Saf. Sci. 93, 29–49 (2017)CrossRefGoogle Scholar
  19. 19.
    Xu, Y., Xi, Y., Li, D., Zhou, Z.: Traffic signal control based on Markov decision process. IFAC-PapersOnLine 49(3), 67–72 (2016)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Dang-Truong Thinh
    • 1
  • Hoang-Van Dong
    • 1
  • Nguyen-Ngoc Doanh
    • 2
    • 3
  • Nguyen-Thi-Ngoc Anh
    • 1
    • 3
    Email author
  1. 1.Hanoi University of Science and TechnologyHanoiVietnam
  2. 2.Thuy Loi UniversityHanoiVietnam
  3. 3.IRD, Sorbonne Universités, UPMC Univ Paris 06 UMMISCOBondy CedexFrance

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