Abstract
In this paper, a new coordinated control model is proposed based on the vehicular operational features, and a multi-objective optimization algorithm NSGA-II is employed to the model for the operation of the vehicle traveling on an urban arterial road taking three evaluation indexes into consideration as the average vehicle delay, the queue length, and the vehicle exhaust emission. A numerical experiment was made in an urban arterial road with three intersections on VISSIM for the proposed strategy, and the simulation results were compared with two commonly used pre-timed methods: Webster’s method and MAXBAND coordinated control method to verify the effectiveness of the proposed strategy in dealing with the unbalanced traffic volume condition, and it proved its advantages in designing and managing traffic systems more efficiently.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Pisarski, A.E.: Prescriptions for research: reviewing the history of TRB’s critical issues in transportation. Tr News (2003)
Zhang, X., Yu, L., Liu, M.: Traffic demand-based traffic congestion measurement models for road networks. Modern Transp. Technol. 5(6), 71–75 (2008) (in Chinese)
Vreeswijk, J.D., Mahmod, M.K.M., Van Arem, B.: Energy efficient traffic management and control—the eCoMove approach and expected benefits. In: International IEEE Conference on Intelligent Transportation Systems (pp. 955–961). IEEE (2010)
Kirkby, P., Kadengal, R.: Traffic management and control using a single ‘congestion price’ like variable across multiple layers of network hierarchy. Control Next Gener. Netw. 67, 4/1–4/6. IET (2002)
Samadi, S., Rad, A.P., Kazemi, F.M., Jafarian, H.: Performance evaluation of intelligent adaptive traffic control systems: a case study. J. Transp. Technol. 2(3), 248–259 (2012)
Tang, T., Lu, J., Zhang, C., Zhang, W., Zhang, Y.: Optimal speed limit investigation on highway for emission reductions. Modern Transp. Technol. 15(1), 82–86 (2018) (in Chinese)
Grote, M., Williams, I., Preston, J., Kemp, S.: Including congestion effects in urban road traffic co2, emissions modelling: do local government authorities have the right options? Transp. Res. Part D Transp. Environ. 43, 95–106 (2016)
Xiao, X.W., Xiao, D., Lin, J.G., Xiao, Y.F.: Overview on multi-objective optimization problem research. Appl. Res. Comput. 28(3), 805–167 (2011)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: nsga-ii. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
Cui, M.Y., Liu, H.Z., Liu, W., Jiang, H.L., Wang, Z.P., Huang, Y.D.: Multi-objective optimization based on improved nsga-II algorithm. J. Nanyang Normal Univ. 13(12), 8–12 (2014)
Qiao, F., Sun, H., Wang, Z., Tobi, F.A.: NSQGA-based optimization of traffic signal in isolated intersection with multiple objectives. Innov. Tech. Appl. Modell. Ident. Control, 291–305 (2018)
Little, J.D.C., Kelson, M.D., Gartner, N.H.: Maxband: a program for setting signal on arteries and triangular network. Transp. Res. Rec. J. Trans. Res. Board 795, 40–46 (1981)
Acknowledgements
This research is partially supported by the National Natural Science Foundation of China (No. 61703288).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Qiao, F., Sun, H., Guo, L., Song, H., Wang, Z. (2019). Multi-objective Optimization Coordination for Urban Arterial Roadway Based on Operational-Features. In: Fang, Q., Zhu, Q., Qiao, F. (eds) Advancements in Smart City and Intelligent Building. ICSCIB 2018. Advances in Intelligent Systems and Computing, vol 890 . Springer, Singapore. https://doi.org/10.1007/978-981-13-6733-5_30
Download citation
DOI: https://doi.org/10.1007/978-981-13-6733-5_30
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6732-8
Online ISBN: 978-981-13-6733-5
eBook Packages: EngineeringEngineering (R0)