Abstract
Linking real-time phase saturability directly to the traffic signal control, the global adaptive control scheme for traffic light loop and the local scheduling control strategy for phase green time are proposed in this paper for real-time traffic signal control systems with multiple phases. First, applying the real-time phase saturability of each phase as the time-varying weight factor, an elastic scheduling model is designed to describe the competitive relationship among the different phase in a traffic light loop. Then the traffic green time scheduling problem in a traffic light loop is formulated as a trade-off optimization problem between the green light time and real-time phase saturability for each phase. By solving a quadratic programming problem that seeks the minimum value of the sum of the squared deviation between the green time and the maximum allowable green time in each phase, the allocated green time in next traffic loop is obtained. If the total real-time traffic load exceeds the allocable maximum value or unreaches the allocable minimum value, the proportional global adaptive control schemes are triggered for rearranging traffic light loop time. Undertaking different traffic flow conditions, the effectiveness of proposed adaptive control schemes and scheduling strategies are illustrated compared with the classic average allocating method.
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
Prashanth, L.A., Shalabh, B.: Reinforcement learning with function approximation for traffic signal control. IEEE Trans. Intell. Transp. Syst. 12, 412–421 (2001)
Zhao, D., Dai, Y., Zhang, Z.: Computational intelligence in urban traffic signal control: a survey. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 42, 485–494 (2012)
Behrang, A., Ardalan, V.: Predictive cruise control: utilizing upcoming traffic signal information for improving fuel economy and reducing trip time. IEEE Trans. Control Syst. Technol. 19, 707–714 (2011)
Han, S.-Y., Zhang, C.-H., Tang, G.-Y.: Approximation optimal vibration for networked nonlinear vehicle active suspension with actuator time delay. Asian J. Control (2017). doi:10.1002/asjc.1419
Han, S.-Y., Tang, G.-Y., Chen, Y.-H., Yang, X.-X., Yang, X.: Optimal vibration control for vehicle active suspension discrete-time systems with actuator time delay. Asian J. Control 15, 1579–1588 (2013)
Han, S.-Y., Wang, D., Chen, Y.-H., Tang, G.-Y., Yang, X.-X.: Optimal tracking control for discrete-time systems with multiple input delays under sinusoidal disturbances. Int. J. Control Autom. Syst. 13, 292–301 (2015)
Han, S.-Y., Chen, Y.-H., Wang, L., Abraham, A.: Decentralized longitudinal tracking control for Cooperative Adaptive Cruise Control Systems in a platoon. In: IEEE International Conference on Systems, Man, and Cybernetics, pp. 2013–2018 (2013)
Zhou, J., Chen, C.L.P., Chen, L., Li, H.X.: A collaborative fuzzy clustering algorithm in distributed network environments. IEEE Trans. Fuzzy Syst. 22, 1443–1456 (2014)
Zhou, J., Chen, C.L.P., Chen, L., Li, H.X.: Fuzzy clustering with the entropy of attribute weights. Neurocomputing 198, 125–134 (2016)
Han, S.-Y., Chen, Y.-H., Tang, G.-Y.: Sensor fault and delay tolerant control for networked control systems subject to external disturbances. Sensors 17, 700 (2017)
Zhou, J., Chen, C.L.P., Chen, L., Li, H.X.: A user customizable urban traffic information collection method based on wireless sensor networks. IEEE Trans. Intell. Transp. Syst. 14, 1119–1128 (2013)
Wei, J., Wang, A., Du, N.: Study of self organizing control of traffic signals in an urban network based on cellular automata. IEEE Trans. Veh. Technol. 54, 744–748 (2005)
Yin, B., Dridi, M., Abdellah, E.M.: Traffic network microsimulation model and control algorithm based on approximate dynamic programming. IET Intell. Transp. Syst. 10, 186–196 (2016)
Mirchandani, P.B., Zou, N.: Queuing models for analysis of traffic adaptive signal control. IEEE Trans. Intell. Transp. Syst. 8, 50–59 (2007)
Srinivasan, D., Choy, M.C., Chen, R.L.: Neural networks for real-time traffic signal control. IEEE Trans. Intell. Transp. Syst. 7, 261–272 (2009)
Choy, M.C., Srinivasan, D., Chen, R.L.: Cooperative, hybrid agent architecture for real-time traffic signal control. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 33, 597–604 (2003)
Sameh, S., Ahmed, E.-M., Yasutaka, W.: A linear time and spacing algorithm for optimal traffic signal duration at an intersection. IEEE Trans. Intell. Transp. Syst. 16, 387–395 (2015)
Yang, X., Li, X., Xue, K.: A new traffic signal control for modern roundabouts: method and application. IEEE Trans. Intell. Transp. Syst. 5, 282–297 (2004)
Buttazzo, G., Lipari, G., Caccamo, M., Abeni, L.: Elastic scheduling for flexible workload management. IEEE Trans. Comput. 51, 289–302 (2002)
Tian, Y.-C., Jiang, X., Levy, D.C., Agrawala, A.: Local adjustment and global adaption of control periods for QoC management of control systems. IEEE Trans. Control Syst. Technol. 20, 846–854 (2012)
Chandra, R., Liu, X., Sha, L.: On the scheduling of flexible and reliable real-time control systems. Real-Time Syst. 24, 153–169 (2003)
Amirijoo, M., Hansson, J., Son, S.H., Gunnarsson, S.: Experimental evaluation of linear time-invariant models for feedback performance control in real-time systems. Real-Time Syst. 35, 209–238 (2007)
Acknowledgments
This work was supported by the National Key Research and Development Plan (No. 2016YFC0106000), the National Natural Science Foundation of China (Grant No. 61640218, 61671220, 61573166, 61673357), the Shandong Distinguished Middle-aged and Young Scientist Encourage and Reward Foundation, China (Grant No. BS2014DX015, ZR2016FB14), the Project of Shandong Province Higher Educational Science and Technology Program, China (Grant No. J16LN07), the Shandong Province Key Research and Development Program, China (Grant No. 2016GGX101022).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Han, SY., Ping, F., Zhang, Q., Chen, YH., Zhou, J., Wang, D. (2017). Global Adaptive and Local Scheduling Control for Smart Isolated Intersection Based on Real-Time Phase Saturability. In: Huang, DS., Jo, KH., Figueroa-García, J. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10362. Springer, Cham. https://doi.org/10.1007/978-3-319-63312-1_65
Download citation
DOI: https://doi.org/10.1007/978-3-319-63312-1_65
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-63311-4
Online ISBN: 978-3-319-63312-1
eBook Packages: Computer ScienceComputer Science (R0)