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First published online January 1, 2014

Coupled Linear Programming Approach for Decentralized Control of Urban Traffic

Abstract

Management of urban traffic systems is a challenging task, partly because queue spillbacks, which bring about loss of intersection capacities and lead to systemwide congestion, arise easily in moderately congested networks. One possible way of ensuring mobility is through proactive spatial distribution of queues to contain their impact locally. In this paper, a traffic signal control strategy based on this idea is proposed. The strategy is traffic adaptive and operates in a decentralized fashion. It is formulated as a coupled system of linear programs, each optimizing a local queuing pattern according to real-time queue information and history of boundary flows. The proposed control is constructed to be scalable and robust to system uncertainties. Its properties (e.g., avoidance of queue spillback and stabilization of traffic) are demonstrated through numerical experiments.

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References

1. Sims A., and Dobinson K. The Sydney Coordinated Adaptive Traffic (SCAT) System Philosophy and Benefits. IEEE Transactions on Vehicular Technology, Vol. 29, No. 2, 1980, pp. 130–137.
2. Hunt P. B., Robertson D. I., Bretherton R. D., and Winton R. I. SCOOT—A Traffic Responsive Method of Coordinating Signals. Report 1014. Transport and Road Research Laboratory, Crowthorne, Berkshire, United Kingdom, 1981.
3. Lo H. K. A Novel Traffic Signal Control Formulation. Transportation Research Part A: Policy and Practice, Vol. 33, No. 6, 1999, pp. 433–448.
4. Chang T.-H., and Sun G.-Y. Modeling and Optimization of an Oversaturated Signalized Network. Transportation Research Part B: Methodological, Vol. 38, No. 8, 2004, pp. 687–707.
5. Gartner N. H. OPAC: A Demand-Responsive Strategy for Traffic Signal Control. In Transportation Research Record 906, TRB, National Research Council, Washington, D.C., 1983, pp. 75–81.
6. Zhang H. M., Ma J., and Nie Y. Local Synchronization Control Scheme for Congested Interchange Areas in Freeway Corridor. In Transportation Research Record: Journal of the Transportation Research Board, No. 2128, Transportation Research Board of the National Academies, Washington, D.C., 2009, pp. 173–183.
7. Varaiya P. The Max-Pressure Controller for Arbitrary Networks of Signalized Intersections. In Advances in Dynamic Network Modeling in Complex Transportation Systems (Ukkusuri S. V., and Ozbay K., eds.), Springer, 2013, New York, pp. 27–66.
8. Lämmer S., and Helbing D. Self-Control of Traffic Lights and Vehicle Flows in Urban Road Networks. Journal of Statistical Mechanics: Theory and Experiment, 2008.
9. Donner R. Emergence of Synchronization in Transportation Networks with Biologically Inspired Decentralized Control. Recent Advances in Nonlinear Dynamics and Synchronization, Vol. 254, 2009, pp. 237–275.
10. Xie X.-F., Smith S. F., Lu L., and Barlow G. J. Schedule-Driven Intersection Control. Transportation Research Part C: Emerging Technologies, Vol. 24, October 2012, pp. 168–189.
11. Smith S. F., Barlow G. J., Xie X.-F., and Rubinstein Z. B. SURTRAC: Scalable Urban Traffic Control. Presented at 92nd Annual Meeting of the Transportation Research Board, Washington, D.C., 2013.
12. Papageorgiou M., Diakaki C., Dinopoulou V., Kotsialos A., and Wang Y. Review of Road Traffic Control Strategies. Proceedings of the IEEE, Vol. 91, No. 12, 2003, pp. 2043–2067.
13. Wu X., Liu H. X., and Gettman D. Identification of Oversaturated Intersections Using High-Resolution Traffic Signal Data. Transportation Research Part C: Emerging Technologies, Vol. 18, No. 4, 2010, pp. 626–638.
14. Bazzan A. L. A Distributed Approach for Coordination of Traffic Signal Agents. Autonomous Agents and Multi-Agent Systems, Vol. 10, No. 2, 2005, pp. 131–164.
15. Daganzo C. The Cell Transmission Model: A Dynamic Representation of Highway Traffic Consistent with the Hydrodynamic Theory. Transportation Research Part B: Methodological, Vol. 28, No. 4, 1994, pp. 269–287.
16. Ben-Tal A., and Nemirovski A. Robust Solutions of Uncertain Linear Programs. Operations Research Letters, Vol. 25, No. 1, 1999, pp. 1–13.
17. Yin Y. Robust Optimal Traffic Signal Timing. Transportation Research Part B: Methodological, Vol. 42, No. 10, 2008, pp. 911–924.
18. Fujisaka H., and Yamada T. Stability Theory of Synchronized Motion in Coupled-Oscillator Systems. Progress of Theoretical Physics, Vol. 69, No. 1, 1983, pp. 32–47.
19. Sekiyama K., Nakanishi J., Takagawa I., Higashi T., and Fukuda T. Self-Organizing Control of Urban Traffic Signal Network. IEEE International Conference on Systems, Man, and Cybernetics, Vol. 4, 2001, pp. 2481–2486.
20. Biham O., Middleton A. A., and Levine D. Self-Organization and a Dynamical Transition in Traffic-Flow Models. Physical Review A, Vol. 46, No. 10, 1992, pp. R6124–R6127.
21. Brockfeld E., Barlovic R., Schadschneider A., and Schreckenberg M. Optimizing Traffic Lights in a Cellular Automaton Model for City Traffic. Physical Review E, Vol. 64, No. 5, 2001. http://arxiv.org/pdf/cond-mat/0107056.pdf.

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Article first published online: January 1, 2014
Issue published: January 2014

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© 2014 National Academy of Sciences.
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Authors

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Jia Li
Room 1001, Ghausi Hall, Department of Civil and Environmental Engineering, University of California, 1 Shields Avenue, Davis, CA 95616.
H. Michael Zhang
Room 3145, Ghausi Hall, Department of Civil and Environmental Engineering, University of California, 1 Shields Avenue, Davis, CA 95616.

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