Traffic Signal Optimization with Greedy Randomized Tabu Search Algorithm
This article has a reply.
VIEW THE REPLYThis article has a reply.
VIEW THE REPLYPublication: Journal of Transportation Engineering
Volume 138, Issue 8
Abstract
Although advanced technologies, such as detection techniques and controllers, have been incorporated within Advanced Traffic Management Systems (ATMS), pretimed signal control still plays an important role in traffic control and management. A wide variety of techniques were proposed to generate optimal or near-optimal solutions for signal optimization problems. However, only a limited research was devoted to the application of tabu search in the signal optimization problem. The characteristics of tabu search could provide accuracy and efficiency with the careful design of local search methods. This research applies a randomized meta-heuristic algorithm, greedy randomized tabu search (GRTS), for network-level signal optimization problems. With the flexibility of the GRTS, detailed representations of signal control settings could be added easily. To compare the performance of GRTS with other algorithms, genetic algorithm (GA) is chosen and implemented. The performance of the GRTS is investigated in numerical analysis in two networks, including a test network and a real city network. Numerical experiments on the test network are used in the comparison of the GA and GRTS algorithms. Numerical experiments on the real city network are conducted to illustrate possible benefits from the proposed approach. The results show that more than 25% reduction of travel time can be achieved for medium and high demand levels.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This paper is based on work partially supported by National Science Council of Taiwan, ROC, through the project NSC 99-2420-H-006-004-DR. Of course, the writers are solely responsible for the contents of this paper.
References
Abu-Lebdeh, G., and Benekohal, R. F. (1997). “Development of a traffic control and queue management procedure for oversaturated arterials.” Transportation Research Record 1603, Transportation Research Board, Washington, DC, 119–127.
Allsop, R. E., and Charlesworth, J. A. (1977). “Traffic in a signal controlled road network: An example of different signal timings inducing different routing.” Traffic Eng. ControlTENCA4, 18(5), 262–264.
Beard, C., and Ziliaskopoulos, A. (2006). “A system optimal signal optimization formulation.” Proc., 85th Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
Bretherton, D., Bodger, M., and Baber, N. (2004). “SCOOT—The future [urban traffic control].” Proc., 12th Int. Conf. on Road Transport Information and Control, IEEE, New York, 301–306.
Ceylan, H., and Bell, M. G. H. (2004). “Traffic signal timing optimisation based on genetic algorithm approach, including drivers’ routing.” Transp. Res. Part BTRBMDY, 38(4), 329–342.
Farges, J. L. (1983). “Commande du tafic urbain par programmation dynamique et methodes hierarchisees.” Ph.D. dissertation, Ecole Nationale de la Statistique et de l'Administration Economique, Toulouse France (in French).
Federal Highway Administration. (1996). “Traffic control systems handbook.” Publication No. FHWA-SA-95-032, Dept. of Transportation, Washington, DC.
Federal Highway Administration. (2005). “Traffic control systems handbook.” Publication No. FHWA—HOP–06–006, Dept. of Transportation, Washington, DC, 〈http://ops.fhwa.dot.gov/publications/fhwahop06006/index.htm〉 (Apr. 20, 2011).
Foy, M. D., Benekohal, R. F., and Goldberg, D. E. (1992). “Signal timing determination using genetic algorithms.” Transportation Research Record 1365, Transportation Research Board, Washington, DC, 108–115.
Glover, F., and Laguna, M. (1997). Tabu search, Kluwer Academic Publishers, Norwell, MA.
Hadi, M. A., and Wallace, C. E. (1993). “Hybrid genetic algorithm to optimize signal phasing and timing.” Transportation Research Record 1421, Transportation Research Board, Washington, DC, 104–112.
Hale, D. (2005). “Traffic network study tool—TRANSYT-7F United States Version.” McTrans Center in the Univ. of Florida, Gainesville, FL.
Gartner, N. H. (1983). “OPAC: A demand-responsive strategy for traffic signal control.” Transportation Research Record 906, Transportation Research Board, Washington, DC, 75–81.
Gartner, N. H., Assmann, S. F., Lasaga, F., and Hom, D. L. (1991). “A multiband-band approach to arterial traffic signal optimization.” Transp. Res. Part BTRBMDY, 25(1), 55–74.
Gartner, N. H., Stamatiadis, C., and Tarnoff, P. J. (1995). “Development of advanced traffic signal control strategies for intelligent transportation systems: Multilevel design.” Transportation Research Record 1494, Transportation Research Board, Washington, DC, 98–105.
Hu, T. Y., Liao, T. Y., Chen, L. W., Huang, Y. K., and Chiang, M. L. (2007). “Dynamic simulation-assignment model (DynaTAIWAN) under mixed traffic flows for ITS applications.” Proc., 86th Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
Hu, T. Y., Tong, C. C., Liao, T. Y., and Chen, L. W. (2008). “Simulation-based dynamic traffic assignment model for mixed traffic flows.” Proc., 87th Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
Hu, T. Y., Tong, C. C., Liao, T. Y., Chen, L. W., Huang, Y. K., and Chiang, M. L. (2009). “Validation and calibration of DynaTAIWAN in urban networks for real-time operations.” Final Rep., Institute of Transportation, Ministry of Transportation and Communications, Beijing, (in Chinese).
Hunt, P. B., Robertson, D. I., and Bretherton, R. D. (1982). “The SCOOT on-line traffic signal optimization technique.” Traffic Eng. ControlTENCA4, 23(4), 190–192.
Husch, D., and Albeck, J. (2006). SYNCHRO Studio 7 user guide, Trafficware, Albany, CA.
Karoonsoontawong, A., and Waller, S. T. (2009). “Combined dynamic user equilibrium and traffic signal optimization problem: reactive tabu search approach.” Proc., 88th Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
Kesur, K. B. (2009). “Advances in genetic algorithm optimization of traffic signals.” J. Transp. Eng.JTPEDI, 135(4), 160–173.
Liao, T. Y., Hu, T. Y., Chen, L. W., and Ho, W. M. (2010). “Development and empirical study of real-time simulation-based dynamic traffic assignment model.” J. Transp. Eng.JTPEDI 136(11), 1008–1020.
Lin, W. H., and Wang, C. (2004). “An enhanced 0-1 mixed-integer linear program formulation for traffic signal control.” IEEE Trans. Intell. Transp. Syst., 5(4), 238–245.
Lo, H. K. (1999). “A novel traffic signal control formulation.” Transp. Res. Part ATRPPEC, 33(6), 433–448.
Lo, H. K., Chang, E., and Chan, Y. C. (2001). “Dynamic network traffic control.” Transp. Res. Part ATRPPEC, 35(8), 721–744.
Lowrie, P. R. (1982). “SCATS: The Sydney coordinated adaptive traffic system—Principles, methodology, algorithms.” Proc., IEEE Int. Conf. on Road Traffic Signalling, IEEE, New York, 67–70.
Mauro, V. (1991). “Road network control.” Concise encyclopedia of traffic and transportation systems, Pergamon Press, Oxford, UK, 361–366.
Mirchandani, P., and Head, L. (1998). “RHODES—A real-time traffic signal control system: Architecture, algorithms, and analysis.” Proc., TRISTAN III (Triennial Symp. on Transportation Analysis).
Mirchandani, P., and Wang, F. Y. (2005). “RHODES to intelligent transportation systems.” IEEE Intell. Syst., 20(1), 10–15.
Park, B., and Lee, J. (2009). “Optimization of coordinated-actuated traffic signal system using shuffled frog leaping algorithm-Based stochastic optimization method.” Proc., 88th Transportation Research Board Annual Meeting, Transportation Research Board, Washington, DC.
Park, B., Messer, C. J., and Urbanik, T. II (1999). “Traffic signal optimization program for oversaturated conditions genetic algorithm approach.” Transportation Research Record 1683, Transportation Research Board, Washington, DC, 133–142.
Park, B., Rouphail, N. M., and Sacks, J. (2001). “Assessment of stochastic signal optimization method using microsimulation.” Transportation Research Record 1748, Transportation Research Board, Washington, DC, 40–45.
PASSER V [Computer software]. (2002). Texas Transportation Institute, College Station, TX.
Pooran, F. J., Andrews, C., and Gartner, N. H. (1999). “Implementation of the OPAC adaptive control system in RT-TRACS.” Proc., 6th World Congress on Intelligent Transport Systems Annual Meeting, ITS America, Washington, DC.
Resende, M. G. C., and Ribeiro, C. C. (2003). “Greedy randomized adaptive search procedures.” International series in operations research & management science, No. 57, Springer, New York, 219–249.
Schutter, B. D., and Moor, B. D. (1998). “Optimal traffic light control for a single intersection.” Eur. J. Control, 4(3), 260–276.
Stevanovic, A., Martin, P. T., and Stevanovic, J. (2007). “VISSIM-based genetic algorithm optimization of signal timings.” Transportation Research Record 2035, Transportation Research Board, Washington, DC, 59–68.
Tourism and Traffic Bureau of Kaohsiung County Government. (2006). “The fundamental planning of light rail transportation (Yenchao line) in Kaohsiung urban area.” Final Rep, Kaohsiung County Government, China.
Wey, W. M. (2000). “Model formulation and solution algorithm of traffic signal control in an urban network.” Comput. Environ. Urban Syst.CEUSD5, 24(4), 355–377.
Wey, W. M., and Jayakrishnan, R. (1999). “Network traffic signal optimization formulation with embedded platoon dispersion simulation.” Transportation Research Record 1683, Transportation Research Board, Washington, DC, 150–159.
Wood, K. (1993). “Urban traffic control, systems review.” Project Rep.41, Transport Research Laboratory, Crowthorne, UK.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 138 • Issue 8 • August 2012
Pages: 1040 - 1050
Copyright
© 2012. American Society of Civil Engineers.
History
Received: Apr 24, 2011
Accepted: Dec 29, 2011
Published online: Jan 6, 2012
Published in print: Aug 1, 2012
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.