Using Automated Planning for Traffic Signals Control
Solving traffic congestions represents a high priority issue in many big cities. Traditional traffic control systems are mainly based on pre-programmed, reactive and local techniques. This paper presents an autonomic system that uses automated planning techniques instead. These techniques are easily configurable and modified, and can reason about the future implications of actions that change the default traffic lights behaviour. The proposed implemented system includes some autonomic properties, since it monitors the current traffic state, detects if the system is degrading its performance, sets up new sets of goals to be achieved by the planner, triggers the planner that generates plans with control actions, and executes the selected courses of actions. The obtained results in several artificial and real world data-based simulation scenarios show that the proposed system can efficiently solve traffic congestion.
Papageorgiou M, Ben-Akiva M, Bottom J, Bovy PHL, Hoogendoorn SP, Hounsell NB, Kotsialos A, McDonald M. ITS and Traffic Management. In: Barnhart C, Laporte G, editors. Handbooks in Operations Research and Management Science, 2007; p 743-754.
Papageorgiou M, Diakaki C, Dinopoulou V, Kotsialos A, Wang Y. Review of road traffic control strategies. Proc. IEEE. 2003 Dec;91(12):2043-2067.
Diakaki C, Papageorgiou M, McLean T. Application and evaluation of the integrated traffic-responsive urban corridor control strategy IN-TUC in Glasgow. Proceedings of the 78th Annual Meeting of the Transportation Research Board; Washington, DC, USA; 1999. Paper 990310.
De Oliveira LB, Camponogara E. Multi-agent model predictive control of signaling split in urban traffic networks. Transp. Res. C, Emerging Technol. 2010 Feb;18(1):120-139.
Bretherton R, Wood K, Bowen GT. SCOOT version 4. Proceedings of the 9th International Conference on Road Transport Information and Control; 1998 Apr 21-23; London, UK; 1998.
Donati F, Mauro V, Roncoloni G, Vallauri M. A hierarchical decentralized traffic light control system: the first realisation “Progetto Torino”. Proceedings of the 9th World Congress of the International Federation of Automotive Control; Budapest, Hungary; 1984. p. 2853-2858.
Lee C, Machemehl RB. Genetic algorithm, local and iterative searches for combining traffic assignment and signal control. Proceedings of the 1st Conference on Traffic and Transportation Studies (ICTTS '98); 1998 July 27-29; Beijing, China; 1998. p. 25-27.
Cascetta E, Gallo M, Montella B. Models and algorithms for the optimization of signal settings on urban networks with stochastic assignment. Ann. Oper. Res. 2006;144(1):301-328.
Heydecker B. A decomposition approach for signal optimisation in road networks. Transp. Res. B. 1996;30(2):99-114.
Chiou SW. Optimization of area traffic control for equilibrium network flows. Transp. Sci. 1999;33(3):279-289.
Wey WM. Model formulation and solution algorithm of traffic signal control in an urban network. Comput. Environ. Urban Syst. 2000;24(4):355-378.
Ziyou G, Yifan S. A reserve capacity model of optimal signal control with user-equilibrium route choice. Transp. Res. Part B. 2002;36(4):313-323.
Gartner N, Little J, Gabby H. Simultaneous optimization of offsets, splits and cycle time. Transp. Res. Rec. 1976;(596):6-15.
Smith MJ. Properties of a traffic control policy which ensure the existence of a traffic equilibrium consistent with the policy. Transp. Res. Part B. 1981;15(6): 453-462.
Alvarez I, Poznyak AS, Malo Tamayo A. Urban traffic control problem: a game theory approach. Proceedings of the 17th World Congress IFAC; 2008 July 6-11; Seoul, Korea; 2008. p. 7154-7159.
Trejo KK, Clempner JB, Poznyak AS. A Stackelberg security game with random strategies based on the extraproximal theoretic approach. Eng. Appl. Artif. Intell. 2015;37:145-153.
Clempner JB, Poznyak AS. Convergence method, properties and computational complexity for Lyapunov games. Int. J. Appl. Math. Comput. Sci. 2011;21(2):349-361.
Clempner JB, Poznyak AS. Modeling the multi-traffic signal-control synchronization: A Markov chains game theory approach. Eng. Appl. of Artif. Intell. 2015;43:147-156.
Tettamanti T, Luspay T, Kulcsár B, Péni T, Varga I. Robust Control for Urban Road Traffic Networks. IEEE Transactions of Intelligent Transportation Systems. 2014;15(1):385-398.
Ghallab M, Nau D, Traverso P. Automated Planning. Theory & Practice. San Francisco: Morgan Kaufmann; 2004.
Fox M, Long D. PDDL2.1: An extension to PDDL for expressing temporal planning domains. Journal of AI Research. 2003;20:61-124.
Garcia J, Florez JE, Torralba A, Borrajo D, Linares-Lopez C, Garcia-Olaya A, Saenz J. Combining linear programming and automated planning to solve multimodal transportation problems. European Journal of Operations Research. 2013;227(1):216-226.
Castillo L, Armengol E, Onaindia E, Sebastiá L, González-Boticario J, Rodríguez A, Fernández S, Arias JD, Borrajo D. SAMAP. A user-oriented adaptive system for planning tourist visits. Expert Systems with Applications. 2008 Feb;34(2):1318-1332.
Ai-Chang M, Bresina J, Charest L, Chase A, Hsu JC-J, Jonsson A, Kanefsky B, Morris P, Rajan K, Yglesias J, Chafin BG, Dias WC, Maldague PF. MAPGEN: Mixed-initiative planning and scheduling for the Mars Exploration Rover mission. IEEE Intelligent Systems. 2004 Feb;19(1):8-12.
Simulation of Urban MObility (SUMO) [homepage on Internet]. [cited 2015 June 06]. Available from: http://sumo.dlr.de/wiki/Main_Page
Krajzewicz D, Erdmann J, Behrisch M, Bieker L. Recent development and applications of SUMO - Simulation of Urban MObility. International Journal On Advances in Systems and Measurements. 2012 Dec;5(3&4):128-138.
Behrisch M, Bieker L, Erdmann J, Krajzewicz D. Sumo - simulation of urban mobility: An overview. SIMUL 2011, The Third International Conference on Advances in Systems Simulation; 2011 October 23-28; Barcelona; 2011. p. 63-68.
Piórkowski M, Raya M, Lugo A, Papadimitratos P, Grossglauser M, Hubaux J-P. TraNS: Realistic joint traffic and network simulator for VANETs. ACM SIGMOBILE Mobile Computing and Communications Review. 2008 Jan;12(1):31-33.
Schäfer R-P. IQ routes and HD traffic: technology insights about tomtom’s time-dynamic navigation concept. Proceedings of the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering (ESEC/FSE ‘09); 2009 Aug 24-28; Amsterdam, The Netherlands; New York, USA: ACM New York; 2009. p. 171-172.
Krajzewicz D, Brockfeld E, Mikat J, Ringel J, Rössel C, Tuchscheerer W, Wagner P, Wösler R. Simulation of modern traffic lights control systems using the open source traffic simulation SUMO. Proceedings of the 3rd Industrial Simulation Conference; 2005 June 9-11; Berlin, Germany; 2005. p. 299-302.
Nota R, Barelds R, van Maercke D. Harmonoise WP 3 Engineering method for road traffic and railway noise after validation and fine-tuning. Technical Report Deliverable 18; Berlin, Germany; 2005.
OpenStreetMap [homepage on Internet]. [cited 2015 June 06] Available from: http://www.openstreetmap.org
TraCI [homepage on Internet]. [cited 2015 June 06] Available from: http://sumo.dlr.de/wiki/TraCI
Ghallab M, Howe A, Knoblock C, McDermott D, Ram A, Veloso M, Weld D, Wilkins D. PDDL – The planning domain definition language. Yale Center for Computational Vision and Control. Tech Report CVC TR-98-003/DCS TR-1165; 1998 Oct.
Németh B, Csikós A, Varga I, Gáspár P. Multicriteria cruise control design considering geographic and traffic conditions. Acta Polytechnica Hungarica. 2013;10(6):119-134.
ICAPS [homepage on Internet]. [cited 2015 June 06] Available from: http://ipc.icaps-conference.org
Richter S, Westphal M. The LAMA planner: Guiding cost-based anytime planning with landmarks. Journal of AI Research. 2010;39:127-177.
Jiménez S, Fernández F, Borrajo D. Integrating planning, execution and learning to improve plan execution. Computational Intelligence Journal. 2013;29(1):1-36.
Tools/Import/OSM [homepage on Internet]. [cited 2015 June 06] Available from: http://sumo.dlr.de/wiki/Tools/Import/OSM#server.py
Allsop R. Some possibilities for using traffic control to influence trip distribution and route choice. Proceedings of the 6th International Symposium on Transportation and Traffic Theory; 1974 Aug 26-28; Sydney, Australia; New York, USA: Elsevier Publishing Company; 1974. p. 345-374.
Yang H, Yagar S. Traffic assignment and signal control in saturated road networks. Transportation Research Part A: Policy and Practice. 1995;29(2):125-139.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).