Abstract
To monitor and control traffic at signalized intersections, several traffic signal control systems (TSCSs) were developed based on optimization and artificial intelligence techniques. Unfortunately, existing approaches put little emphasis on providing concepts and mechanisms that are generic enough to deal with a variety of disturbances while maintaining traffic fluidity. Moreover, only a few works have investigated case-based reasoning (CBR) to control traffic at signalized intersections. Existing works usually state that the case-base is created using experts’ knowledge but do not specify how this knowledge is acquired and how the case-base is built. The contribution of this study is threefold. First, a new TSCS is designed to monitor and control traffic at a signalized intersection using innovative concepts and mechanisms borrowed from the biological immune memory and secondary immune response. Immune memory provides the concepts to represent cases to deal with disturbances in a more generic way, and immune secondary response mechanisms guide the design of a CBR system to monitor traffic and control disturbances. Second, a new learning algorithm for the creation of the case-base combining simulation-optimisation, condensed nearest neighbour algorithm and a rule-based system are developed. Third, the performance of the suggested TSCS is assessed by benchmarking it against two standard control strategies from the literature, namely fixed-time traffic signal control and the longest queue first-maximal weight matching algorithm. The suggested TSCS is implemented in Python and applied on an intersection simulated using VISSIM, a state-of-the-art traffic simulation software. The results show that the suggested TSCS is able to handle different traffic scenarios with competitive performance, and that it is recommended for extreme situations involving blocked approaches and high traffic flow.
This is a preview of subscription content, log in via an institution to check access.
Reproduced with permission from De Castro and Von Zuben (1999)
Similar content being viewed by others
References
Ahmad A, Arshad R, Mahmud SA, Khan GM, Al-Raweshidy HS (2014) Earliest-deadline-based scheduling to reduce urban traffic congestion. IEEE Trans Intell Transp Syst 15(4):1510–1526. https://doi.org/10.1109/TITS.2014.2300693
Althoff K-D, Branting L, Bergmann R (1999) Case-based reasoning research and development. Springer, Berlin, London
Angulo E, Romero FP, García R, Serrano-Guerrero J, Olivas JA (2011) An adaptive approach to enhanced traffic signal optimization by using soft-computing techniques. Expert Syst Appl 38(3):2235–2247. https://doi.org/10.1016/j.eswa.2010.08.011
Araghi S, Khosravi A, Creighton D (2015) A review on computational intelligence methods for controlling traffic signal timing. Expert Syst Appl 42(3):1538–1550. https://doi.org/10.1016/j.eswa.2014.09.003
Bellemans T, Schutter B, De Moor B (2002) Model predictive control with repeated model fitting for ramp metering. In: Proceedings of the IEEE 5th international conference on intelligent transportation systems, vol 19, pp 236–241. https://doi.org/10.1109/ITSC.2002.1041221
Boillot F, Blosseville JM, Lesort JB, Motyka V, Papageorgiou M, Sellam S (1992) Optimal signal control of urban traffic networks. In: 6th IEE international conference on road traffic monitoring and control, IET. http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=363749
Bouhana A, Fekih A, Abed M, Chabchoub H (2013) An integrated case-based reasoning approach for personalized itinerary search in multimodal transportation systems. Transp Res C Emerg Technol 31:30–50. https://doi.org/10.1016/j.trc.2013.02.014
Chang ECP, Lei JCK, Messer CJ (1988) Arterial signal timing optimization using PASSER-II-87. ITE J 467:27–31
Chen L-W, Sharma P, Tseng Y-C (2013) Dynamic traffic control with fairness and throughput optimization using vehicular communications. IEEE J Sel Areas Commun 31(9):504–512. https://doi.org/10.1109/JSAC.2013.SUP.0513045
Coomans D, Massart DL (1982) Alternative k-nearest neighbour rules in supervised pattern recognition. Anal Chim Acta 138:167–176. https://doi.org/10.1016/S0003-2670(01)85299-5
Darmoul S, Elkosantini S (2014) Artificial immunity to control disturbances in public transportation systems: concepts, mechanisms and a prototype implementation of a knowledge based decision support system. Knowl Based Syst. https://doi.org/10.1016/j.knosys.2014.02.022
De Castro LN, Von Zuben FJ (1999) Artificial immune systems: part 1—basic theory and applications, vol 19. Springer. http://eva.evannai.inf.uc3m.es/docencia/doctorado/cib/documentacion/OverviewIS.pdf
De Castro LN, Timmis J (2002) Artificial immune systems: a new computational intelligence approach. Springer, London
De Schutter B, Hoogendoorn SP, Schuurman H, Stramigioli S (2003) A multi-agent case-based traffic control scenario evaluation system. In: Proceedings of the 2003 IEEE international conference on intelligent transportation systems, vol 1. IEEE, pp 678–683. https://doi.org/10.1109/ITSC.2003.1252037
Diala D, Sid-Ali A, Abderrahman EM, Habib C (2012) A dynamic multi-criteria aid for process driving using case-based reasoning. J Decis Syst 18:459–484
Elkosantini S, Mnif S, Chabchoub H (2011a) A system for the traffic control in signposted junctions. In: Proceedings of the 2011 IEEE symposium on computational intelligence in vehicles and transportation systems (CIVTS). IEEE, pp 52–58. https://doi.org/10.1109/CIVTS.2011.5949528
Elkosantini S, Mnif S, Chabchoub H (2011b) An urban traffic controller for signposted road-rail intersections. In: 2011 4th international conference on logistics. IEEE, pp 13–18. https://doi.org/10.1109/LOGISTIQUA.2011.5939396
Fellendorf M, Vortisch P (2010) Microscopic traffic flow simulator VISSIM. In: Barceló J (ed) Fundamentals of traffic simulation. Springer, New York, pp 63–93. https://doi.org/10.1007/978-1-4419-6142-6
Guo G, Wang H, Bell D, Bi Y, Greer K (2003) KNN model-based approach in classification. In: Meersman R, Tari Z, Schmidt DC (eds) On the move to meaningful internet systems 2003: CoopIS, DOA, and ODBASE. Springer, Berlin, pp 986–996. https://doi.org/10.1007/978-3-540-39964-3_62
Henry JJ, Farges J-L, Tuffal J (1984) The PRODYN real time traffic algorithm. In: IFAC/IFIP/IFORS conference on control in transportation systems. Baden-Baden, Germany, pp 305–310. http://trid.trb.org/view.aspx?id=339694
Hofmeyr SA (2001) An interpretative introduction to the immune system. In: Segel LA, Cohen IR (eds) Design principles for the immune system and other distributed autonomous systems. Oxford University Press, New York, pp 3–28
Karim A, Adeli H (2003) CBR model for freeway work zone traffic management. J Transp Eng. https://doi.org/10.1061/(ASCE)0733-947X(2003)129:2(134)
Kosonen I (2003) Multi-agent fuzzy signal control based on real-time simulation. Transp Res C Emerg Technol 11(5):389–403. https://doi.org/10.1016/S0968-090X(03)00032-9
Labreuche C (2003) The Choquet integral for the aggregation of interval scales in multicriteria decision making. Fuzzy Sets Syst 137(1):11–26. https://doi.org/10.1016/S0165-0114(02)00429-3
Leake DB, Wilson DC (2000) Remembering why to remember: performance-guided case-base maintenance (pp. 161–172). Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44527-7_15
Li J-Q (2011) Discretization modeling, integer programming formulations and dynamic programming algorithms for robust traffic signal timing. Transp Res C Emerg Technol 19(4):708–719. https://doi.org/10.1016/j.trc.2010.12.009
Little JDC, Kelson MD, Gartner NM (1981) MAXBAND: a program for setting signals on arteries and triangular networks. In: 60th annual meeting of the transportation research board, pp 40–46. Washington District of Columbia, United States: Transportation Research Board. http://trid.trb.org/view.aspx?id=172891
Luk JYK (1984). Two traffic-responsive area traffic control methods: scat and scoot. Traffic Eng Control 25(1). http://trid.trb.org/view.aspx?id=203568
Marichal J-L (2004) Tolerant or intolerant character of interacting criteria in aggregation by the Choquet integral. Eur J Oper Res 155(3):771–791. https://doi.org/10.1016/S0377-2217(02)00885-8
Mirchandani P, Head L (2001) A real-time traffic signal control system: architecture, algorithms, and analysis. Transp Res C Emerg Technol 9(6):415–432. https://doi.org/10.1016/S0968-090X(00)00047-4
Moalla D, Elkosantini S, Darmoul S (2013) An artificial immune network to control traffic at a single intersection. In: Proceedings of the fifth international conference on industrial engineering and systems management, IESM 2013
Murty MN, Devi VS (eds) (2011) Nearest neighbour based classifiers. In: Pattern recognition. Springer, London, pp 48–85. https://doi.org/10.1007/978-0-85729-495-1
Negi P (2006) Artificial immune system based urban traffic control. Texas A&M University. http://oaktrust.library.tamu.edu/bitstream/handle/1969.1/5764/etd-tamu-2006A-MEEN-Negi.pdf
Perelson A, Weisbuch G (1997) Immunology for physicists. Rev Mod Phys 69(4):1219–1268. https://doi.org/10.1103/RevModPhys.69.1219
PTV G (2015) VISSIM simulation software. Retrieved 28 Sept 2015. http://vision-traffic.ptvgroup.com/en-uk/home/
Raza A, Fernandez BR (2015) Immuno-inspired robotic applications: a review. Appl Soft Comput 37:490–505. https://doi.org/10.1016/j.asoc.2015.08.050
Robertson DI (1969) “TRANSYT” method for area traffic control. Traffic Eng Control 11(6):276–281. http://trid.trb.org/view.aspx?id=116630
Robertson DI, Bretherton RD (1991) Optimizing networks of traffic signals in real time—the SCOOT method. IEEE Trans Veh Technol 40(1):11–15. https://doi.org/10.1109/25.69966
Sadek AW, Smith BL, Demetsky MJ (2001) A prototype case-based reasoning system for real-time freeway traffic routing. Transp Res C Emerg Technol 9(5):353–380. https://doi.org/10.1016/S0968-090X(00)00046-2
Smyth B, McKenna E (1999) Building compact competent case-bases. In: Althoff K-D, Bergmann R, Branting LK (eds) Case-based reasoning research and development, vol 1650. Springer, Berlin, pp 329–342. https://doi.org/10.1007/3-540-48508-2
Stevanovic A (2010) Adaptive traffic control systems: domestic and foreign state of practice. Transportation research Board. http://trid.trb.org/view.aspx?id=916104
Tahilyani S, Darbari M, Shukla PK (2013) Soft computing approaches in traffic control systems: a review. AASRI Procedia 4:206–211. https://doi.org/10.1016/j.aasri.2013.10.032
Trabelsi B, Elkosantini S, Darmoul S (2012) Traffic control at intersections using artificial immune system approach. In: 9th international conference of modeling, optimization and simulation—MOSIM’12. Bordeaux, France
Traffic Signal Control Systems (1997) In: Advanced transportation management technologies. United States Department of Transportation, National Transportation Library, pp 1–28. http://ntl.bts.gov/lib/jpodocs/edldocs1/13480/ch3.pdf
Ulutaş BH, Kulturel-Konak S (2011) A review of clonal selection algorithm and its applications. Artif Intell Rev 36(2):117–138. https://doi.org/10.1007/s10462-011-9206-1
Wallace CE, Courage KG, Reaves DP, Schoene GW, Euler GW (1984) TRANSYT-7F user’s manual. http://trid.trb.org/view.aspx?id=213009
Wen W (2008) A dynamic and automatic traffic light control expert system for solving the road congestion problem. Expert Syst Appl 34(4):2370–2381. https://doi.org/10.1016/j.eswa.2007.03.007
Wong Y, Woon W (2008) An iterative approach to enhanced traffic signal optimization. Expert Syst Appl 34(4):2885–2890. https://doi.org/10.1016/j.eswa.2007.05.007
Wu J, Abbas-Turki A, El Moudni A (2011) Cooperative driving: an ant colony system for autonomous intersection management. Appl Intell 37(2):207–222. https://doi.org/10.1007/s10489-011-0322-z
Wunderlich R, Elhanany I, Urbanik T (2008) A novel signal-scheduling algorithm with quality-of-service provisioning for an isolated intersection. IEEE Trans Intell Transp Syst 9(3):536–547. https://doi.org/10.1109/TITS.2008.928266
Wunderlich R, Elhanany I, Urbanik T (2007) A stable longest queue first signal scheduling algorithm for an isolated intersection. In: 2007 IEEE international conference on vehicular electronics and safety. IEEE, pp 1–6. https://doi.org/10.1109/ICVES.2007.4456393
Yager RR (2004) Generalized OWA aggregation operators. Fuzzy Optim Decis Mak 3(1):93–107. https://doi.org/10.1023/B:FODM.0000013074.68765.97
Yin Y (2008) Robust optimal traffic signal timing. Transp Res B Methodol 42(10):911–924. https://doi.org/10.1016/j.trb.2008.03.005
Acknowledgements
This project was funded by the Deanship of Scientific Research at King Saud University through research Group No. (RG-1438-056).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Louati, A., Elkosantini, S., Darmoul, S. et al. An immune memory inspired case-based reasoning system to control interrupted flow at a signalized intersection. Artif Intell Rev 52, 2099–2129 (2019). https://doi.org/10.1007/s10462-017-9604-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10462-017-9604-0