Abstract
Coordination of traffic signal timing systems has significant impacts on traffic congestion, waiting time, risks of accidents, and unnecessary fuel consumption. Actually, systems of traffic light’s programming involve complex calculations especially to tackle problematic situations in real time. Another way of doing is to manage traffic flow by traffic officers. Despite the limitation of short-term retention of human brain to few elements, human being can make decisions in case of system malfunction or during special events. The human strategy as that of the traffic officers is simple and is based on common sense. This paper explains how to implement this strategy and gives some results obtained. The simulation is performed with the open-source traffic simulation software, simulation of urban mobility (SUMO). The preliminary simulation results are promising for the continuation of this research. The observation of patterns could bring to propose an intelligent system more efficient that reuses similar cases to save time.
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Notes
- 1.
Founded in 1930, ITE is a community of transportation professionals including, but not limited to transportation engineers, transportation planners, consultants, educators, and a network of nearly 17,000 members, working in more than 90 countries, http://www.ite.org/aboutite/, accessed March 25, 2015.
- 2.
SUMO is a free and open traffic simulation suite which is available since 2001. SUMO allows modeling of intermodal traffic systems including road vehicles, public transport, and pedestrians. http://www.dlr.de/ts/en/desktopdefault.aspx/tabid-9883/16931_read-41000/, accessed March 25, 2015
- 3.
DLR is the national aeronautics and space research center of the Federal Republic of Germany. Its extensive research and development work in aeronautics, space, energy, transport, and security is integrated into national and international cooperative ventures. DLR has approximately 8000 employees. http://www.dlr.de/dlr/en/desktopdefault.aspx/tabid-10002/#/DLR/Start/About, accessed March 25, 2015
- 4.
Tutorials/Hello Sumo, Hello Sumo—Introduction, http://sumo.dlr.de/wiki/Tutorials/Hello_Sumo, accessed March 25, 2015.
- 5.
OpenStreetMap (OSM) is a collaborative project to create a free editable map of the world, https://en.wikipedia.org/wiki/OpenStreetMap, accessed March 25, 2015.
- 6.
JOSM is an extensible editor for OpenStreetMap written in Java 7, https://josm.openstreetmap.de/, accessed March 25, 2015.
References
Hossain S, Kattan L, Radmanesh A (2011) Responsive signal control for non-recurrent traffic congestion on an arterial. In: TRB 90th annual meeting, Washington
Institute of Transportation Engineers, Traffic Signal Timing Manual, Washington (2009)
Kofod-Petersen A, Andersen OJ, Aamodt A (2014) Case-based reasoning for improving traffic flow in urban intersections, case-based reasoning research and development. Lecture Notes in Computer Science, vol 8765, pp 215–229
Krajzewicz D, Brockfeld E, Mikat J, Ringel J, Rössel C, Tuchscheerer W, Wagner P, Wösler R (2005) Simulation of modern traffic lights control systems using the open source traffic simulation SUMO. In: Proceedings of the 3rd industrial simulation conference 2005, Berlin, Germany, pp 299–302
Miller George A (1956) The magical number seven plus or minus two: some limits on our capacity for processing information. Harvard University-Psychological Review, pp 81–97
Pignataro LJ (1973) Traffic engineering—Theory and practice. Prentice-Hall, New Jersey, pp 180–182
Sadek A, Spencer M, Spencer M (2003) Wael El–Dessouki: case-based reasoning for assessing intelligent transportation systems benefits, computer-aides civil and infrastructure engineering. Blackwell Publishing, USA
Tarnoff Philip J, Ordonez J (2004) Signal timing practices and procedures, state of the practice. University of Maryland, Center for Advanced Transportation Technology, Maryland
Wannige CT, Sonnadara DUJ (2009) Adaptive neuro-fuzzy traffic signal control for multiple junctions. In: International conference on industrial and information systems (ICIIS), pp 262–267
Yang W, Zhang L, He Z, Yang Y, Fang Y (2012) Urban traffic signal two-stage combination fuzzy control and Paramics simulation. IEEE explore Digital Librar, pp 771–775
Zubillaga D, Cruz G, Aguilar LD, Zapotécatl J, Fernández N, Aguilar J, Rosenblueth DA, Gershenson C (2014) Measuring the complexity of self-organizing traffic lights. Entropy 2384–2407
Acknowledgements
We wish to thank the German Aerospace Center (DLR) of Berlin and officials of SUMO for their continued support, especially Jakob Erdmann and Michael Behrisch who make it a duty to respond quickly and clearly to user requests. We also want to thank Bruno Rémy of OpenStreetMap Quebec group for his help and valuable advice. We finally thank the Department of Computer Science and Software Engineering of the Faculty of Science and Engineering at Laval University for financial support under a merit scholarship given to this project.
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Vaudrin, F., Capus, L. (2019). Improving Traffic Lights System Management by Translating Decisions of Traffic Officer. In: Behrisch, M., Weber, M. (eds) Simulating Urban Traffic Scenarios. Lecture Notes in Mobility. Springer, Cham. https://doi.org/10.1007/978-3-319-33616-9_9
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DOI: https://doi.org/10.1007/978-3-319-33616-9_9
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