Comparative Assessment of Traffic Control Parameters within an UTC-Distributed System
Publication: Journal of Transportation Engineering
Volume 140, Issue 3
Abstract
Modern urban traffic control (UTC) systems are a key element of intelligent transportation systems (ITS). They represent the answer to the need of increased road network capacity and provide important benefits by reducing delays, stops, and travel times. Traffic parameters, measured or computed in the field, enable an UTC system to operate in a fully adaptive mode. This way, local decision units are able to follow variations in the traffic behavior and produce optimal signaling plans. Therefore, it is highly important to have this information within a distributed approach, where neighboring junctions cooperate to produce optimal control strategies. This paper aims to demonstrate the importance of different traffic parameters and how their absence affects the signaling plans and the accuracy of traffic analyses. The present study uses a local adaptation simulation option embedded in the Synchro 7 modeling tool to assess and classify these parameters according to their impact on performing efficient traffic control; the results can be deployed in any real UTC distributed system to ensure that critical information is successfully exchanged between its local decision units to maintain a fully adaptive operation.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The work has been funded by the Sectorial Operational Program Human Resources Development 2007–2013 of the Romanian Ministry of Labor, Family and Social Protection through the Financial Agreement POSDRU/107/1.5/S/76813.
References
Binning, J. C., Crabtree, M., and Burtenshaw, G. (2003). Transyt 12 user guide, Transport Research Laboratory, U.K.
Camponogara, E., Scherer, H. F., and Moura, L. V. (2009). “Distributed optimization for predictive control with input and state constraints: Preliminary theory and application to urban traffic control.” Proc., 2009 IEEE Int. Conf. on Systems, Man, and Cybernetics.
Dunn Engineering Associates /Siemens Intelligent Transportation Systems (ITS). (2005). Traffic control systems handbook, Washington, PA.
Gu, J., Qu, Y., and Zhang, Z. (2009). “Data sharing and exchanging method for urban traffic control system based on XML.” Int. Conf. on Measuring Technology and Mechatronics Automation, College of Transportation, Ludong Univ., Yantai, China.
Hall, F. L. (2001). “Traffic flow theory—A state-of-the-art report.” Chapter 6, Traffic stream characteristics, Committee on Traffic Flow Theory and Characteristics (AHB45).
Hunt, P. B., Robertson, D. I., Bretherton, R. D., and Royle, M. C. (1982). “The SCOOT on-line traffic signal optimization technique.” Traffic Eng. Control, 190–199.
Kaparias, I., Zavitsas, K., and Bell, M. G. H. (2010). “State-of-the-art of urban traffic management policies and technologies v.2.” 7th Framework Programme, Theme 7: TRANSPORT (including AERONAUTICS), Coordination of Network Descriptors for Urban Intelligent Transport Systems (CONDUITS), Imperial College London, London, U.K.
Klein, L. A., Mills, M. K., and Gibson, D. R. P. (2006). Traffic detector handbook, 3rd Ed., Vol. I, U.S. Dept. of Transportation, Federal Highway Administration, Washington, DC.
KonSULT. (2005). “The knowledgebase on sustainable urban land use and transport.” 〈http://www.konsult.leeds.ac.uk/〉 (Dec. 2012).
Koonce, P., et al. (2008). Traffic signal timing manual, U.S. Dept. of Transportation, Federal Highway Administration, Washington, DC.
Li, S. (2012). “A survey of urban traffic coordination controls in intelligent transportation systems.” IEEE Int. Conf. on Service Operations and Logistics, and Informatics (SOLI), Duke Univ., Durham, NC.
Lowrie, P. R. (1992). “SCATS—Sydney co-ordinated adaptive traffic system.” A traffic responsive method of controlling urban traffic, Roads and Traffic Authority, Sydney, Australia.
Lu, B., Xu, R., Hou, L., and Zhang, Z. (2011). “Signal control optimization for urban traffic against incident-induced congestion.” Chinese Control and Decision Conf. (CCDC), Dept of Autom., Tsinghua Univ., Beijing, China.
Mauro, V., and Di Taranto, D. (1990). “UTOPIA.” Control, Computers, Communications in Transportation: Selected Papers from the IFAC Symp., Pergamon Press, New York, 245–252.
McQueen, B., and McQueen, J. (1999). Intelligent transportation systems architectures, Artech House Publishers, Norwood, MA.
Minea, M., Grafu, F. D., and Surugiu, M. C. (2007a). Sisteme inteligente de transport—Aplicaţii (Intelligent Transportation Systems—Applications), Matrixrom, Bucharest, Romania (in Romanian).
Minea, M., Grafu, F. D., and Surugiu, M. C. (2007b). Telematică în transporturi—noţiuni fundamentale şi aplicaţii (Telematics in transports—basic concepts and applications), Matrixrom, Bucharest, Romania (in Romanian).
Minnesota Department of Transportation. (2009). MN/DOT traffic signal timing and coordination manual, Minneapolis.
Mizar Automazione S.p.A. Utopia. (2012). “Urban traffic control system architecture.” 〈http://www.citilabs.com/sites/default/files/files/3_Swarco.pdf〉 (Apr. 02, 2012).
Oregon State University. (2012). “Signal progression.” Kiewit Center for Infrastructure and Transportation 〈http://kiewit.oregonstate.edu/pdf/pw_sigprog.pdf〉 (Jun. 23, 2013).
Prikryl, J. (2006). “Overview of distributed decision-making for urban traffic control.” Proc., Abstracts of the 7th Int. Ph.D. Workshop on Interplay of Societal and Technical Decision-Making, Department of Adaptive Systems Institute of Information Theory and Automation Academy of Sciences of the Czech Republic, Prague, Czech Republic.
Robertson, D. I., and Bretherton, R. D. (1991). “Optimizing networks of traffic signals in real time—The SCOOT method.” IEEE Transactions on Vehicular Technology, 40(1), 11–15.
Schmidt, M. S. (2010). Adaptive traffic control systems in the United States, HDR Engineering.
Slager, G., and Milano, M. (2010). “Urban traffic control system using self-organization.” 13th Int. IEEE Annual Conf. on Intelligent Transportation Systems, IEEE, New York.
Trafficware Website. (2011). 〈http://www.trafficwareinc.com/〉 (Mar. 2011).
Transportation Research Board. (2010a). “Highway capacity manual.” National Academies of Science 〈http://hcm.trb.org/ch18/〉 (Feb. 12, 2012).
Transportation Research Board. (2010b). NCHRP synthesis 403—Adaptive traffic control systems: Domestic and foreign state of practice, Washington, DC.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 140 • Issue 3 • March 2014
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Apr 30, 2013
Accepted: Sep 24, 2013
Published online: Sep 26, 2013
Published in print: Mar 1, 2014
Discussion open until: May 6, 2014
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.