TECHNICAL PAPERS
Jul 19, 2010

Methodology to Identify Optimal Placement of Point Detectors for Travel Time Estimation

Publication: Journal of Transportation Engineering
Volume 137, Issue 3

Abstract

The purpose of this research was to develop a decision support methodology to identify the optimal locations of a finite set of point detectors on a freeway corridor to minimize the error in travel time estimation. The developed methodology, consisting of floating vehicle-based global-positioning system data collection, and use of a heuristic search technique (genetic algorithm)–based search tool, was shown to be effective in determining preferred detector locations for the chosen objective. Case studies of freeway sections in two Virginia regions were conducted to demonstrate the utility of the developed methodology. The writers found that the placement of detectors for the development of accurate travel time estimates will vary by location on the basis of specific conditions. Arbitrary, evenly spaced detectors do not necessarily result in accurate travel time estimates. With carefully placed detectors that are well maintained, travel time estimates can be derived with an acceptable level of accuracy from point detection, under incident-free travel conditions.

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References

Bartin, B., Ozbay, K., and Iyigun, C. A. (2007). “Clustering based methodology for determining the optimal roadway configuration of detectors for travel time estimation.” Transportation Research Record, 2000, 98–105.
Chan, S., and Lam, H. K. (2002). “Optimal speed detector density for the network with travel time information.” Transp. Res. Part A, 36, 203–223.
Coello, C. A. (1999). “A survey of constraint handling techniques used with evolutionary algorithms.” Technical Rep. Lania-RI-99-04, Laboratorio Nacional de Informatica Avanzada, Veracruz, Mexico.
Coifman, B., and Cassidy, M. (2002). “Vehicle reidentification and travel time measurement on congested freeways.” Transp. Res. Part A, 36(10), 899–917.
Edara, P., Guo, J., Smith, B., and McGhee, C. (2008). “Optimal placement of point detectors on Virginia’s freeways: Case studies of Northern Virginia and Richmond.” VTRC 08-CR3, Virginia Transportation Research Council, Charlottesville, VA.
Ehlert, A., Bell, M., and Grosso, S. (2006). “The optimization of traffic count locations in road networks.” Transp. Res. Part B (Methodological), 40, 460–479.
Fujito, I., Margiotta, R., Huang, W., and Perez, W. A. (2006). “The effect of sensor spacing on performance measure calculations.” Proc., 85th Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, D.C.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning, Addison-Wesley, Reading, MA.
Liepins, G. E., and Vose, M. D. (1990). “Representational issues in genetic optimization.” J. Exper. Theoret. Artif. Intell., 2(2), 101–115.
Liu, Y., Lai, X., and Chang, G.-L. (2006). “Detector placement strategies for freeway travel time estimation.” Proc., IEEE Intelligent Transportation Systems Conference, Toronto, Canada, 499–504.
Michalewicz, Z. (1995). Genetic algorithms + data structures = evolution programs, Springer-Verlag, Berlin.
Monsere, C., Breakstone, A., Bertini, R., Deeter, D., and McGill, G. (2006). “Validating dynamic message sign freeway travel time messages with ground truth geospatial data.” Transportation Research Record, 1959, 19–27.
Ogle, J., Guensler, R., Bachman, W., Koutsak, M., and Wolf, J. (2002). “Accuracy of global positioning system for determining driver performance parameters.” Transportation Research Record, 1818, 12–21.
Oh, S., Ran, B., and Choi, K. (2003). “Optimal detector location for estimating link travel speed in urban arterial roads.” Proc., 82nd Annual Meeting, Transportation Research Board, Washington, DC.
Orvosh, D., and Davis, L. (1993). “Shall we repair? Genetic algorithms, combinatorial optimization and feasibility constraints.” Proc., Fifth Int. Conf. on Genetic Algorithms, Morgan Kauffman Publishers, San Mateo, CA.
Quiroga, C. (2000). “Performance measures and data requirements for congestion management systems.” Transp. Res. Part C, 8, 287–306.
Quiroga, C., and Bullock, D. (1998). “Travel time studies with global positioning and geographic information systems: an integrated methodology.” Transp. Res. Part C, 6, 101–127.
Pan, C., Lu, J., Wang, D., and Ran, B. (2007). “Data collection based on global positioning system for travel time and delay for arterial roadway network.” Transportation Research Record, 2024, 35–43.
ReVelle, C. S., and Eiselt, H. A. (2005). “Location analysis: A synthesis and survey.” Eur. J. Oper. Res., 165(1), 1–19.
Sherali, H. D., Desai, J., Rakha, H. A., and El-Shawarby, I. (2006). “Discrete optimization approach for locating automatic vehicle identification readers for the provision of roadway travel times.” Transp. Res. Part B (Methodological), 40, 857–871.
Sisiopiku, V. P., Rouphail, N. M., and Santiago, A. (1994). “Analysis of correlation between arterial travel time and detector data from simulation and field studies.” Transportation Research Record, 1457, 166–173.
Sun, C., Ritchie, S., Tsai, K., and Jayakrishnan, R. (1999). “Use of vehicle signature analysis and lexicographic optimization for vehicle reidentification on freeways.” Transp. Res. Part C, 7, 167–185.
Teodorović, D., Van Aerde, M., Zhu, F., and Dion, F. (2002). “Genetic algorithms approach to the problem of the automated vehicle identification equipment locations.” J. Adv. Transp., 36, 1–21.
Thomas, G. (1999). “The relationship between detector location and travel characteristics on arterial streets.” ITE J., 169, 36–42.
Turner, S. M., Eisele, W. L., Benz, R. J., and Holdene, D. J. (1998). “Travel time data collection handbook.” FHWA-PL-98-035, Federal Highway Administration, Washington, DC.
Williams, B. M., and Guin, A. (2007). “Traffic management center use of incident detection algorithms: Findings of a nationwide survey.” IEEE Trans. Intell. Transp. Syst., 8(2), 351–358.
Wolshon, B., and Hatipkarasulu, Y. (2000). “Results of car following analyses using global positioning system.” J. Transp. Eng., 126(4), 324–331.
Yang, H., and Zhou, J. (1998). “Optimal traffic counting locations for origin-destination matrix estimation.” Transp. Res. Part B (Methodological), 32, 109–126.

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Information

Published In

Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 137Issue 3March 2011
Pages: 155 - 173

History

Received: Apr 28, 2009
Accepted: Jun 23, 2010
Published online: Jul 19, 2010
Published in print: Mar 1, 2011

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Authors

Affiliations

Praveen Edara
Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Missouri, E3502 Lafferre Hall, Columbia, MO 65211.
Brian Smith, M.ASCE
Associate Professor of Civil Engineering, Center for Transportation Studies, Univ. of Virginia, Charlottesville, VA 22911.
Jianhua Guo
Research Associate, Center for Transportation Studies, Univ. of Virginia, Charlottesville, VA 22911.
Simona Babiceanu
Software Engineer, Center for Transportation Studies, Univ. of Virginia, Charlottesville, VA 22911.
Catherine McGhee
Acting Associate Director, Virginia Transportation Research Council, Charlottesville, VA 22911.

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