Federal Highway Administration Vehicle Classification from Video Data and a Disaggregation Model
Publication: Journal of Transportation Engineering
Volume 131, Issue 9
Abstract
To assess highway system performance, states are required to submit compositional traffic count reports to the Federal Highway Administration (FHWA). A methodology was developed for obtaining compositional vehicle counts from low-cost portable video technology. Autoscope, an advanced video camera with machine vision processing, was used to capture, process, and store compositional counts based on vehicle length. A maximum of five length-based vehicle classes can be differentiated from video; therefore a methodology was developed that generates the FHWA 13-category vehicle classes. A disaggregation process, typically used in stochastic hydrology, is employed. Results from the disaggregation model are compared with actual FHWA classification data obtained from axle counters. It was observed that less than 1% of the vehicles were not included in the model output and 3.43% were misclassified. In addition, 95 and 99% confidence intervals calculated by the disaggregation model included 92.3 and 100% of the actual axle counter data.
Get full access to this article
View all available purchase options and get full access to this article.
References
Abdelbaki, H. M., Hussain, K., and Gelenbe, E. (2001). “A laser intensity image based automatic vehicle classification system.” Proc., 2001 IEEE Intelligent Transportation Systems Conf., Institute of Electrical and Electronics Engineers, Inc., New York, 460–465.
Bras, R. L., and Rodriguez-Iturbe, I. (1993). Random functions and hydrology, Dover, New York, 559.
Dalgleish, M. J. (1994). “Vehicle detection for advanced transportation telematics.” Proc., 7th Int. Conf. on Road Traffic Monitoring and Control, Institution of Electrical Engineers, London, 164–167.
Econolite. (2003). “Data sheet.” Econolite, ⟨www.econolite.com⟩, accessed January 10, 2005.
Gupte, S., Masoud, O., Martin, R. F. K., and Papanikolopoulos, N. P. (2002). “Detection and classification of vehicles.” IEEE Intell. transp. syst., trans., 3(1), 37–47.
Hallenbeck, M., and Weinblatt, H. (2004). “Equipment for collecting traffic load data.” NCHRP Rep. 509, Transportation Research Board, Washington, D.C., 58.
Highway performance monitoring system field manual (Highway). (2000). United States Department of Transportation, Federal Highway Administration.
Panda, D. P., Jacobson, R. D., Bernard, B. E., and Michalopoulos, P. G. (1996). “Image sensing system technology advancement for adaptive traffic management.” Proc., 3rd World Congress on Intelligent Transportation Systems, Intelligent Transportation Society of America, Washington, D.C., 5.
Peng, S., and Harlow, C. A. (1996). “System for vehicle classification from range imagery.” Proc., 28th IEEE Southeastern Symposium on System Theory, Institute of Electrical and Electronics Engineers, Inc., New York, 327–330.
Skszek, S. L. (2001). “State-of-the-art’ report on non-traditional traffic counting methods.” Rep. FHWA-AZ-01-503, Arizona Department of Transportation, National Technical Information Service, Springfield, Va., 78.
Traffic monitoring guide (Traffic). (2001). United States Department of Transportation, Federal Highway Administration, Office of Highway Policy Information, Washington, D.C.
Tropartz, S., Hoerber, E., and Gruener, K. (1999). “Experiences and results from vehicle classification using infrared overhead laser sensors at toll plazas in New York City.” Proc., 1999 Int. Conf. on Intelligent Transportation Systems, IEEE/IEEJ/JSAI, Institute of Electrical and Electronics Engineers, Inc., New York, 686–691.
Valencia, D., and Schaake, J. C., Jr. (1973). “Disaggregation process in stochastic hydrology.” Water Resour. Res., 9(3), 580–585.
Wang, N., and Smith, B. (2004). “VMT estimation associated with ITS data and maintenance of loop detectors.” Research Rep. UVACTS-15-0-88, Univ. of Virginia, Charlottesville, Va., 78.
Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 131 • Issue 9 • September 2005
Pages: 689 - 698
Copyright
© 2005 ASCE.
History
Received: May 28, 2004
Accepted: Nov 12, 2004
Published online: Sep 1, 2005
Published in print: Sep 2005
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.