Freeway Recurrent Bottleneck Identification Algorithms Considering Detector Data Quality Issues
Publication: Journal of Transportation Engineering
Volume 138, Issue 10
Abstract
Computer algorithms used to identify recurrent freeway bottlenecks have been studied since the deployment of loop detecting systems. Such algorithms automatically analyze the archived loop detector data and identify potential recurrent bottlenecks and their characteristics, such as location, time of day, and activation rate, for further investigation. In a highway congestion mitigation project, such algorithms can save time and resources for the initial screening of bottlenecks over a large freeway network. These algorithms include rule-based, contour-map-based, and simulation-based methods. However, existing methods require loop detector data with high accuracy and consistency, which is difficult to achieve in prevailing loop detecting systems. This paper proposes a new bottleneck identification algorithm with strong error and noise tolerance. Several simple denoising methods to improve the error resistance of existing algorithms are also proposed. Using statistical error analysis methods, the proposed algorithm and the denoising methods were calibrated and evaluated using field data collected from two distinct freeway corridors (US 12/14 and I-894) in the U.S. state of Wisconsin. Ground truth data for this study come from the manual inspection of 287,055 traffic video snapshots in the course of a month. In the evaluation tests, the proposed algorithm can produce quality congestion identification results with fewer false alarms than the existing algorithms, especially when identifying severe bottleneck congestion.
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Acknowledgments
Loop detector data for this paper was obtained from the WisTransPortal system (TOPS 2011) at the University of Wisconsin-Madison Traffic Operations and Safety (TOPS) Lab. Real-time video snapshots were obtained from the Wisconsin 511 Traveler Information system. The paper was also partly supported by the National High-Technology Research and Development (863) Program of China (Grant Nos. 2011AA110404). The authors would like to thank the anonymous reviewers for their insightful comments and suggestions.
References
Ban, X., Chu, L., and Benouar, H. (2007). “Bottleneck identification and calibration for corridor management planning.”, Transportation Research Board, Washington, DC, 40–53.
Banks, J. H. (1990). “Flow processes at a freeway bottleneck.”, Transportation Research Board, Washington, DC, 20–28.
Banks, J. H. (1991). “Two-capacity phenomenon at freeway bottlenecks: A basis for ramp metering.”, Transportation Research Board, Washington, DC, 83–90.
Cambridge Systematics and TX Transportation Institute. (2005). “Traffic congestion and reliability: Trends and advanced strategies for congestion mitigation.” 〈http://www.ops.fhwa.dot.gov/congestion_report/〉 (Jan. 4, 2011).
Cassidy, M. J., and Bertini, R. L. (1999). “Some traffic features at freeway bottlenecks.” Transp. Res. Part B, 33(1), 25–42.
Chen, C., Skabardonis, A., and Varaiya, P. (2004). “Systematic identification of freeway bottlenecks.”, Transportation Research Board, Washington, DC, 46–52.
Das, S., and Levinson, D. (2004). “Queuing and statistical analysis of freeway bottleneck.” J. Transp. Eng., 130(6), 787–795.
Gomes, G. (2009). “Evaluate IST-222 loop detector system.”. 〈http://www.path.berkeley.edu/PATH/Publications/PDF/PRR/2009/PRR-2009-17.pdf〉 (Oct. 2011).
Greenshields, B. D., Bibbins, J. R., Channing, W. S., and Miller, H. H. (1935). “A study of traffic capacity.” Highway Res. Board Proc., 14(1), 448–477.
Halkias, B, Kopelias, P., Papandreou, K., Politou, A., Prevedouros, P., and Skabardonis, A. (2007). “Freeway bottleneck simulation, implementation, and evaluation.”, Transportation Research Board, Washington, DC, 84–93.
Hall, F. L., Allen, B. L., and Gunter, M. A. (1986). “Empirical analysis of freeway flow-density relationships.” Transp. Res. Part A, 20A(3), 197–210.
Jin, J. (2009). “Automatic incident detection based on fundamental diagrams of traffic flow.” Ph.D. dissertation. Univ. of Wisconsin Madison, Madison, WI, 2009.
Jin, J., and Ran, B. (2009). “Automatic incident detection based on fundamental diagrams of traffic flow.”, Transportation Research Board, Washington, DC, 65–75.
Kerner, B. S. (2004). The physics of traffic: Empirical freeway pattern features, engineering applications and theory, Springer, Berlin.
Koshi, M., Iwasaki, M., and Okhura, I. (1983). “Some findings and an overview on vehicular flow characteristics.” Proc. 8th Int. Symp. on Transportation and Traffic Flow Theory, University of Toronto Press, Toronto, 403–426.
Mitchell, M. T. (1997). “Machine learning.” McGraw-Hill, New York.
Neudorff, L. G., Randall, J. E., Reiss, R., and Gordon, R. (2003). “Freeway management and operations handbook.”, 〈http://ops.fhwa.dot.gov/freewaymgmt/publications/frwy_mgmt_handbook/〉 (Jan. 4, 2011).
Ringert, J., and Urbanik, T. II (1993). “Study of freeway bottlenecks in texas.”, Transportation Research Board, Washington, DC, 31–41.
Traffic Operations and Safety Laboratory (TOPS). (2011). “The WisTransPortal project.” 〈http://transportal.cee.wisc.edu/〉 (Jan. 4, 2010).
Transportation Research Board. (2000). Highway capacity manual, 4th Ed., Washington, DC.
Tufte, K.A., Ahn, S., Bertini, R., Auffray, B., and Rucker, J. (2007). “Toward the systematic improvement of data quality in the Portland, Oregon Regional Transportation Archive Listing (PORTAL).” Proc. Trans. Res. Board, 7(1561), 1–11.
Turner, S. (2007). “Quality control procedures for archived operations traffic data: Synthesis of practice and recommendations.” 〈http://www.fhwa.dot.gov/policy/ohpi/travel/qc/index.cfm〉 (Jan. 4, 2011).
Wisconsin Dept. of Transportation (WisDOT). (2011). “Wisconsin department of transportation traveler information.” 〈http://www.511wi.gov/Web/〉 (Jan. 4, 2011).
Zhang, L., and Levinson, D. (2004). “Some properties of flows at freeway bottlenecks.”, Transportation Research Board, Washington, DC, 122–131.
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© 2012 American Society of Civil Engineers.
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Received: Mar 10, 2011
Accepted: Mar 6, 2012
Published online: Mar 8, 2012
Published in print: Oct 1, 2012
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