Identifying Large Truck Hot Spots Using Crash Counts and PDOEs
Publication: Journal of Transportation Engineering
Volume 137, Issue 1
Abstract
Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high-risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High-risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using property damage only equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large annual average daily traffic (AADTs), whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.
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Acknowledgments
This study was funded by the ADOT, Federal Highway Administration, and the Arizona State University. We thank the two anonymous reviewers who have helped improve this paper by providing valuable comments.
References
Analysis Division, Federal Motor Carrier Administration (FMCSA). (2009). “Large truck and bus crash facts.” Publication FMCSA-RRA-09-029, U.S. DOT, Washington, D.C.
Ardekani, S., Hauer, E., and Jamei, B. (1996). “Revised monograph on traffic flow theory.” Traffic impact models, N. H. Gartner, C. J. Messer, and A. K. Rathi, eds., Federal Highway Administration (FHWA), U.S. DOT, Washington, D.C.
Bauer, K. M., and Harwood, D. (1994). “Statistical models of at-grade intersection accidents-addendum.” Publication FHWA-RD-99-094, Federal Highway Administration, U.S. DOT, Washington, D.C.
Blincoe, L., et al. (2000). Economic impact of motor vehicle crashes, National Highway Traffic Safety Administration, NHTSA, Washington, D.C.
Blower, D., and Campbell, K. L. (2006). “Large truck crash causation study.” Publication FMCSA-RI-05-037, FMCSA, U.S. DOT, Washington, D.C.
Carson, J. L. (2007). “Large truck crashes in Texas: A predictive approach for identifying those at higher risk.” Rep. No. SWUTC/07/473700-00089-1, Texas Transportation Institute (TTI), College Station, Tex.
Chang, L., and Mannering, F. (1999). “Analysis of injury severity and vehicle occupancy in truck and non-truck involved accidents.” Accid. Anal Prev., 31(5), 579–592.
Cheng, W., and Washington, S. P. (2005). “Experimental evaluation of hotspot identification methods.” Accid. Anal Prev., 37(5), 870–881.
Golob, T. F., and Regan, A. C. (2004). “Truck-related crashes and traffic levels on urban freeways.” Proc., 83rd Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, D.C.
Hauer, E. (1997). Observational before-after studies in road safety, Pergamon, Tarrytown, N.Y.
Higle, J. L., and Hecht, M. B. (1989). “A comparison of techniques for the identification of hazardous locations.” Transp. Res. Rec., 1238, 10–19.
Hiselius, L. W. (2004). “Estimating the relationship between accident frequency and homogeneous and inhomogeneous traffic flows.” Accid. Anal Prev., 36(6), 985–992.
Joshua, S., and Garber, N. (1990). “Estimating truck accident rate and involvements using linear and poisson regression model.” Transportation Planning and Technology, 15, 41–58.
Khorashadi, A., Niemeier, D., Shankar, V., and Mannering, F. (2005). “Differences in rural and urban driver-injury severities in accidents involving large-trucks: An exploratory analysis.” Accid. Anal Prev., 37(5), 910–921.
Li, W., Carriquiry, A., Pawlovich, M., and Welch, T. (2008). “The choice of statistical models in road safety countermeasure effectiveness studies in Iowa.” Accid. Anal Prev., 40(4), 1531–1542.
Lord, D. (2006). “Modeling motor vehicles crashes using Poisson-gamma models: Examining the effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter.” Accid. Anal Prev., 38(4), 751–766.
Lord, D., Middleton, D., and Whitacre, J. (2005a). “Does separating trucks from other traffic improve safety?” Transp. Res. Rec., 1922, 156–166.
Lord, D., Washington, S. P., and Ivan, J. N. (2005b). “Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: Balancing statistical fit and theory.” Accid. Anal Prev., 37(1), 35–46.
Ma, J., Kockelman, K., and Damien, P. (2008). “A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods.” Accid. Anal Prev., 40(3), 964–975.
Miaou, S., and Lord, D. (2003). “Modeling traffic crash-flow relationships for intersections: Dispersion parameter, function form, and Bayes versus empirical Bayes methods.” Transp. Res. Rec., 1840, 31–40.
Miaou, S. P. (1994). “The relationship between truck accidents and geometric design of road sections: Poisson versus negative binomial regressions.” Accid. Anal Prev., 26(4), 471–482.
Miaou, S. P. (2005). “Bayesian ranking of sites for engineering safety improvements: Decision parameter, treatability concept, statistical criterion, and spatial dependence.” Accid. Anal Prev., 37(4), 699–720.
Miaou, S. P., Hu, P. S., Wright, T., Rathi, A. K., and Davis, S. C. (1992). “Relationships between truck accidents and highway geometric design: A Poisson regression approach.” Transp. Res. Rec., 1376, 10–18.
Middleton, D., and Fitzpatrick, K. (1996). “Truck accident countermeasures for urban freeways.” ITE J., 66(11), 44–51.
Milton, J., and Mannering, F. (1998). “The relationship among highway geometrics, traffic-related elements and motor vehicle accident frequencies.” Transportation, 25(4), 395–413.
National Center for Statistics and Analysis, National Highway Traffic Safety Administration (NHTSA). (2008). “Traffic safety facts.” Publication DOT-HS-811-158, NHTSA, U.S. DOT, Washington, D.C.
Oh, J., Washington, S. P., and Lee, D. (2010). “Property damage crash equivalency factors to solve crash frequency—severity dilemma: Case study on South Korean rural roads.” Transportation Research Record: Journal of the Transportation Research Board, Transportation Research Board, Washington, D.C., 83–92.
Pigman, J. G., and Agent, K. R. (1999). “Heavy truck involvement in traffic accidents and related countermeasures.” Rep. No. KTC-99-20, Kentucky Transportation Cabinet, Federal Highway Administration, Washington, D.C.
Shefer, D. (1997). “Congestion and safety on highways: Towards an analytical model.” Urban Stud., 34(4), 679–692.
Tarko, A. P., and Kanodia, M. (2004). “Effective and fair identification of hazardous locations.” Transp. Res. Rec., 1897, 64–70.
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© 2011 ASCE.
History
Received: Aug 28, 2009
Accepted: May 5, 2010
Published online: Jun 5, 2010
Published in print: Jan 2011
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