Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Animal-vehicle crashes (AVCs) are a severe concern in the United States as well as in Wyoming. This study investigated the current trends of AVCs and crash rate per vehicle miles traveled (VMT) for the State of Wyoming using police-reported crash data for ten years collected from the Wyoming Department of Transportation (WYDOT). The study also examined different driver, vehicular, roadway, and environmental conditions related factors that had a strong association with AVCs. The logistic regression model was developed to check how the factors prevalent in AVCs influence the severity of AVCs. The results showed that the percentage of AVCs to that of total crashes ranged from around 15% to 22%. Among different animals involved in crashes, the majority were deer. AVCs were found to have two peaks: dawn and dusk. AVC rate was found to be the highest in November. Also, dark and unlit conditions had a strong association with AVCs. Most of the AVCs tended to occur when there were no adverse weather conditions. When the speed limit was examined, it was found that the AVC crash rate tended to increase when the posted speed limit was higher than 60 mph. AVC rate was also higher when the road surface condition was dry. Higher posted speed limit, younger drivers, and dry road surface were also found to increase the severity of AVCs. The results identified in this study will be helpful to identify effective countermeasures to reduce AVCs in Wyoming.
Rocznik
Tom
Strony
25--42
Opis fizyczny
Bibliogr. 45 poz., tab., wykr., wzory
Twórcy
autor
- University of Wyoming, 1000 E. University Ave., Laramie, WY 82071 United States Department of Civil and Architectural Engineering, Wyoming Technology Transfer Center
autor
- University of Wyoming, 1000 E. University Ave., Laramie, WY 82071 United States Department of Civil and Architectural Engineering, Wyoming Technology Transfer Center
Bibliografia
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- Dissanayake, S., & Roy, U. (2014). Crash severity analysis of single vehicle run-off-road crashes. Journal of Transportation Technologies, 4(1). https://doi.org/10.4236/jtts.2014.41001.
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- Gordon, K., Anderson, S., Gribble, B., & Johnson, M. (2001). Evaluation of the FLASH (Flashing Light Animal Sensing Host) System in Nugget Canyon, Wyoming. Report No. FHWA-WY-01/03F. Wyoming Department of Transportation.
- Gunson, K.E., Chruszcz, B., & Clevenger, A.P. (2003). Large animal-vehicle collisions in the Central Canadian Rocky Mountains: patterns and characteristics. In Proceedings of the 2003 International Conference on Ecology and Transportation. Center for Transportation and the Environment, North Carolina State University, Raleigh, NC, pp. 355-366.
- Hardy, A., Lee, S., & Al-Kaisy, A.F. (2006). Effectiveness of animal advisory messages on dynamic message signs as a speed reduction tool: Case study in rural Montana. Transportation Research Record, 1973(1). https://doi.org/10.1177/0361198106197300108.
- Huijser, M., McGowen, P., Fuller, J., Hardy, A., Kociolek, A., Clevenger, A., Smith, D., & Ament, R. (2008). Wildlife-Vehicle Collision Reduction Study: Report to Congress. Report Number FHWA-HRT-08-034. Federal Highway Administration, McLean, Virginia.
- Huijser, M.P., McGowen, P.T., & Camel, W. (2006). Animal vehicle crash mitigation using advanced technology phase I: Review, design, and implementation. Report No. FHWA-OR-TPF-07-01. Federal Highway Administration, Washington DC.
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- Langley, R.L., Higgins, S.A., & Herrin, K.B. (2006). Risk factors associated with fatal animal-vehicle collisions in the United States, 1995-2004. Wilderness & Environmental Medicine, 17(4), 229-239. https://doi.org/10.1580/06-WEME-OR-001R1.1.
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- Marcoux, A. (2005). Deer-vehicle collisions: an understanding of accident characteristics and drivers' attitudes, awareness, and involvement. Master’s thesis. Michigan State University.
- McCollister, M., & Van Manen, F. (2010). Effectiveness of wildlife underpasses and fencing to reduce wildlife‐vehicle collisions. The Journal of Wildlife Management, 74(8). https://doi.org/10.2193/2009-535.
- Morelle, K., Lehaire, F., & Lejeune, P. (2013). Spatio-temporal patterns of wildlife-vehicle collisions in a region with a high-density road network. Nature Conservation, (5), 53-73. http://hdl.handle.net/2268/158178.
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- Rodríguez-Morales, B., Díaz-Varela, E., & Marey-Pérez, M. (2013). Spatiotemporal analysis of vehicle collisions involving wild boar and roe deer in NW Spain. Accident Analysis & Prevention, 60, 121-133. https://doi.org/10.1016/j.aap.2013.07.032.
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- Savolainen, P., & Ghosh, I. (2008). Examination of Factors Affecting Driver Injury Severity in Michigan's Single-Vehicle-Deer Crashes. Transportation Research Record, 2078(1). https://doi.org/10.3141/2078-03.
- Sullivan, J. (2011). Trends and characteristics of animal-vehicle collisions in the United States. Journal of Safety Research, 42(1). https://doi.org/10.1016/j.jsr.2010.11.002.
- Wilkins, D.C., Kockelman, K.M., & Jiang, N. (2019). Animal-vehicle collisions in Texas: How to protect travelers and animals on roadways. Accident Analysis & Prevention, 131, 157-170. https://doi.org/10.1016/j.aap.2019.05.030.
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- Yang, X., Zou, Y., Wu, L., Zhong, X., Wang, Y., Ijaz, M., & Peng, Y. (2019). Comparative analysis of the reported animal-vehicle collisions data and carcass removal data for hotspot identification. Journal of Advanced Transportation, 2019. https://doi.org/10.1155/2019/3521793.
- Young, R., & Vokurka, C. (2007). Relating wildlife crashes to road reconstruction. Mountain Plains Consortium, U.S. Department of Transportation, Washington, D.C.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-79d7653f-c369-418d-a214-56d479172191