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Ungulate-vehicle collision risk and traffic volume on roads

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Abstract

We analyzed data from traffic counters installed on 143 Czech roads (motorways and primary roads) which precisely indicated current traffic volume during occurrences of ungulate-vehicle collisions (UVC). One thousand nine hundred ninety-five UVCs were identified over the period 2009–2015 on these 143 road segments. The overall range of annual average daily traffic (AADT) values, for the respective roads, was between 1547 and 78,320 AADT (vehicles/day). Almost 80% of UVC took place at volume lower than 1000 vehicles/h. We demonstrate that traffic volume has a different distribution during the day when compared with UVC distribution. The highest relative risk of UVC was identified for traffic up to 750 vehicles/h. The risk of UVC varied over the course of the year as it was influenced by ungulate locomotory activity. We concluded that the AADT, representing average annual daily traffic, does not accurately represent the actual traffic volume which is present during the night hours, where the majority of UVC usually occur. Therefore, there is a danger that UVC risk modeling, relying on AADT, will be distorted.

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References

  • Anastasopoulos PC, Mannering FL, Shankar VN, Haddock JE (2012) A study of factors affecting highway accident rates using the random-parameters tobit model. Accid Anal Prev 45:628–633

    Article  Google Scholar 

  • Bíl M, Kubeček J, Sedoník J, Andrášik R (2017) Srazenazver.cz: a system for evidence of animal-vehicle collisions along transportation networks. Biol Conserv 213PA:167–174

    Article  Google Scholar 

  • Clopper CJ, Pearson ES (1934) The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 26:404–413

    Article  Google Scholar 

  • Core Team R (2014) A language and environment for statistical computing. R foundation for Statistical Computing, Vienna

    Google Scholar 

  • Diaz-Varela ER, Vazquez-Gonzalez I, Marey-Pérez MF, Álvarez-López CJ (2011) Assessing methods of mitigating wildlife–vehicle collisions by accident characterization and spatial analysis. Transp Res D 16:281–287

    Article  Google Scholar 

  • Elvik R (2008) The predictive validity of empirical Bayes estimates of road safety. Accid Anal Prev 40:1964–1969

    Article  Google Scholar 

  • Gkritza K, Baird M, Hans ZN (2010) Deer-vehicle collisions, deer density, and land use in Iowa’s urban deer herd management zones. Accid Anal Prev 42:1916–1925

    Article  Google Scholar 

  • Haikonen H, Summala H (2001) Deer–vehicle crashes: extensive peak at 1 h after sunset. Am J Prev Med 21(3):209–213

    Article  CAS  Google Scholar 

  • Hauer E (2001) Overdispersion in modelling accidents on road sections and in Empirical Bayes estimation. Accid Anal Prev 33:799–808

    Article  CAS  Google Scholar 

  • Huijser MP, Fuller J, Wagner ME, Hardy A, Clevenger AP (2007) Animal–vehicle collision data collection. A Synthesis of Highway Practice. NCHRP Synthesis 370. Project 20-05/Topic 37–12. Transportation Research Board of the National Academies, USA

  • Iuell B, Bekker G, Cuperus R et al (2003) Wildlife and traffic: an European handbook for identifying conflicts and designing solutions. KNNV, Bruxelles

    Google Scholar 

  • Jacobson SL, Bliss-Ketchum LL, de Rivera CE, Smith WP (2016) A behavior-based framework for assessing barrier effects to wildlife from vehicle traffic volume. Ecosphere 7(4):e01345

    Article  Google Scholar 

  • Kämmerle J-L, Brieger F, Kröschel M, Hagen R, Storch I, Suchant R (2017) Temporal patterns in road crossing behaviour in roe deer (Capreolus capreolus) at sites with wildlife warning reflectors. PLoS ONE 12(9):e0184761. https://doi.org/10.1371/journal.pone.0184761

  • Kamler JF, Jedrzejewska B, Jedrzejewski W (2007) Factors affecting daily ranges of red deer Cervus elaphus in Bialowieza Primeval Forest, Poland. Acta Theriol 52:113–118

    Article  Google Scholar 

  • Kruuse M, Enno S-E, Oja T (2016) Temporal patterns of wild boar-vehicle collisions in Estonia, at the northern limit of its range. Eur J Wildl Res 62(6):787–791

    Article  Google Scholar 

  • Kušta T, Keken Z, Ježek M, Holá M, Šmíd P (2017) The effect of traffic intensity and animal activity on probability of ungulate-vehicle collisions in the Czech Republic. Saf Sci 91:105–113

    Article  Google Scholar 

  • Madsen AB, Strandgaard H, Prang A (2002) Factors causing traffic killings of roe deer Capreolus capreolus in Denmark. Wildl Biol 8(1):55–61

    Article  Google Scholar 

  • Milligan C, Montufar J, Regehr J, Ghanney B (2016) Road safety performance measures and AADT uncertainty from short-term counts. Accid Anal Prev 97:186–196

    Article  Google Scholar 

  • Niemi M, Rolandsen CM, Neumann W, Kukko T, Tiilikainen R, Pusenius J, Solberg EJ, Ericsson G (2017) Temporal patterns of moose-vehicle collisions with and without personal injuries. – Accid. Anal Prev 98:167–173

    Article  Google Scholar 

  • Romin LA, Bissonette JA (1996) Deer-vehicle collisions: status of state monitoring activities and mitigation efforts. Wildl Soc Bull 24:276–283

    Google Scholar 

  • Seiler A (2004) Trends and spatial patterns in ungulate-vehicle collisions in Sweden. Wildl Biol 10:301–313

    Article  Google Scholar 

  • Seiler A (2005) Predicting locations of moose-vehicle collisions in Sweden. J Appl Ecol 42:371–382

    Article  Google Scholar 

  • Steiner W, Leisch F, Hackländer K (2014) A review on the temporal pattern of deer-vehicle accidents: impact of sesonal, diurnal and lunar effects in cervids. Accid Anal Prev 66:168–181

    Article  Google Scholar 

  • Sullivan JM (2011) Trends and characteristics of animal-vehicle collisions in the United States. J Saf Res 42:9–16

    Article  Google Scholar 

  • Thurfjell H, Spong G, Olsson M, Ericsson G (2015) Avoidance of high traffic levels results in lower risk of wild boar-vehicle accidents. Landsc Urban Plan 133:98–104

    Article  Google Scholar 

  • Vangala P, Lord D, Geedipally SR (2015) Exploring the application of the Negative Binomial-Generalized Exponential model for analyzing traffic crash data with excess zeros. Anal Methods Accid Res 7:29–36

    Article  Google Scholar 

  • Vanlaar WGM, Barrett H, Hing MM, Brown SW, Robertson RD (2019) Canadian wildlife-vehicle collisions: an examination of knowledge and behavior for collision prevention. J Saf Res 68:181–186

    Article  Google Scholar 

  • Yu H, Liu P, Chen J, Wang H (2014) Comparative analysis of the spatial analysis methods for hotspot identification. Accid Anal Prev 66:80–88

    Article  Google Scholar 

  • Zuberogoitia I, del Real J, Torres JJ, Rodríguez L, Alonso M, Zabala J (2014) Ungulate vehicle collisions in a peri-urban environment: consequences of transportation infrastructures planned assuming the absence of ungulates. PLoS ONE 9(9):e107713

    Article  Google Scholar 

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Acknowledgments

This work was supported by the Ministry of Education, Youth and Sports within the National Sustainability Program I, project of Transport R&D Centre (LO1610), on the research infrastructure acquired from the Operation Program Research and Development for Innovations (CZ.1.05/2.1.00/03.0064). We would like to thank Tomáš Kušta for inspiring discussion regarding the locomotory activity of ungulates. We would also like to thank David Livingstone for proofreading the English and the four anonymous reviewers for their constructive comments and suggestions.

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Correspondence to Michal Bíl.

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This article is part of the Topical Collection on Road Ecology Guest Editor: Marcello D’Amico

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Bíl, M., Kubeček, J. & Andrášik, R. Ungulate-vehicle collision risk and traffic volume on roads. Eur J Wildl Res 66, 59 (2020). https://doi.org/10.1007/s10344-020-01397-8

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  • DOI: https://doi.org/10.1007/s10344-020-01397-8

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