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Traffic Injury Prevention Volume 21, 2020 - Issue 7
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Articles

Seasonal crash prediction model for urban signalized intersections: Wisconsin southeast region

Boris ClarosTraffic Operations and Safety (TOPS) Laboratory, University of Wisconsin – Madison, Madison, WisconsinCorrespondence[email protected]
,
Madhav ChitturiTraffic Operations and Safety (TOPS) Laboratory, University of Wisconsin – Madison, Madison, Wisconsin
,
Glenn VorhesTraffic Operations and Safety (TOPS) Laboratory, University of Wisconsin – Madison, Madison, Wisconsin
,
Andi BillTraffic Operations and Safety (TOPS) Laboratory, University of Wisconsin – Madison, Madison, Wisconsin
&
David NoyceTraffic Operations and Safety (TOPS) Laboratory, University of Wisconsin – Madison, Madison, Wisconsin
Pages 447-452 | Received 21 Sep 2019, Accepted 05 Jun 2020, Published online: 18 Jun 2020

References

  • American Association of State Highway Transportation Officials (AASHTO). 2014. Highway safety manual (HSM) with supplement, 1st ed. Washington, DC: AASHTO.
  • Caliendo C, Guida M, Parisi A. 2007. A crash-prediction model for multilane roads. Accid Anal Prev. 39(4):657–670. doi:10.1016/j.aap.2006.10.012
  • Claros B, Sun C, Edara P. 2017. Enhancing safety risk management with quantitative measures. Transp Res Record. 2603(1):1–12. doi:10.3141/2603-01
  • El-Basyouny K, Barua S, Islam MT. 2014. Investigation of time and weather effects on crash types using full Bayesian multivariate Poisson lognormal models. Accid Anal Prev. 73:91–99. doi:10.1016/j.aap.2014.08.014
  • Federal Highway Administration. 2018. How do weather events impact roads? Road weather management. [Accessed 2019 November 29]. https://ops.fhwa.dot.gov/weather/q1_roadimpact.htm. Published 2018.
  • Federal Highway Administration. 2019. Chapter VII. Trip purpose. [Accessed 2020 March 9] https://www.fhwa.dot.gov/policy/otps/nextgen_stats/chap7.cfm. Published 2019.
  • Hauer E. 2015. The art of regression modeling in roadway safety. Switzerland: Springer.
  • Hauer E, Council F, Mohammedshah Y. 2004. Safety models for urban four-lane undivided road segments. Transp Res Record. 1897(1):96–105. doi:10.3141/1897-13
  • Lord D, Mannering F. 2010. The statistical analysis of crash-frequency data: a review and assessment of methodological alternatives. Transp Res Part A: Pol and Prac. 44(5):291–305. doi:10.1016/j.tra.2010.02.001
  • Ma X, Chen F, Chen S. 2015. Modeling crash rates for a mountainous highway by using refined-scale panel data. Transp Res Record. 2515(1):10–16. doi:10.3141/2515-02
  • Maze TH, Agarwal M, Burchett G. 2006. Whether weather matters to traffic demand, traffic safety, and traffic operations and flow. Transp Res Record. 1948(1):170–176. doi:10.1177/0361198106194800119
  • Memmott J, Young P. Seasonal variation in traffic congestion: a study of three U.S. cities. Bureau of Transportation Statistics. U.S. Department of Transportation; 2008.
  • Naik B, Tung LW, Zhao S, Khattak AJ. 2016. Weather impacts on single-vehicle truck crash injury severity. J Safety Res. 58:57–65. doi:10.1016/j.jsr.2016.06.005
  • Qiu L, Nixon W. 2008. Effects of adverse weather on traffic crashes: systematic review and meta-analysis. Transp Res Record. 2055(1):139–146. doi:10.3141/2055-16
  • Theofilatos A, Yannis G. 2014. A review of the effect of traffic and weather characteristics on road safety. Accid Anal Prev. 72:244–256. doi:10.1016/j.aap.2014.06.017
  • Ulfarsson G, Shankar V. 2003. Accident count model based on multiyear cross-sectional roadway data with serial correlation. Transp Res Record. 1840(1):193–197. doi:10.3141/1840-22
  • Wisconsin Traffic Operations and Safety (TOPS) Laboratory. 2017. The WisTransPortal data hub. University of Wisconsin – Madison. [Accessed 2017 Nov 1]. http://transportal.cee.wisc.edu/.
  • Yu R, Xiong Y, Abdel-Aty MA. 2015. correlated random parameter approach to investigate the effects of weather conditions on crash risk for a mountainous freeway. Transp Research Part C Emerg Tech. 50:68–77. doi:10.1016/j.trc.2014.09.016

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