Literature DB >> 17005154

Bicyclist injury severities in bicycle-motor vehicle accidents.

Joon-Ki Kim1, Sungyop Kim, Gudmundur F Ulfarsson, Luis A Porrello.   

Abstract

This research explores the factors contributing to the injury severity of bicyclists in bicycle-motor vehicle accidents using a multinomial logit model. The model predicts the probability of four injury severity outcomes: fatal, incapacitating, non-incapacitating, and possible or no injury. The analysis is based on police-reported accident data between 1997 and 2002 from North Carolina, USA. The results show several factors which more than double the probability of a bicyclist suffering a fatal injury in an accident, all other things being kept constant. Notably, inclement weather, darkness with no streetlights, a.m. peak (06:00 a.m. to 09:59 a.m.), head-on collision, speeding-involved, vehicle speeds above 48.3 km/h (30 mph), truck involved, intoxicated driver, bicyclist age 55 or over, and intoxicated bicyclist. The largest effect is caused when estimated vehicle speed prior to impact is greater than 80.5 km/h (50 mph), where the probability of fatal injury increases more than 16-fold. Speed also shows a threshold effect at 32.2 km/h (20 mph), which supports the commonly used 30km/h speed limit in residential neighborhoods. The results also imply that bicyclist fault is more closely correlated with greater bicyclist injury severity than driver fault.

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Year:  2006        PMID: 17005154     DOI: 10.1016/j.aap.2006.07.002

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  31 in total

1.  Where do bike lanes work best? A Bayesian spatial model of bicycle lanes and bicycle crashes.

Authors:  Michelle C Kondo; Christopher Morrison; Erick Guerra; Elinore J Kaufman; Douglas J Wiebe
Journal:  Saf Sci       Date:  2018-03       Impact factor: 4.877

2.  Vision Zero in the United States Versus Sweden: Infrastructure Improvement for Cycling Safety.

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3.  A study of bicycle and passenger car collisions based on insurance claims data.

Authors:  Irene Isaksson-Hellman
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4.  Epidemiology and spatial examination of bicycle-motor vehicle crashes in Iowa, 2001-2011.

Authors:  Cara Hamann; Corinne Peek-Asa; Charles F Lynch; Marizen Ramirez; Paul Hanley
Journal:  J Transp Health       Date:  2015

5.  ATV and bicycle deaths and associated costs in the United States, 2000-2005.

Authors:  James C Helmkamp; Mary E Aitken; Bruce A Lawrence
Journal:  Public Health Rep       Date:  2009 May-Jun       Impact factor: 2.792

6.  Assessing bicycle-related trauma using the biomarker S100B reveals a correlation with total injury severity.

Authors:  E P Thelin; E Zibung; L Riddez; C Nordenvall
Journal:  Eur J Trauma Emerg Surg       Date:  2015-10-21       Impact factor: 3.693

7.  Database improvements for motor vehicle/bicycle crash analysis.

Authors:  Anne C Lusk; Morteza Asgarzadeh; Maryam S Farvid
Journal:  Inj Prev       Date:  2015-04-02       Impact factor: 2.399

Review 8.  The impact of transportation infrastructure on bicycling injuries and crashes: a review of the literature.

Authors:  Conor C O Reynolds; M Anne Harris; Kay Teschke; Peter A Cripton; Meghan Winters
Journal:  Environ Health       Date:  2009-10-21       Impact factor: 5.984

9.  Helmet legislation and admissions to hospital for cycling related head injuries in Canadian provinces and territories: interrupted time series analysis.

Authors:  Jessica Dennis; Tim Ramsay; Alexis F Turgeon; Ryan Zarychanski
Journal:  BMJ       Date:  2013-05-14

10.  Environmental determinants of bicycling injuries in Alberta, Canada.

Authors:  Nicole T R Romanow; Amy B Couperthwaite; Gavin R McCormack; Alberto Nettel-Aguirre; Brian H Rowe; Brent E Hagel
Journal:  J Environ Public Health       Date:  2012-11-28
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