Literature DB >> 12729808

Overall injury risk to different drivers: combining exposure, frequency, and severity models.

Young-Jun Kweon1, Kara M Kockelman.   

Abstract

Traffic crash risk assessments should incorporate appropriate exposure data. However, existing US nationwide crash data sets, the NASS General Estimates System (GES) and the Fatality Analysis Reporting System (FARS), do not contain information on driver or vehicle exposure. In order to obtain appropriate exposure data, this work estimates vehicle miles driven (VMD) by different drivers using the Nationwide Personal Transportation Survey (NPTS). These results are combined with annual crash rates and injury severity information from the GES for a comprehensive assessment of overall risk to different drivers across vehicle classes. Data are distinguished by driver age, gender, vehicle type, crash type (rollover versus non-rollover), and injury severity. After correcting for drivers' crash exposure, results indicate that young drivers are far more crash prone than other drivers (per VMD) and that drivers of sports utility vehicles (SUVs) and pickups (PUs) are more likely to be involved in rollover crashes than those driving passenger cars. Although, the results suggest that drivers of SUVs are generally much less crash prone than drivers of passenger cars, the rollover propensity of SUVs and the severity of that crash type offset many of the incident benefits for SUV drivers.

Mesh:

Year:  2003        PMID: 12729808     DOI: 10.1016/s0001-4575(02)00021-0

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


  11 in total

1.  Smooth handling: the lack of safety-related consumer information in car advertisements.

Authors:  Nick Wilson; Anthony Maher; George Thomson; Michael Keall
Journal:  Inj Prev       Date:  2007-10       Impact factor: 2.399

2.  SUV rollover in single vehicle crashes and the influence of ESC and SSF.

Authors:  Michael J Kallan; Jessica Steps Jermakian
Journal:  Ann Adv Automot Med       Date:  2008-10

3.  "Diabetes and literacy: negotiating control through artifacts of medicalization".

Authors:  David S Martins
Journal:  J Med Humanit       Date:  2009-06

4.  Adolescent crash rates and school start times in two central Virginia counties, 2009-2011: a follow-up study to a southeastern Virginia study, 2007-2008.

Authors:  Robert Daniel Vorona; Mariana Szklo-Coxe; Rajan Lamichhane; J Catesby Ware; Ann McNallen; David Leszczyszyn
Journal:  J Clin Sleep Med       Date:  2014-11-15       Impact factor: 4.062

5.  Education level inequalities and transportation injury mortality in the middle aged and elderly in European settings.

Authors:  C Borrell; A Plasència; M Huisman; G Costa; A Kunst; O Andersen; M Bopp; J-K Borgan; P Deboosere; M Glickman; S Gadeyne; C Minder; E Regidor; T Spadea; T Valkonen; J P Mackenbach
Journal:  Inj Prev       Date:  2005-06       Impact factor: 2.399

6.  Effect of model year and vehicle type on rollover crashes and associated injuries to children.

Authors:  Michael J Kallan; Kristy B Arbogast; Dennis R Durbin
Journal:  Annu Proc Assoc Adv Automot Med       Date:  2006

7.  What we know about ADHD and driving risk: a literature review, meta-analysis and critique.

Authors:  Laurence Jerome; Alvin Segal; Liat Habinski
Journal:  J Can Acad Child Adolesc Psychiatry       Date:  2006-08

8.  Investigation of Key Factors for Accident Severity at Railroad Grade Crossings by Using a Logit Model.

Authors:  Shou-Ren Hu; Chin-Shang Li; Chi-Kang Lee
Journal:  Saf Sci       Date:  2010-02-01       Impact factor: 4.877

9.  Risk of death in crashes on Ontario's highways.

Authors:  Damian Rzeznikiewiz; Hala Tamim; Alison K Macpherson
Journal:  BMC Public Health       Date:  2012-12-28       Impact factor: 3.295

10.  High life in the sky? Mortality by floor of residence in Switzerland.

Authors:  Radoslaw Panczak; Bruna Galobardes; Adrian Spoerri; Marcel Zwahlen; Matthias Egger
Journal:  Eur J Epidemiol       Date:  2013-05-10       Impact factor: 8.082

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