Driving behaviors associated with emergency service vehicle crashes in the U.S. fire service
AffiliationUniv Arizona, Dept Epidemiol & Biostat
Univ Arizona, Dept Community Environm & Policy
MetadataShow full item record
PublisherTAYLOR & FRANCIS INC
CitationD. P. Bui, C. Hu, A. M. Jung, K. M. Pollack Porter, S. C. Griffin, D. D. French, S. Crothers & J. L. Burgess (2018) Driving behaviors associated with emergency service vehicle crashes in the U.S. fire service, Traffic Injury Prevention, 19:8, 849-855, DOI: 10.1080/15389588.2018.1508837
JournalTRAFFIC INJURY PREVENTION
Rights© 2018 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractEmergency service vehicle incidents are a leading cause of firefighter fatalities and are also hazardous to civilian road users. Modifiable driving behaviors may be associated with emergency service vehicle incidents. The goal of this study was to use telematics to identify driving behaviors associated with crashes in the fire service. Forty-three emergency service vehicles in 2 fire departments were equipped with telematics devices (12 in Department A and 31 in Department B). The devices collected vehicle coordinates, speed, and g forces, which were monitored for exceptions to driving rules established by the fire departments regarding speeding, harsh braking, and hard cornering. Fire department administrative reports were used to identify vehicles involved in crashes and merged with daily telematics data. Penalized logistic regression was used to identify driving rules associated with crashes. Least absolute shrinkage and selection operator (LASSO) regression was used to generate a telematics-based risk index for emergency service vehicle incidents. Nearly 1.1 million km of driving data and 44 crashes were recorded among the 2 departments during the study. Harsh braking was associated with increased odds of crash in Department A (odds ratio [OR] = 2.22; 95% confidence interval [CI], 1.09-4.51) and Department B (OR = 1.55; 95% CI, 1.12-2.15). For every kilometer of nonemergency speeding, the odds of crash increased by 35% in Department A (OR = 1.35; 95% CI, 1.03-1.77) and by over 2-fold in Department B (OR = 2.09; 95% CI, 1.19-3.66). In Department B, hard cornering (OR = 1.14; 95% CI, 1.03-1.26) and emergency speeding (OR = 1.65; 95% CI, 1.06-2.57) were also associated with increased odds of crash. The final LASSO risk index model had a sensitivity of 73% and specificity of 57%. Harsh braking and excessive speeding were driving behaviors most associated with crash in the fire service. Telematics may be a useful tool for monitoring driver safety in the fire service.
NoteOpen access article
VersionFinal published version
SponsorsFederal Emergency Management Agency Fire Prevention & Safety Research & Development Grant [EMW-2013-FP-00351]
Except where otherwise noted, this item's license is described as © 2018 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/).