Weather impacts on single-vehicle truck crash injury severity

Bhaven Naik, Li Wei Tung, Shanshan Zhao, Aemal J. Khattak

Research output: Contribution to journalArticle

37 Scopus citations

Abstract

Introduction The focus of this paper is on illustrating the feasibility of aggregating data from disparate sources to investigate the relationship between single-vehicle truck crash injury severity and detailed weather conditions. Specifically, this paper presents: (a) a methodology that combines detailed 15-min weather station data with crash and roadway data, and (b) an empirical investigation of the effects of weather on crash-related injury severities of single-vehicle truck crashes. Method Random parameters ordinal and multinomial regression models were used to investigate crash injury severity under different weather conditions, taking into account the individual unobserved heterogeneity. The adopted methodology allowed consideration of environmental, roadway, and climate-related variables in single-vehicle truck crash injury severity. Results and conclusions Results showed that wind speed, rain, humidity, and air temperature were linked with single-vehicle truck crash injury severity. Greater recorded wind speed added to the severity of injuries in single-vehicle truck crashes in general. Rain and warmer air temperatures were linked to more severe crash injuries in single-vehicle truck crashes while higher levels of humidity were linked to less severe injuries. Random parameters ordered logit and multinomial logit, respectively, revealed some individual heterogeneity in the data and showed that integrating comprehensive weather data with crash data provided useful insights into factors associated with single-vehicle truck crash injury severity. Practical applications The research provided a practical method that combined comprehensive 15-min weather station data with crash and roadway data, thereby providing useful insights into crash injury severity of single-vehicle trucks. Those insights are useful for future truck driver educational programs and for truck safety in different weather conditions.

Original languageEnglish (US)
Pages (from-to)57-65
Number of pages9
JournalJournal of Safety Research
Volume58
DOIs
StatePublished - Sep 1 2016

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Keywords

  • Crash severity
  • Mixed logit model
  • Random parameters ordered logit model
  • Truck safety
  • Weather data

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

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