Climate Change Modeling and the Weather-Related Road Accidents

Shohel Amin, Alireza Zareie, Luis Amador-Jimenez

Research output: Contribution to journalArticlepeer-review


The objective of this research is to study the impact of climate change on the hazardous weather-related road accidents in the New Brunswick, Canada. We develop an Exposure to Weather-Accident Severity (EWAS) index multiplying accident and weather severity. The Negative Binomial Regression and Poisson regression models are applied to estimate the spatial–temporal relationship between the EWAS index and weather-related explanatory variables of road accidents. The regression results show that the surface-weather condition, weather, driver’s gender, weather-driver’s age, weather-driver’s experience, and weather-vehicle’s age have strong positive correlation with the EWAS index, while the surface-road alignment and surface-road characteristics have negative relationship with the EWAS index. The climate change model also indicates that the number of accidents declines during snowy and freezing days—most people stay at home and those who travel extra cautious—accidents do occur. The study suggests that the Road Safety Strategy 2015 of the Transport Canada should take a holistic approach to help minimize the incidences of severe road accident during the normal as well as hazardous weather conditions.
Original languageEnglish
Pages (from-to)171-183
Number of pages13
JournalTransportation Research Part D: Transport and Environment
Publication statusPublished - 1 Oct 2014


  • Accident severity
  • Climate change
  • Global climate model
  • Statistical downscaling
  • Negative binomial regression
  • Poisson regression


Dive into the research topics of 'Climate Change Modeling and the Weather-Related Road Accidents'. Together they form a unique fingerprint.

Cite this