Research Papers

A Logistic Model for Examining Pedestrian Serious Injury Risk in Traffic Crashes

Filename Anowar.pdf
Filesize 367 KB
Version 1
Date added June 6, 2010
Downloaded 1 time/fois
Category 2010 CMRSC XX Niagara
Tags Session 5B
Author/Auteur Sabreena Anowar, Shamsunnahar Yasminand, Richard Tay

Abstract

Despite endeavours to alleviate the problem, pedestrian fatalities and injuries are still a public- health concern. Every year more than 1000 pedestrian casualty accidents occur in the state of Alberta amongst which more than 50 are fatalities. This study attempted to identify the factors associated with the serious injury risk of pedestrian crashes in the city of Calgary, Alberta, Canada for the periods 2004-2007 by applying a binary logistic regression model. The accidents occurring on pedestrian crosswalks, roadways with median barriers or without any special facilities (e.g. interchange ramp, loop etc.) were more likely to result in serious injuries. In addition, sun-glare, pedestrians' state of inebriation and being above the age of 60 years and pedestrians being hit by trucks were found to be associated with higher likelihood of serious injury as well. On the other hand, snowy surface was associated with a lower likelihood of serious injury. The presence of traffic signal and pedestrians attempts to cross road without appropriate right of way increased their risk of being seriously injured. Transportation engineers and other road safety professionals should target these factors in their efforts to make walking safer and more attractive to Calgarians.

Sabreena Anowar, Shamsunnahar Yasminand and Richard Tay