Citation

Mohanty M, Samal SR. Eur. Transp. 2019; 74: e1.

Copyright

(Copyright © 2019, Istituto per lo studio dei trasporti nell'integrazione economica Europea, Publisher Giordano Editore)

DOI

unavailable

PMID

unavailable

Abstract

Road crashes has been the prime cause of deaths in young age people (15-25 years). Though statistics and facts suggest that the age group of 15-25 years are the most vulnerable to road crashes but a microscopic study in the desired age group was missing. The age group was divided into 4 different categories i.e. 1518, 18-21, 21-24, and >24 years. A questionnaire was prepared containing questions related to various causes of road crashes including age, category of victim and type of injury suffered. Data was collected from an emerging smart city of India i.e. Bhubaneswar. The analysis was done by logistic regression modeling. The results revealed that in the age range of 15-25 years, it is 18-21 years age group which have the highest probability of facing a severe road crash. The probability decreases as age increases. On an average, a driver of 18-21 years age group has 100 times more chance of facing a severe road crash. Along with victims' age, time of day and type of lighting, traffic movement, character of road, type of junction, speed of vehicle, kind of vehicles involved, land use on both sides of road, drivers' license and helmet use were also found to be significantly affecting the road crashes. A questionnaire was prepared to collect the data related to causes of road crashes including age of driver and type of injury sustained. The obtained data were first analysed for statistical significance and then modelling was done using logistic regression. Speed of vehicle above 80 kmph is considered a catastrophe for riders. Similarly not using helmet increases the chances of an accident being severe by around 400 times. The modelled equations predict the severity of road crashes accurately by taking into account all the independent variables, including age groups, speed of the vehicle, helmet use, etc.

Language: en