Road traffic injuries alone account for nearly 3000 deaths per day and around two million lives worldwide. India, developing nation also faces substantial number of death due to road accidents, and it is increasing at an alarming rate. Among several states, Tamilnadu topped the number of road accidents accounting for around 14.9% of the road accidents occurring in the country. Among the cities, Chennai reported the highest number of road accidents during 2016. Hence, systematically analyzing road data and implementing proper measures are need of the hour to reduce fatality rate in coming years in urban cities. Hence, in this study, road traffic data extracted from the road accidents analysis and management system (RADMS) database has been analyzed for urban Chennai for the year 2015. The outcome variable was considered to be accident severity and the predictor variables were classified into driver, road, vehicle, temporal, collision and environmental factors. The quantitative data was analyzed for descriptive statistics, and chi-square test was performed to measure the association between accident severity and predictor variables at 95% confidence intervals. Driver’s gender, no. of drivers involved in accidents, whether the accident was hit and run case, location of accident, vehicle type, Illumination level, road surface conditions, central divider, junction type, no. of lanes, traffic movement and landmark were the contributing factors associated with accident severity. Data analysis from this study provide insights on factors to be considered to reduce accident fatalities and injuries.


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    Title :

    Risk Factors Associated with Accident Severity in Urban Chennai


    Additional title:

    Design Science and Innovation



    Conference:

    International Conference of the Indian Society of Ergonomics ; 2021 ; Aligarh, India December 08, 2021 - December 10, 2021



    Publication date :

    2021-12-14


    Size :

    6 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English