摘要: |
This study is an attempt to model and analyse changes in the accident rates and pattern during lockdown period where there was significant reduction in the passenger transit resulting in changes in vehicle composition. Such an analysis is utmost important for traffic management measures to reduce the frequency of occurrence of accidents involving various types of vehicles with different static and dynamic factors sharing the same road stretches. Classified traffic volume data before and during lockdown, collected from road stretches in Kerala and secondary accident data obtained from Website of Kerala Police is adopted for the analysis. Paired t-test for mean accident rates for categories, total accidents, fatality, grievous injury and property damage carried out showed that there is significant reduction in the accident rates before and during lockdown. ANOVA performed showed that, strong correlation exist between accident causes with modes involved in collision and severity of accidents. Using envelope hierarchy technique accident severity involving different modes was quantified and it found that motorized two wheelers (2W) are the most vulnerable, leading to fatal accidents. Negative Binomial regression technique was used to arrive at predominant factors contributing to accident rates and fatalities. The traffic volume and composition have significant effect on accident rate and its severity and is high time to separate motorized two wheelers especially in rural area from the traffic, which itself can reduce the accidents by 38%. |