A study of factors influencing the severity of road crashes involving drunk drivers and non drunk drivers

In this study, an attempt has been made to develop Multinomial Logit (MNL) model by analysing the drunken and non drunken drivers involved in road crashes on Indian highways. Multinomial Logit model has been deployed to assess the influence of various parameters like vehicular, environment and geometric factors on the set of drivers who were found to be drunk at the time of getting involved in the road crash and those who were not under the influence of alcohol at the time of meeting with the road crash. The total economic cost of road crashes in the case of non-drunk driver road crash is Rs. 1046.27 million whereas in the case of drunk driver road crashes it is estimated to be Rs. 204.50 million. Further, it can be observed that economic cost of drunk driver road crashes is varying from 13 to 19 % across different types of road crashes.     

Modeling time mean speed and space mean speed for heterogeneous traffic conditions

This paper analyzes vehicular speeds at a micro level and studies the relationships between the important elements of speed, namely space mean speed (SMS) and time mean speed (TMS) under heterogeneous traffic conditions. Vehicular speed data were collected at selected road stretches around Delhi, India, in an attempt to understand and model the type of relationships between SMS and TMS under heterogeneous traffic conditions. To demonstrate the superiority of the proposed models, comparisons are made with existing traditional models. The results reveal that the proposed models are consistent in predicting speeds with high accuracy.