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.     

Hydrography and biogeochemistry of the north western Bay of Bengal and the north eastern Arabian Sea during winter monsoon

The north eastern Arabian Sea and the north western Bay of Bengal within the Indian exclusive economic zone were explored for their environmental characteristics during the winter monsoons of 2000 and 2001 respectively. The two regions were found to respond paradoxically to comparable intensities of the atmospheric forcing. There is an asymmetry in the net heat exchange of these two basins with atmosphere because of the varying thickness of barrier layer. During winter, the convective mixing in the Arabian Sea is driven by net heat loss from the ocean, whereas the Bay of Bengal does not contribute to such large heat loss to the atmosphere. It appears that the subduction of high saline Arabian Sea water mass is the mechanism behind the formation of a barrier layer in the northeast Arabian Sea; whereas that in the Bay of Bengal and the southeast Arabian Sea are already established as due to low saline water mass. The weak barrier layer in the Arabian Sea yields to the predominance of convective mixing to bring in nitrate-rich waters from the deeper layers to the surface, thereby supporting enhanced biological production. On the other hand, the river discharge into the Bay of Bengal during this period results in the formation of a thick and stable barrier layer, which insulates vertical mixing and provide oligotrophic condition in the Bay.     

Updating free speed models through mechanistic principles for Indian conditions

The prediction of free speeds of vehicles is an integral part of the economic appraisal of highways. It is to be noted that speeds not only govern the travel time costs, but also have major impacts on Vehicle Operating Costs (VOC). The World Bank has proposed a mechanistic free speed model based on the limiting speed concept for Highway Design and Maintenance (HDM)‐III. This model along with some refinements has been included in HDM‐4. The underlying assumption in the HDM free speed prediction model is that the free speed at any given point of time is the minimum of possible constraining speeds. This paper mainly addresses the methodology considered to update the free speed models through mechanistic principles (based on HDM‐4). This is accomplished by calibration of the model using the current data on free speeds, road and vehicle characteristics. Subsequently, the validation of the developed models has been carried out.