Pedestrian crash risk analysis using extreme value models: New insights and evidence.

Facilitating proactive pedestrian safety management, the application of extreme value theory (EVT) models has gained popularity due to its extrapolation capabilities of estimating crashes from their precursors (i.e., conflicts).

Factors propelling fatalities during road crashes: A detailed investigation and modelling of historical crash data with field studies.

One of the major concerns in developing countries like India is to maintain traffic safety under mixed and heterogenous scenario. Although zero accidents is the need of the hour, the first step to attain it is ensuring zero deaths and no serious long-term disabling injuries in road crashes. To reduce the road crash fatalities, explicit and detailed studies have been conducted by utilising historical road crash data of two emerging smart cities of India - Bhubaneswar and Visakhapatnam.

Development of crash prediction models by assessing the role of perpetrators and victims: a comparison of ANN & logistic model using historical crash data.

Road traffic injuries cost countries 3% of their annual GDP. In developing countries like India, every year around 150,000 people die on roads. The type of vehicles involved in a crash contribute majorly to the outcome of casualty (injury/death).

Investigation of adolescent accident predictive variables in hilly regions.

The study aims to determine the significant personal and environmental factors in predicting the adolescent accidents in the hilly regions taking into account two cities Hamirpur and Dharamshala, which lie at an average elevation of 700--1000 metres above the mean sea level (MSL). Detailed comparisons between the results of 2 cities are also studied. The results are analyzed to provide the list of most significant factors responsible for adolescent accidents.