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In 2021, 412,432 road accidents were reported in India, resulting in 153,972 deaths and 384,448 injuries. India has the highest number of road fatalities, accounting for 11% of the global road fatalities. Therefore, it is important to explore the underlying causes of accidents on Indian roads. The objective of this study is to identify the factors inherent in accidents in India using clustering analysis based on self-organizing maps (SOM). It also attempts to recommend some countermeasures based on the identified factors. The study used Indian accident data collected by members of ICAT-ADAC (International Centre for Automotive Technology - Accident Data Analysis Centre) under the ICAT-RNTBCI joint project approved by the Ministry of Heavy Industries, Government of India. 210 cases were collected from the National Highway between Jaipur and Gurgaon and 239 cases from urban and semi-urban roads around Chennai were used for the analysis.

This study focused on European NCAP activities of introducing a new head protection evaluation procedure, as proposed by BASt (Federal Highway Research Institute - GERMANY). Various kinds of E-bikes are available in the market, ranging from E-bikes that have a small motor to assist the rider’s pedal-power i.e., pedelecs to somewhat more powerful E-bikes which is similar to a moped-style scooter. This paper focused on identifying the factors influencing bicyclist head kinematics during bicycle vs. passenger vehicle (PV) collisions at the intersection. Two AM50 bicyclist FE models are developed using i) GHBMC Human Body Model (HBM) and ii) WorldSID (WS) side impact dummy. Head kinematics of bicyclists of pedal-assist E-bike and normal bike were compared using CAE simulation. It is found that the vehicle’s impact velocity, type of bicycle, the mass of E-bike and bicycle traveling speed will influence the head kinematics.

Many active safety systems are being developed with the intent of protecting pedestrians namely; pedestrian airbags, active hood, active emergency braking (AEB), etc. Effectiveness of such protection system relies on the efficiency of the sensing systems. The pop-uphood system was developed to help reduce pedestrian head injuries. A pop-up system is expected to make full deployment of the hood before the pedestrian’s head could hit the hood. The system should have the capability to detect most road users ranging from a six year old (6YO) child to a large male. To test the sensing system, an impactor model (PDI-2) was developed. Sensor response varies for vehicles with different front end profile dimensions.