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The analysis presented here updates and expands previous research in which rollover critical events were classified based on a detailed review of about 500 police-reported single-vehicle rollover crashes of ESC-equipped vehicles. In order to compare the rollover performance of vehicles with and without ESC for the present study, an additional sample of 150 police reports on non-ESC passenger cars and 196 police reports on light vehicles with ESC in single-vehicle rollovers were obtained, and detailed coding of rollover scenarios was performed. The coding effort was undertaken by an engineering team and focused on critical events leading to rollovers (departure from road, loss of directional control, impact with an object, and departure from road with possible driver's input); driver factors (alcohol/drug involvement, speeding, inattention, distraction, fatigue, and overcorrection); and environmental factors.

India is facing the challenge of reducing road accident fatalities, which claim close to 100,000 lives every year. Road infrastructure is slowly improving, but the number of vehicles on the road is rising fast and so is the number of road accidents, which continue to increase year after year. The data collected by law enforcement agencies is not detailed enough to identify causes and develop solutions. Traffic accidents need to be investigated in detail to include specifics concerning crash location, vehicle damage and injuries sustained by road users. The development of such a detailed database requires the co-operation of a number of government and private organizations associated with road traffic collisions. The foundation for data collection activities is a road traffic accident notification network that enables access to accident details, crashed vehicles, and injury reports in a timely manner.

With the support and cooperation of the Kanchipuram district police and Tamil Nadu police, researchers conducted detailed investigations of accidents occurring on the National Highway 45 over a 60 km stretch. The primary objective was to collect and analyze India-based traffic crash data to begin to create a sound basis for decision making for improving safety on India's roadways. A secondary objective was to establish a standardized methodology using economical tools for collecting and analyzing crash data, specific to Indian roads. For the 45 day study period, an accident intimation network was established between researchers and all police stations/highway patrols in the study area. On occurrence of an accident, police called a 24-hour contact number and researchers responded to the scene. On site, researchers used standardized reporting forms, methodologies, and equipment to perform accident scene examinations, accident vehicle examination, and AIS injury coding.

Field data is used to evaluate the number of light vehicle occupants injured or killed in side underride crashes with “combination trucks”. Statistical analyses were performed of federal crash data files for side underride crashes with passenger compartment intrusion (PCI) in the light vehicle, and an in-depth review of combination truck crashes was performed using photographs, scene diagrams, and other vehicle and occupant data. Results show that, annually, fewer than 4% of all occupant fatalities and approximately 5.5% of all occupant injuries sustained in light vehicles that have collided with combination trucks can be attributed to side impact underride with PCI.

This study examined the Consumer Product Safety Commission (CPSC) Death Certificate file to identify frequency and rate of accidental CO poisoning deaths associated with exhaust gases of stationary vehicles in enclosed areas. A comprehensive search was then made to determine whether or not there was an increase in such deaths with the introduction of “smart keys” (available as standard equipment beginning in 2004). For 2000-2011 CY, the CPSC file contained 4,760 death certificate records for ICD-10 code X47 (accidental poisoning by exposure to other gases and vapors). The manual review of narratives for these records covered 2004-2011 and found 1,553 CO poisoning deaths associated with vehicle exhaust, including 748 for enclosed areas. For these 748 incidents, information on victim and location was then identified, and an exhaustive effort was undertaken to determine whether the vehicles involved were equipped with rotary or smart keys.

Pedal misapplication events were examined using police-reported crash data to determine crash characteristics and other contributing factors. The study used police-reported crash data narratives from North Carolina (1994-2009) and included detailed manual review of each selected police report to identify possible pedal misapplication events. A comprehensive keyword search of all the records in the North Carolina data was performed to identify crashes most likely to be associated with pedal misapplications. The identified records were reviewed by engineers and classified as either “Yes,” “Possible,” or “No” pedal misapplication. For the “Yes” and “Possible” records, examination was made of the sequence of events leading up to the possible pedal misapplication. Findings show that the most frequently reported pedal misapplication events include: parking, slowing, stopped, starting, and backing, which are all low-speed events.

India's growing trend of serious road accidents has created an urgent need to understand the primary factors involved in these crashes and in the resulting severe injuries and fatalities. In order to improve the safety of highways and automobiles for all road users, a consortium of safety researchers and vehicle manufacturers has come together to collect first-hand, detailed and consistent crash and injury data for traffic accidents on Indian roads. After three years of pilot studies, a methodology, called Road Accident Sampling System - India (RASSI), has been developed for conducting on-site crash investigations and collecting in-depth accident data on road accidents in India. The processes developed under RASSI to investigate onsite crashes and collect quality accident data suitable for detailed analysis are described. The program includes all types of traffic accidents with injury outcomes.