India's national road crash statistics indicate a continuing increase in casualties. Pre-crash safety technologies are effective in high-income countries, but it is unclear how these will perform in India and which crash types will remain after their implementation. The study objective was to predict and characterize the crashes resulting in moderate or more-severe injuries (Maximum Abbreviated Injury Scale 2 or above: MAIS2+) that remain on Indian roads after 22 pre-crash safety technologies have been implemented in all cars, heavy vehicles (buses and trucks), and Powered Two-Wheelers (PTW). Two deterministic rulesets (one optimistic and one conservative) were modeled for each of the pre-crash safety technologies. Each rule was designed and tuned to the functionality of one technology. The data were obtained from the Road Accident Sampling System India (RASSI) database. In addition to the effectiveness of each technology alone, the combined effectiveness of all technologies was estimated. Further, the characteristics of those crashes that none of the technologies would have avoided were determined. Rear-end-specific Autonomous Emergency Braking (AEB REAR-END) and Electronic Stability Control (ESC) installed in cars and heavy vehicles reduced MAIS2+ crashes the most. Crashes between PTWs and cars were significantly reduced by a rear-end-specific AEB installed in the cars. A pedestrian-specific AEB (AEB-PED) in cars and heavy vehicles was also shown to be effective. The only pre-crash safety technology in PTWs that was included, Antilock Braking Systems (ABS), reduced overall PTW crash involvement, but only reduced PTW-to-pedestrian crashes marginally. The largest proportion of remaining crashes were those that involved PTWs, indicating that PTW safety will remain a concern in future.


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    Title :

    Characterizing future crashes on Indian roads using counterfactual simulations of pre-crash vehicle safety technologies


    Contributors:


    Publication date :

    2022




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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