Estimation of driver fatality ratio using computational modeling and objective measures based on vehicle intrusion ratio in head-on collisions
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Setpally, R. & Moradi, R (2011). Estimation of Driver Fatality Ratio Using Computational Modeling and Objective Measures Based on Vehicle Intrusion Ratio in Head-on Collisions. -- In Proceedings: 7th Annual Symposium: Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University, p. 134-135
The National Highway Traffic Safety Administration (NHTSA) has introduced a Driver Fatality Ratio (DFR), based on the Fatality Analysis Reporting System (FARS) and General Estimating System (GES) crash Involvement statistics, which has produced good estimates of the aggressive behavior of vehicles in crashes. The DFR proposed by NHTSA is based on the statistical data, which makes it difficult to evaluate DFR for other vehicle categories (e.g., crossovers, etc.), which are relatively new in the market as they do not have sufficient crash statistics. This research work proposes a new methodology based on computational reconstruction of impact crashes and objective measures to predict the DFR for any vehicle. The objective measures considered include the ratios of maximum intrusion, peak acceleration, and weight for the two vehicles in head-on collisions. Factors which directly influence fatal injuries to the occupants are identified and studied to develop a relation between these objective measures to the DFR. The proposed method is then validated for a range of Light Trucks and Vans (LTVs) against a passenger car, and is then used to predict the DFR of cross category vehicles. Factors which influence these objective measures in predicting the DFR are discussed. Results from this study indicate that the ratio of intrusions produces a better estimate of the DFR and can be utilized in predicting fatality ratios for head-on collisions.
Paper presented to the 7th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Marcus Welcome Center, Wichita State University, May 4, 2011.
Research completed at the Department of Mechanical Engineering