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dc.contributor.advisorLankarani, Hamid M.en_US
dc.contributor.authorSetpally, Rajarshien_US
dc.contributor.authorMoradi, Rasoulen_US
dc.date.accessioned2011-07-15T14:55:18Z
dc.date.available2011-07-15T14:55:18Z
dc.date.issued2011-05-04en_US
dc.identifier.citationSetpally, 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. 134-135en_US
dc.identifier.urihttp://hdl.handle.net/10057/3598
dc.descriptionPaper 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.en_US
dc.descriptionResearch completed at the Department of Mechanical Engineeringen_US
dc.description.abstractThe 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.en_US
dc.language.isoen_USen_US
dc.publisherWichita State University. Graduate Schoolen_US
dc.relation.ispartofseriesGRASPen_US
dc.relation.ispartofseriesv.7en_US
dc.titleEstimation of driver fatality ratio using computational modeling and objective measures based on vehicle intrusion ratio in head-on collisionsen_US
dc.typeConference paperen_US


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