This research investigates the relationship between vehicle design, crash characteristics, infrastructure, and driver attributes using current databases; the structure of the accident causation-consequence system via fault-tree analysis; and optimization of vehicle design criteria to minimize the risk of injury and fatality when constraints on fuel economy, cost, and convenience are recognized. The study will enable structuring and classification of knowledge about accident causation and crash management using quantitative risk analysis tools and methodologies, and allow identification of knowledge gaps that are preventing a more complete understanding of the complex highway transportation system. Decision models resulting from this work will aid the automobile industry in the selection of the optimal crash-avoidance measure under resource constraints in a timely yet market-focused and cost effective manner. Several features of the proposed decision making framework include the consideration of the multiple conflicting and noncommensurable objectives in the optimal design process; the allowance of the impact analysis on multiple injury levels and on various consumer groups; and the recognition of complex system interactions. To achieve the stated objectives two sources of expertise will be used: From academic research recently developed and/or enhanced engineering design methodologies including fault-tree analysis, multiobjective and trade-off analysis, and optimal resource allocation will be used. Industrial research will contribute an understanding of the biomechanical responses to the physical characteristics of various energy-absorbing materials.
