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One of the primary issues in the interpretation of vehicle impact response data, observed from vehicle crash test events, is coping with variability. This vehicle response inconsistency generally causes test results to be unpredictable and makes CAE test validation work difficult as well. This paper, considering the uncertain characteristics of vehicle impact events, has implemented a stochastic assessment of vehicle NCAP response variation through a CAE vehicle impact model, and it has accomplished the three primary study objectives as stated follows: 1) Identify the response variation causing factors stochastically from various structural and environmental factor candidates and quantify the degree of their influences on crash response, 2) Develop a methodology for interpreting the significance of the factor effects in conjunction with vehicle impact mechanics and physics, and 3) Implement a stochastic improvement of the vehicle NCAP responses and their repeatability

Today's interior systems engineer has been challenged with providing cost-effective instrument panel design solutions to meet NHTSA's new FMVSS 208 front crash regulations. Automotive manufacturers are in continuous search of newer methods and techniques to reduce prototype tests and cost. Analytical methods of predicting occupant and structural behavior using computer-aided engineering (CAE) analysis has been in place for quite some time. With the new FMVSS 208 regulations requiring both 5th and 50th percentile occupant testing, CAE analysis of predicting occupant response has become increasingly important. The CAE analyst is challenged with representing the barrier test condition, which involves the structure and the occupant moving at velocities of 25, 30 and 35 mph. Representing the cab kinematics in high-speed impacts is crucial, since capturing the vehicle intrusion and pitching should be made part of the input variables.