A systems modeling approach is presented for assessment of harm in the automotive accident environment. The methodology is presented in general form and then applied to evaluate vehicle aggressivity in frontal crashes. The methodology consists of parametric simulation of several controlled accident variables, with case results weighted by the relative frequency of each specific event. A hierarchy of models is proposed, consisting of a statistical model to define the accident environment and assign weighting factors for each crash situation case, and vehicle and occupant models for kinematic simulation of crash events. Head and chest injury results obtained from simulation are converted to harm vectors, in terms of probabilistic Abbreviated Injury Scale (AIS) distributions based on previously defined risk analyses. These harm vectors are weighted by each case's probability as defined by the statistical model, and summed to obtain a total estimate of harm for the accident environment. The methodology is applied to a subset accident environment consisting of single-and two-vehicle frontal collisions among passenger cars and light trucks. The model is validated against recent crash statistics, and is found to accurately reflect trends in distribution of injury severity while slightly underestimating moderate to severe injuries. The model is subsequently exercised for variable sensitivity analyses, wherein the effects of light truck/car population mix are evaluated in terms of their impact on occupant harm within the subset accident environment.

A systems modeling approach is presented for assessment of harm in the automotive accident environment. The methodology consists of parametric simulation of several controlled accident variables, with case results weighted by the relative frequency of each specific event. A hierarchy of models is proposed, consisting of a statistical model to define the accident environment and assign weighting factors for each crash situation case, and vehicle and occupant models for kinematic simulation of crash events. Head and chest injury results obtained from simulation are converted to harm vectors, in terms of probabilistic Abbreviated Injury Scale (AIS) distributions based on previously defined risk analyses. These harm vectors are weighted by each case’s probability as defined by the statistical model, and summed to obtain a total estimate of harm for the accident environment. The methodology is applied to a subset accident environment consisting of single- and two-vehicle frontal collisions among passenger cars and light trucks. The model is validated against injury field data, and is found to accurately reflect trends in distribution of injury severity while slightly underestimating moderate to severe injuries. The model is also exercised for variable sensitivity analyses, wherein the effects of light truck/car population mix are evaluated in terms of their impact on occupant harm within the subset accident environment.

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This paper investigates the effects the four most common misuses of a child safety seat (CSS) have on a toddler involved in a motor vehicle crash using a validated MADYMO model. These misuses involved a locking clip, shoulder harness chest clip and straps, and vehicle safety belt. A properly seated toddler in a forward-facing CSS was secured to a standard vehicle seat in a 48-kph frontal collision. The new proposed injury criteria (HIC, chest acceleration, and maximum axial neck load) and other occupant responses were used for model evaluation. For a CSS with as little as 3 centimeters of excessive slack in the vehicle safety belt, the child dummy exceeds each of the injury threshold values. Although some misuses provide a significant increase in injury response, the other misuses either individually or combined did not increase the injury potential of the child dummy in this CSS to unacceptable levels.