This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Modeling/Analysis of Pedestrian Back-Over Crashes from NHTSA's SCI Database

Journal Article
ISSN: 1946-3995, e-ISSN: 1946-4002
Published April 12, 2011 by SAE International in United States
Modeling/Analysis of Pedestrian Back-Over Crashes from NHTSA's SCI Database
Citation: Stanley, L., Angell, L., Deering, R., Perez, M. et al., "Modeling/Analysis of Pedestrian Back-Over Crashes from NHTSA's SCI Database," SAE Int. J. Passeng. Cars – Mech. Syst. 4(1):562-571, 2011,
Language: English


An analysis of the first 35 back-over crashes reported by NHTSA's Special Crash Investigations unit was undertaken with two objectives: (1) to test a hypothesized classification of backing crashes into types, and (2) to characterize scenario-specific conditions that may drive countermeasure development requirements and/or objective test development requirements. Backing crash cases were sorted by type, and then analyzed in terms of key features. Subsequent modeling of these SCI cases was done using an adaptation of the Driving Reliability and Error Analysis Methodology (DREAM) and Cognitive Reliability and Error Analysis Methodology (CREAM) (similar to previous applications, for instance, by Ljung and Sandin to lane departure crashes [10]), which is felt to provide a useful tool for crash avoidance technology development. This modeling effort identified contributing causes of back-over crashes, thus providing a basis for countermeasure requirements development and identifying key elements of objective test conditions for evaluating countermeasure effectiveness. This analytic work characterized the conditions under which back-over crashes occur, driver and pedestrian characteristics, and driver behaviors preceding the crash. Of particular importance, this CREAM/DREAM analysis assisted in identifying the five most common factors leading to a back-over crash (e.g., insufficient knowledge regarding line of sight and blind spots, hidden information in the environment).