This paper defines the problem of motor vehicle crashes involving pedestrians and pedalcyclists in the United States (U.S.), and provides a basis for related future research in the U.S. Department of Transportation's Intelligent Vehicle Initiative (IVI). The IVI is focused on solving traffic safety problems through the development and deployment of vehicle-based and vehicle-infrastructure cooperative countermeasure systems using advanced technologies. The Volpe National Transportation Systems Center, in conjunction with the National Highway Traffic Safety Administration (NHTSA), conducted a study into motor vehicular crashes involving pedestrians [1] and pedalcyclists [2], with the goal of enabling the development of concepts, functional requirements, performance guidelines, and test procedures as well as the safety assessment of potential pedestrian and pedalcyclist crash avoidance systems. The NHTSA's National Automotive Sampling System/General Estimates System (NASS/GES) crash database system [3], being a nationally representative sample of all roadway crashes, was used to describe the pedestrian and pedalcyclist crashes in this study. An aggregate of four years of GES data (1995-1998) was utilized due to the relatively low annual frequency of these two crash problems. A large crash database was needed in order to obtain a better statistical description of various crash characteristics. This paper identifies and counts these crashes by vehicle and pedestrian/pedalcyclist precrash movements, thus delineating pre-crash scenarios that represent vehicle dynamics and pedestrian/pedalcyclist actions immediately prior to impact. These scenarios then form the foundation to statistically describe the physical setting of these crashes, environmental factors, and crash consequences such as pedestrian/pedalcyclist age and maximum injury severity. The physical setting is delineated in terms of crash location to junction, presence of traffic control device, and posted speed limit. Generally, the combination of causal factors and pre-crash scenarios allows the development of crash countermeasure concepts and essential functional requirements. Information on pre-crash scenarios and their physical setting helps to develop performance guidelines and objective test procedures, including test scenarios, for crash avoidance systems. Such information also guides researchers to collect the appropriate data on driver and pedestrian/pedalcyclist performance with and without the assistance of crash avoidance systems. Such data are essential to the design of effective warning algorithms and driver-vehicle interfaces, and estimation of safety benefits for crash avoidance systems. The age and injury severity statistics support the projection of safety benefits in terms of injury severity reduction that might be accrued by the use of pedestrian/pedalcyclist crash avoidance systems.
Samenvatting