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A novel methodology is presented to estimate the safety benefits of intelligent vehicle safety systems in terms of reductions in the number of collisions and the number and severity of crash-related injuries. In addition, mathematical models and statistics are provided to support the estimation of the crash injury reduction factor in rear-end, lane change, and single vehicle roadway departure collisions. Simple models based on Newtonian mechanics are proposed to derive Δv, the change in speed that a vehicle undergoes as a consequence of crashing. Statistics on the distribution of vehicle types and weights in the United States are supplied, which are needed for Δv estimation. Moreover, mathematical equations are derived to estimate the average harm per collision. Finally, statistics on the average harm per occupant are obtained from the 1994 and 1995 Crashworthiness Data System crash databases.

The potential safety benefits of an Intelligent Cruise Control (ICC) system are assessed in terms of the number of rear-end crashes that might be avoided on U.S. freeways if all vehicles were equipped with such a system. This analysis utilizes naturalistic driving data collected from a field operational test that involved 108 volunteers who drove ten passenger cars for about 68 and 35 thousand miles in manual and ICC control modes, respectively. The effectiveness of the ICC system is estimated at about 17 percent based on computer simulations of two rear-end precrash scenarios that are distinguished by whether the following vehicle encounters a suddenly-decelerating or slow-moving lead vehicle. The ICC system has the potential to eliminate approximately 13 thousand policereported rear-end crashes on U.S. freeways, using 1996 national crash statistics.

Dynamically-distinct precrash scenarios in rear-end collisions were identified in a recent study conducted by the Volpe National Transportation Systems Center, of the United States Department of Transportation, Research and Special Programs Administration, in conjunction with the National Highway Traffic Safety Administration (NHTSA) using NHTSA's General Estimates System (GES) crash database from 1992 through 1996. Precrash scenarios represent vehicle dynamics immediately prior to a collision. This paper provides a statistical description of the five most frequently-occurring rear-end precrash scenarios in terms of vehicle and driver characteristics, using the 1996 GES database.