Opportunities for preventing rear-end crashes: Findings from the analysis of actual freeway crash data

To date most traffic crash analyses have been conducted using aggregated crash data. The main focus was given to determining the relationship between crashes and corresponding variables such as traffic volume, speed, speed variance, and geometry conditions. Few studies have focused on the cause of crashes at the individual vehicular level. Recently, the Minnesota Traffic Observatory at the University of Minnesota developed a set of vehicle trajectory data containing five actual rear-end crashes. This article analyzes these data and attempts to establish a trigger factor for preventing crashes. An inverse of time-to-collision value of 0.4 detected all five actual crashes before the collision, but with a large number of false alarms. An additional trigger factor, the deceleration rate difference between leading and following vehicles greater than 15 ft/sec², completely eliminated those false alarms. In addition, it was found that an advanced warning intended to alert the driver offers little help in preventing the crashes. This is because a driver reaction time of about 0.57 sec is required before initiating deceleration. Thus, the deceleration rate required to avoid a crash became impractical, resulting in actual avoidance of only 20% crashes. This indicated that an automated braking system should be applied to prevent crashes or effectively mitigate the crash impacts.