Academic journal article Human Factors

Human Performance Models and Rear-End Collision Avoidance Algorithms

Academic journal article Human Factors

Human Performance Models and Rear-End Collision Avoidance Algorithms

Article excerpt


Collision warning systems offer a promising approach to mitigate rear-end collisions, but substantial uncertainty exists regarding the joint performance of the driver and the collision warning algorithms. A simple deterministic model of driver performance was used to examine kinematics-based and perceptual-based rear-end collision avoidance algorithms over a range of collision situations, algorithm parameters, and assumptions regarding driver performance. The results show that the assumptions concerning driver reaction times have important consequences for algorithm performance, with underestimates dramatically undermining the safety benefit of the warning. Additionally, under some circumstances, when drivers rely on the warning algorithms, larger headways can result in more severe collisions. This reflects the nonlinear interaction among the collision situation, the algorithm, and driver response that should not be attributed to the complexities of driver behavior but to the kinematics of the situation. Comp arisons made with experimental data demonstrate that a simple human performance model can capture important elements of system performance and complement expensive human-in-the-loop experiments. Actual or potential applications of this research include selection of an appropriate algorithm, more accurate specification of algorithm parameters, and guidance for future experiments.


Front-to-rear-end crashes currently represent approximately one fourth of all collisions. For 1995, the National Safety Council reported that of approximately 10.7 million motor vehicle crashes, 2.8 million were rear-end crashes, about 26.5% of the total (National Safety Council, 1996). According to the General Estimates System and Fatal Analysis Reporting System, in 1995 there were approximately 2.05 million police-reported rear-end crashes (National Safety Council, 1996). These crashes constituted approximately 28% of all police-reported crashes but only about 4.3% of all fatalities. Although many injuries and fatalities are caused by rear-end crashes, such crashes also cause approximately 157 million vehicle-hours of delay annually, which is approximately one third of all crash-caused delays.

Several driver-performance factors contribute to rear-end collisions: driver inattention, perception/reaction time, and perceptual thresholds. Driving an automobile is a complex task that requires the operator to scan the environment and respond properly in order to maintain control, avoid obstacles, and interact safely with other vehicles. Driver inattention is a particularly important factor that can undermine driving performance. Knipling et al. (1993) estimated that driver inattention accounted for 64% of all police-reported rear-end crashes. Inattention associated with following a vehicle too closely represents the cause of 14% of all crashes. The remaining causal factors include alcohol (15%), poor judgment (2%), encroachment of other vehicles (3%), and poor visibility (3%).

Because rear-end crashes account for such a large percentage of automobile crashes, and because inattention is the most frequent cause of these crashes, there has been considerable research into the possibility of alerting inattentive drivers to potential collision situations (An & Harris, 1996; Dingus, Jahns, Horowitz, & Knipling, 1998; Hirst & Graham, 1997; Knipling et al., 1993; McGehee, 1995; Shinar, Rothenberg, & Cohen, 1997; Sidway, Fairweather, Sekiya, & McNitt-Gray, 1996). A number of different rear-end collision avoidance systems (RECASs) are under development by Japanese, European, and U.S. automobile manufacturers, in addition to the evaluation efforts sponsored by the National Highway Traffic Safety Administration (NHTSA). These systems all use different algorithms to trigger a driver warning and different displays to present the warning.

The purpose of a collision warning system is to provide drivers with sufficient time to react in a collision situation, so the algorithm that determines the timing of the collision warning is critical. …

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