Nusholtz, G., Hsu, T., Gracián, M., Prado, J. et al., "Forward Collision Warning Timing in Near Term Applications," SAE Int. J. Trans. Safety 1(2):467-479, 2013, doi:10.4271/2013-01-0727.
Forward Collision Warning (FCW) is a system intended to warn the driver in order to reduce the number of rear end collisions or reduce the severity of collisions. However, it has the potential to generate driver annoyances and unintended consequences due to high ineffectual (false or unnecessary) alarms with a corresponding reduction in the total system effectiveness. The ineffectual alarm rate is known to be closely associated with the “time to issue warning.” This results in a conflicting set of requirements. The earlier the time the warning is issued, the greater probability of reducing the severity of the impact or eliminating it. However, with an earlier warning time there is a greater chance of ineffectual warning, which could result in significant annoyance, frequent complaints and the driver's disengagement of the FCW. Disengaging the FCW eliminates its potential benefits. A shorter warning time may be beneficial; it would reduce ineffectual alarm rates and thus reduce driver's annoyance level, increasing the driver's confidence in the system, which leads to improve overall system efficiency. To use a shorter warning time, its impact needs to be understood.In this paper an analysis of certain factors affecting the time to issue warnings is presented. A kinematics model is used to simulate variation in driving scenarios and driver characteristics, such as driver reaction time and brake force level. The analysis relies on a stochastic model that uses a set of distributions of driver responses in rear end collision avoidance maneuvers, along with the relation between crash severity/hypothetic fatality rates (HFR), to estimate the impact of the different proposed warning strategies. The study finds that a shorter warning time may be beneficial. The analysis is limited in scope to the simplest, but common, driving scenarios and for the first time quantitatively studies the impact of shorter time to warn.