Forward Collision Warning: Clues to Optimal Timing of Advisory Warnings

Abstract

We examined the effectiveness of a heads-up Forward Collision Warning (FCW) system in 39 younger to middle aged drivers (25-50, mean = 35 years) and 37 older drivers (66-87, mean = 77 years). The warnings were implemented in a fixed based, immersive, 180 degree forward field of view simulator. The FCW included a visual advisory component consisting of a red horizontal bar which flashed in the center screen of the simulator that was triggered at time-to-collision (TTC) 4 seconds. The bar roughly overlapped the rear bumper of the lead vehicle, just below the driver's line-of-sight. A sustained auditory tone (~80 dB) was activated at TTC=2 to alert the driver to an imminent collision. Hence, the warning system differed from the industry standard in significant ways. 95% Confidence intervals for the safety gains ranged from −.03 to .19 seconds in terms of average correction time across several activations. Older and younger adults did not differ in terms of safety gains. Closer inspection of data revealed that younger to middle aged drivers were already braking (42%) on a larger proportion of FCW activations than older drivers (26%), p < .001. Conversely, older drivers were still accelerating (38%) on a larger proportion of FCW activations than younger to middle aged drivers (23%) at the time FCW was activated, p < .009. There were no differences in the proportion of activations when drivers were coasting at the time FCW was activated, p = .240. Furthermore, large individual differences in basic visual, motor, and cognitive function predicted the tendency to brake prior to FCW activation. Those who tended to be better functioning in each of these domains were more likely to be already braking prior to FCW activation at the fixed threshold of TTC=4. These findings suggest optimal timing for advisory alerts for forward events may need to be larger than TTC=4.

Practical and statistical challenges in driving research

“…Most research hypotheses address whether explanatory variables can predict outcomes, following the directions of the arrows in Figure . A few examples of such questions are the following: Do drivers with Alzheimer's disease have different crash rates than controls in the simulators? Do drivers with Parkinson's disease have different rates of driving errors than controls in an instrumented vehicle? What neuropsychological predictors are associated with driving errors in an instrumented vehicle? Do warning devices in a simulator affect the reaction time in older drivers? …”

“…Do warning devices in a simulator affect the reaction time in older drivers? 9 At the beginning of many studies, it takes a conscientious effort to get the hypotheses as specific as those phrased earlier. For example, a researcher may indicate an interest in comparing two groups of drivers to see which has "better" or "safer" drivers, but initially may not know how to define those vague terms.…”

MagTrack

“…Some advanced driver assistance systems can effectively detect abnormal vehicle motions, then warn the drivers of impending collisions [22], lane deviations [33], and aggressive steering [6,9,29]. However, they often leave insufficient time for the drivers to respond to complex road situations, especially when the drivers are distracted [2,19,34]. Therefore, it is important to detect unsafe driving activities early before any dangerous maneuvers occur.…”

Regression and boosting methods to inform precisionized treatment rules using data from crossover studies

“…Determining the population specific safety improvement of ADAS would be relevant to several industries. There is preliminary evidence to suggest ADAS may not benefit all drivers or may need to be altered for certain populations (Aksan et al, 2015, Aksan et al, 2016, and Aksan et al, 2017. Vehicle manufacturers and insurance providers could use the information to tailor safety warnings to individual drivers.…”

“…Driving simulators are used to study driving habits under various conditions. In a recent crossover study conducted by Aksan et al (2016), 76 drivers (ages 25-50 and 66-87 years) drove in a fixed-based driving simulator to examine the effectiveness of a forward collision warning (FCW) system. The purpose of the study was to determine whether the effectiveness of the FCW varied according to individual factors.…”