Quantifying Driver Response Times Based upon Research and Real Life Data

The purpose of this paper was to build upon previous research,identify the variables that significantly influence driver response times, and todetermine the amplitude (constant) of that influence. The goal is that this researchwill explain why seemingly analogous published studies have come to verydifferent driver response time results. An analogous driver response situation isdefined as being in one of four groups: (1) lead vehicles that were stopped ormoving slowly, (2) being cut off (when a vehicle changes lanes into the path ofthe responding driver), (3) path intrusions, or (4) known lights, icons or sounds. Itwas found that research that measured response times in analogous situations canbe used to estimate the mean response time for a particular situation ifadjustments are made to account for methodological differences between thestudies. Non-analogous studies are poor predictors of driver response (Ananticipated light stimulus response cannot accurately predict the response time toa path intrusion or lead vehicle). Mean driver response times can be predictedwithin 400 ms without accounting for individual difference. Therefore, externalvalidity can be obtained regardless of the testing method (closed course, simulatoror road), as long as the subject is unaware of either the stimulus or the appropriateresponse. Having a subject respond to multiple events does not (by itself) suggestthat drivers will respond significantly faster

Comparison of Anticipatory Glancing and Risk Mitigation of Novice Drivers and Exemplary Drivers when Approaching Curves

Novice drivers are overrepresented in run-off-the-road crashes. Indeed, the previous literature demonstrates that novice drivers are less likely to anticipate hazards or maintain attention to the forward roadway and as a result fail to mitigate hazards by slowing. This research was an effort to compare the linked hazard anticipation and hazard mitigation behaviors of novice drivers with exemplary experienced drivers at curves, locations that are known to have a greater crash risk. Each driver navigated three drives in a driving simulator, one of which included a moderate curve left and one of which included a tightening curve right. Experienced drivers made more anticipatory glances and began slowing significantly earlier in the curves than did novice drivers. However, novice drivers who anticipated hazards were much more likely to also mitigate the hazard. The use of these results in a PC-based driver hazard mitigation training program will be discussed

Backing collisions: a study of drivers\u27 eye and backing behaviour using combined rear-view camera and sensor systems

Context—Backing crash injures can be severe; approximately 200 of the 2,500 reported injuries of this type per year to children under the age of 15 years result in death. Technology for assisting drivers when backing has limited success in preventing backing crashes. Objectives—Two questions are addressed: Why is the reduction in backing crashes moderate when rear-view cameras are deployed? Could rear-view cameras augment sensor systems? Design—46 drivers (36 experimental, 10 control) completed 16 parking trials over 2 days (eight trials per day). Experimental participants were provided with a sensor camera system, controls were not. Three crash scenarios were introduced. Setting—Parking facility at UMass Amherst, USA. Subjects—46 drivers (33 men, 13 women) average age 29 years, who were Massachusetts residents licensed within the USA for an average of 9.3 years. Interventions—Vehicles equipped with a rear-view camera and sensor system-based parking aid. Main Outcome Measures—Subject’s eye fixations while driving and researcher’s observation of collision with objects during backing. Results—Only 20% of drivers looked at the rear-view camera before backing, and 88% of those did not crash. Of those who did not look at the rear-view camera before backing, 46% looked after the sensor warned the driver. Conclusions—This study indicates that drivers not only attend to an audible warning, but will look at a rear-view camera if available. Evidence suggests that when used appropriately, rear-view cameras can mitigate the occurrence of backing crashes, particularly when paired with an appropriate sensor system

Identifying hazard mitigation behaviors that lead to differences in the crash risk between experienced and novice drivers

The three most common crash types for drivers under age 18 are run-off-the-road crashes, left turn at intersection crashes, and rear end crashes. Previous literature points to novice drivers being less likely to anticipate hazards or maintain attention to the forward roadway and as a result failing to mitigate hazards by slowing adequately. In two experiments using a fixed-based high fidelity driving simulator, two groups of drivers were evaluated in potential hazard scenarios. Anticipatory glances, slowing behaviors, and lane position of experienced drivers with exemplary records and newly licensed 16 – 18 year old drivers were compared at the two curves, two intersections, and two straight segments that were most heterogeneous relative to tasks and risk of all those negotiated. In Experiment 1, experienced drivers were significantly more likely to make anticipatory (glance), and mitigation (slowing and lane keeping) responses when approaching locations of greatest risk. Experienced drivers crashed nine times and novice drivers crashed 23 times. Overall, experienced drivers began to slow approximately eight seconds before the incidents, slowed to target speed when within three seconds of the incident and selected safer lane positions than did novice drivers. In Experiment 2, the ACT (Anticipate, Control, and Terminate) computer program was developed and utilized to train one group of novice drivers. The other group received placebo training. The ACT Program was designed to teach novice drivers to slow for HRECCS (pronounced wrecks). HRECCS is an acronym that explains the reasons a driver should slow (hidden obstacles, roadside hazards, no escape route, closing with no option to pass, curves, and traffic signals). Each participant completed a pre-test, training, saw the responses made by the experienced drivers, was offered mediated training (shown their mistakes and correct responses), and finally, completed a posttest. Placebo trained drivers had the same routine but rather than rules training and mediation, they received training related to street signs. ACT trained drivers made many more anticipatory glances, slowed to target speed more often and selected safer lane positions than did the placebo trained drivers. ACT trained drivers crashed eight times compared to 22 for the placebo trained drivers

Evaluation of a Training Intervention to Improve Novice Drivers’ Hazard Mitigation Behavior on Curves

Newly licensed teenage drivers experience a higher risk of crashing compared to other age cohorts. Literature reveals that novice drivers exhibit poor hazard mitigation skills. The current study assesses the effectiveness of a training program at improving novice divers’ hazard mitigation and speed selection behaviors on curves. In this study, drivers are randomly assigned to two training cohorts (ACT and placebo), and were exposed to 2 different scenarios of interest, one scenario contained a moderate curve left and the other included a tightening curve right. ACT trained drivers made more glances to the far extent of the curve, than the placebo-trained drivers. ACT (Anticipate, Control, and Terminate) trained drivers were also significantly more likely to slow to the target speed before the curve, when compared to the placebo trained drivers. The results indicate the effectiveness of ACT as a countermeasure, at training novice drivers to select better glancing and speed management strategies