Michelle L. Reyes

Collision Warning Timing, Driver Distraction, and Driver Response to Imminent Rear-End Collisions in a High-Fidelity Driving Simulator:

Rear-end collisions account for almost 30% of automotive crashes. Rear-end collision avoidance systems (RECASs) may offer a promising approach to help drivers avoid these crashes. Two experiments performed using a high-fidelity motion-based driving simulator examined driver responses to evaluate the efficacy of a RECAS. The first experiment showed that early warnings helped distracted drivers react more quickly---and thereby avoid more collisions---than did late warnings or no warnings. Compared with the no-warning condition, an early RECAS warning reduced the number of collisions by 80.7%. Assuming collision severity is proportional to kinetic energy, the early warning reduced collision severity by 96.5%. In contrast, the late warning reduced collisions by 50.0 % and the corresponding severity by 87.5%. The second experiment showed that RECAS benefits even undistracted drivers. Analysis of the braking process showed that warnings provide a potential safety benefit by reducing the time required for drivers to release the accelerator. Warnings do not, however, speed application of the brake, increase maximum deceleration, or affect mean deceleration. These results provide the basis for a computational model of driver performance that was used to extrapolate the findings and identify the most promising parameter settings. Potential applications of these results include methods for evaluating collision warning systems, algorithm design guidance, and driver performance model input.

Nonintrusive Detection of Driver Cognitive Distraction in Real Time Using Bayesian Networks

Driver distraction has become an important and growing safety concern as the use of in-vehicle information systems (IVISs), such as cell phones and navigation systems, continues to increase. One approach to allowing people to benefit from IVISs without compromising safety is to create adaptive IVISs that adjust their functions according to driver and roadway state. A critical element of adaptive IVISs involves monitoring driver distraction in real time; with such a monitoring function it is possible to mitigate that distraction. This study applied Bayesian networks (BNs), a data mining method, to develop a real-time approach to detecting cognitive distraction using drivers’ eye movements and driving performance. Data were collected in a simulator experiment involving 10 participants who interacted with an IVIS system while driving. BN models were trained and tested to investigate the influence of three model characteristics on distraction detection: time history of driver behavior, inclusion of hidden nodes in the model structure, and how data are summarized and the length of training sequences. Results showed that BNs could identify driver distraction reliably with an average accuracy of 80.1%. Dynamic BNs (DBNs) that consider time dependencies of driver behavior produced more sensitive models than static BNs (SBNs). Longer training sequences improved DBN model performance. Blink frequency and fixation measures were particularly indicative of distraction. These results demonstrate that BNs, especially DBNs, can detect driver cognitive distraction by extracting information from complex behavioral data. Potential applications include the design of adaptive in-vehicle systems and the evaluation of driver distraction.

The Influence of IVIS Distractions on Tactical and Control Levels of Driving Performance

Computer, software, telecommunications, and automotive companies have begun to develop In-Vehicle Information System (IVIS) functions despite the potential for these devices to distract drivers. A simulator study examined how the demands of an IVIS affected driver response in tactical and control braking conditions. The IVIS demands were manipulated according to multiple resource theory dimensions of processing code and stage. Drivers listened to and answered questions about messages containing information about restaurants. The findings show that verbal and spatial coding had little effect on driving performance, but responding to the messages degraded reaction time in the tactical braking conditions. These results suggest that particular consideration should be given to IVIS tasks that demand a response from the driver and that tactical rather than simply control driving performance merits attention in IVIS evaluation.

329 A randomised trial to improve novice driving

Background Motor vehicle crashes are a leading cause of death worldwide, and novice drivers have the highest crash risk. Interventions that integrate parents in motivating safe teen driving are a promising strategy. Methods A randomised trial tested two intervention strategies: in-vehicle video feedback and a parent-focused communication program called “Steering Teens Safe (STS).” For the in-vehicle video feedback, two small video cameras with GPS recorded driving and driving errors (exceeding a threshold for acceleration/deceleration or lateral movement). A blinking light alerted drivers of an error, and parents received a weekly report card with video clips and a summary. STS trained parents to improve the quality and quantity of parent-teen communication about safe driving. Evaluations have shown both interventions to be effective independently, but no studies have examined parent-teen interaction related to in-vehicle feedback systems. 153 parent-teen dyads were recruited through local high schools and randomised to one of three groups: control; in-vehicle video feedback; and feedback with STS. Preliminary Results During baseline (4 weeks), groups averaged between 22 and 27 driving errors per week. The STS plus video group reduced their average driving errors to 8 in the first month (a 64% reduction) and to five or less in the second through fourth months (−77%). The video only group had a slight reduction of 27 to 23 (−15%) driving errors in the first month, then reduced to ten or less for months two through four (−63%). The control group did not show any decrease in driving errors. Proportionate hazards models indicate that the STS group had a significantly faster reduction in driving errors, and both intervention groups had significant reductions by the fourth month. Conclusions In-vehicle video feedback systems effectively reduce driving errors, and the effectiveness is significantly improved when paired with a parent-focused communication program.