Divided attention in young drivers under the influence of alcohol

Aim: The present research evaluates driving impairment linked to two crashes factors, divided attention task and alcohol, and determines whether it is higher for novice drivers than for experienced drivers. Method: Novice and experienced drivers participated in three experimental sessions in which blood alcohol concentrations (BACs) were 0.0 g/L, 0.2 g/L and 0.5 g/L. They performed a divided attention task with a main task of car-following task and an additional task of number parity identification. Driving performance, response time and accuracy on the additional task were measured. Results: ANOVA showed a driving impairment and a decrease in additional task performance from BAC of 0.5g/L, particularly for novice drivers. Indeed, the latter adopt more risky behaviour such as tailgating. In the divided attention task, driving impairment was found for all drivers and impairment on information processing accuracy was highlighted, notably in peripheral vision. Impact of research: The divided attention task used here provides a relevant method for identifying the effects of alcohol on cognitive functions and could be used in psychopharmacological research

Alaska Young Driver Safety: Distracted Driving, Seat Belt Use and Drinking and Driving

Presented to the Faculty of the University of Alaska Anchorage in Partial Fulfillment of Requirements for the Degree of MASTER OF PUBLIC HEALTHUnited States teenagers have the highest crash rate of any group in the nation. The data tell us that there are eight identified leading causes of teen injuries and deaths associated with vehicle collisions: Driver inexperience; driving with teen passengers; nighttime driving; not using seat belts; distracted driving; drowsy driving; reckless driving; and impaired driving (CDC, 2014). Alaska data tell a similar story. The leading causes of crashes for Alaskan teen drivers are: driver inattention, unsafe speed, failure to yield and driver inexperience (Alaska Injury Prevention Center, 2012). In partnership with the Alaska Injury Prevention Center, this practicum project created a resource guide identifying best practices in teen driving interventions connected to three of these areas: distracted driving, seat belt use and drinking and driving. The Strategies to Support Safe Teen Driving in Alaska resource guide is intended as a tool for community partners to access information about interventions for distracted driving, seat belt use and drinking and driving for Alaska teens and to work to put those interventions into action in their local communities. Project research efforts included a synthesis review of available intervention reports, including a multi-step filtering process that distilled available program literature down to a final collection of strategies based on best available evidence. These resulting strategies were categorized into a taxonomy identifying currently available approaches, and were also classified into levels of promise associated with certainty of effectiveness and potential population impact. Upon evaluation of intervention types within a Promise Table structure, the strategies found to be most promising were all public policy efforts surrounding graduated drivers’ licensing programs, a minimum legal drinking age at 21, cell phone restrictions while driving and seat belt requirements. In addition, the community role of creating partnerships to prevent unsafe teen driving behaviors, as well as the parental role of boundary setting and monitoring their teen’s driving behavior, were found to have equal levels of promise. Of most significance was the finding identifying the importance of executing teen driving strategies with diverse influences, including all levels of the Social Ecological Model’s influence (i.e. public policy, community, organizational, interpersonal and intrapersonal). Additional priority areas included attention to matters of community culture, public policy, enforcement and parental influence. Resulting recommendations include multiple public policy enhancements in the state of Alaska, including graduated driver’s license program modifications, enhancement of the state’s zero-tolerance policy and broad scale restrictions of driver cell-phone use.Signature Page / Title Page / Abstract / Table of Contents / List of Figures / List of Tables / List of Appendices / Introduction / Background and Significance / Project Goal and Objectives / Methods / Results / Discussion, Strengths and Limitations / Conclusions and Recommendations / References / Appendice

Autonomous Control and Automotive Simulator Based Driver Training Methodologies for Vehicle Run-Off-Road and Recovery Events

Traffic fatalities and injuries continue to demand the attention of researchers and governments across the world as they remain significant factors in public health and safety. Enhanced legislature along with vehicle and roadway technology has helped to reduce the impact of traffic crashes in many scenarios. However, one specifically troublesome area of traffic safety, which persists, is run-off-road (ROR) where a vehicle\u27s wheels leave the paved portion of the roadway and begin traveling on the shoulder or side of the road. Large percentages of fatal and injury traffic crashes are attributable to ROR. One of the most critical reasons why ROR scenarios quickly evolve into serious crashes is poor driver performance. Drivers are unprepared to safely handle the situation and often execute dangerous maneuvers, such as overcorrection or sudden braking, which can lead to devastating results. Currently implemented ROR countermeasures such as roadway infrastructure modifications and vehicle safety systems have helped to mitigate some ROR events but remain limited in their approach. A complete solution must directly address the primary factor contributing to ROR crashes which is driver performance errors. Four vehicle safety control systems, based on sliding control, linear quadratic, state flow, and classical theories, were developed to autonomously recover a vehicle from ROR without driver intervention. The vehicle response was simulated for each controller under a variety of common road departure and return scenarios. The results showed that the linear quadratic and sliding control methodologies outperformed the other controllers in terms of overall stability. However, the linear quadratic controller was the only design to safely recover the vehicle in all of the simulation conditions examined. On average, it performed the recovery almost 50 percent faster and with 40 percent less lateral error than the sliding controller at the expense of higher yaw rates. The performance of the linear quadratic and sliding algorithms was investigated further to include more complex vehicle modeling, state estimation techniques, and sensor measurement noise. The two controllers were simulated amongst a variety of ROR conditions where typical driver performance was inadequate to safely operate the vehicle. The sliding controller recovered the fastest within the nominal conditions but exhibited large variability in performance amongst the more extreme ROR scenarios. Despite some small sacrifice in lateral error and yaw rate, the linear quadratic controller demonstrated a higher level of consistency and stability amongst the various conditions examined. Overall, the linear quadratic controller recovered the vehicle 25 percent faster than the sliding controller while using 70 percent less steering, which combined with its robust performance, indicates its high potential as an autonomous ROR countermeasure. The present status of autonomous vehicle control research for ROR remains premature for commercial implementation; in the meantime, another countermeasure which directly addresses driver performance is driver education and training. An automotive simulator based ROR training program was developed to instruct drivers on how to perform a safe and effective recovery from ROR. A pilot study, involving seventeen human subject participants, was conducted to evaluate the effectiveness of the training program and whether the participants\u27 ROR recovery skills increased following the training. Based on specific evaluation criteria and a developed scoring system, it was shown that drivers did learn from the training program and were able to better utilize proper recovery methods. The pilot study also revealed that drivers improved their recovery scores by an average of 78 percent. Building on the success observed in the pilot study, a second human subject study was used to validate the simulator as an effective tool for replicating the ROR experience with the additional benefit of receiving insight into driver reactions to ROR. Analysis of variance results of subjective questionnaire data and objective performance evaluation parameters showed strong correlations to ROR crash data and previous ROR study conclusions. In particular, higher vehicle velocities, curved roads, and higher friction coefficient differences between the road and shoulder all negatively impacted drivers\u27 recoveries from ROR. The only non-significant impact found was that of the roadway edge, indicating a possible limitation of the simulator system with respect to that particular environment variable. The validation study provides a foundation for further evaluation and development of a simulator based ROR recovery training program to help equip drivers with the skills to safely recognize and recover from this dangerous and often deadly scenario. Finally, building on the findings of the pilot study and validation study, a total of 75 individuals participated in a pre-post experiment to examine the effect of a training video on improving driver performance during a set of simulated ROR scenarios (e.g., on a high speed highway, a horizontal curve, and a residential rural road). In each scenario, the vehicle was unexpectedly forced into an ROR scenario for which the drivers were instructed to recover as safely as possible. The treatment group then watched a custom ROR training video while the control group viewed a placebo video. The participants then drove the same simulated ROR scenarios. The results suggest that the training video had a significant positive effect on drivers\u27 steering response on all three roadway conditions as well as improvements in vehicle stability, subjectively rated demand on the driver, and self-evaluated performance in the highway scenario. Under the highway conditions, 84 percent of the treatment group and 52 percent of the control group recovered from the ROR events. In total, the treatment group recovered from the ROR events 58 percent of the time while the control group recovered 45 percent of the time. The results of this study suggest that even a short video about recovering from ROR events can significantly influence a driver\u27s ability to recover. It is possible that additional training may have further benefits in recovering from ROR events

Identification and safety effects of road user related measures. Deliverable 4.2 of the H2020 project SafetyCube

Safety CaUsation, Benefits and Efficiency (SafetyCube) is a European Commission supported Horizon 2020 project with the objective of developing an innovative road safety Decision Support System (DSS). The DSS will enable policy-makers and stakeholders to select and implement the most appropriate strategies, measures, and cost-effective approaches to reduce casualties of all road user types and all severities. This document is the second deliverable (4.2) of work package 4, which is dedicated to identifying and assessing road safety measures related to road users in terms of their effectiveness. The focus of deliverable 4.2 is on the identification and assessment of countermeasures and describes the corresponding operational procedure and outcomes. Measures which intend to increase road safety of all kind of road user groups have been considered [...continues]