729 research outputs found
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The Influence of Passenger-Driver Interaction on Young Drivers
No full textThe mechanisms for young drivers being at increased risk of collision with peer aged passengers in the car are not well understood. Most studies infer a link between passenger distraction and the number of passengers, but a causal link has not been previously shown. A group of young drivers with their full Ontario, Canada G license were tested in a simulated driving environment in three conditions. The first condition involved a peer aged female passenger who asked the driver questions as they navigated a course. The second condition involved the same passenger sitting silently in the passenger seat while the driver navigated a course. The third condition involved the passenger being absent, and the driver was alone in the car while they navigated a course. Speed and way finding behaviours were found to deteriorate in the first condition compared to the other two, and standard deviation of lane position and reaction times were found to improve in the first condition compared to the other two, indicating that the drivers were moving their eyes around the environment less with conversation. This highlights the importance of reducing passenger distractions for younger drivers
The United States Version of the Stroke Drivers’ Screening Assessment Battery: A Report of Preliminary Findings
No full textWe investigated the potential for predicting driving performance of a United States (US)-based population of participants using an adapted version of the Stroke Drivers’ Screening Assessment (SDSA) battery. Participants included seven first-ever stroke survivors (age 51±8 years) and 11 individuals with Hoehn & Yahr Stage 2 or 3 Parkinson’s disease (PD) (age 65±8 years). We adapted the original United Kingdom (UK) version of the SDSA to make it suitable for use in the US by replacing all UK-specific traffic situations and road signs with their US equivalents. Following administration of the adapted (US) version of the SDSA, stroke participants’ driving performance was evaluated in a driving simulator. PD participants’ driving performance was evaluated in the driving simulator as well as on-road. The pass/fail SDSA equations of the original UK version of the SDSA were applied to predict the pass/fail outcome of participants’ driving evaluation. The SDSA predicted stroke participants’ simulator-based driving performance with 100% accuracy. The SDSA predicted PD participants’ simulator-based performance with 73% accuracy and the on-road performance with 82% accuracy. The accuracy with which driving performance of stroke and PD participants in this preliminary study was predicted by the US version of the SDSA is promising and informs the need for a larger study to better investigate and validate its predictive accurac
Driving Performance of Drug-Impaired Bus Drivers in Work Zone Areas
No full textThere are several safety issues in work zone areas due to decrease lane width, and presence of large equipment and on-site workers. The safety issues are compounded for drivers that are also drug impaired. In this study, we examine the driver performance of 18 commercial bus operators in a simulated environment while they are under the influence of a benzodiazepine drug (Triazolam). The findings show that those drivers under the influence of the drug had higher steering entropy and greater difficulty staying close to the intended travel lane when compared to those who were not under the influence of the drug. These wider travelling distances around work barrels, by those under the influence of Triazolam, could have a potential impact on the safety of nearby construction workers and heavy machine operators
PERCLOS: An Alertness Measure of the Past
No full textThe growing number of fatigue related accidents in recent years has become a serious concern. Accidents caused by fatigue, or more precisely impaired alertness, in transportation and in mining operations involving heavy equipment can lead to substantial damage and loss of life. Preventing such fatigue related accidents is universally desirable, but requires techniques for continuously estimating and predicting the operator’s alertness state. PERCLOS (percentage of eye closure) was introduced as an alertness measure. Some years later, it was claimed to be superior in fatigue detection to any other measure, including the general Eye-Tracking Signal (ETS) and even EEG recordings. This study will show that this is not the case. To put things into the prospective a fair and objective comparison between PERCLOS, the general ETS and EEG/EOG has to be established. To achieve this purpose, a protocol was established to investigate the fatigue detection capabilities of PERCLOS, ETS, and EEG/EOG in a simple two class discrimination analysis using an ensemble of Learning Vector Quantization (LVQ) networks as a classification tool. Karolinska Sleepiness Scale (KSS) and Variation of Lane Deviation (VLD) were used in order to obtain independent class labels, whereas KSS provided subjective alertness labels while VLD provided objective alertness labels. The general ETS and the fused EEG/EOG measures contain substantially greater amounts of fatigue information than the PERCLOS measures alone. These conclusions were found to be valid for all three commercially available infrared video camera systems that were utilized in the study. The data utilized in the discrimination analysis were obtained from 16 young volunteers who participated in overnight experiments in the real car driving simulation lab at the University of Schmalkalden
Potential Benefits of a Concurrent Verbal Task when Feeling Fatigued Due to Monotonous Driving Conditions
No full textWork by Atchley and Chan (2011) reported that engaging in a concurrent verbal task might serve to alleviate performance decrements in drivers when vigilance was low. Building on previous findings, the current study investigated the potential benefits of a concurrent verbal task when drivers were likely to be fatigued due to the extended duration and monotony of a driving task. Driver performance was studied under distracted and non-distracted conditions. Results indicated that strategically engaging in a concurrent verbal task led to improved driving performance when fatigue was at its highest
The Development of a Cognitive Skills Training to Support Driver Education: Experimental Validation of Theoretical Underpinnings
No full textCrash numbers of novice drivers are, despite best efforts of all involved institutions, alarmingly high. One central explanation refers to deficits in cognitive skills such as hazard perception, which have a tremendous influence on accident involvement of younger drivers. Conventional forms of driver training have largely failed to build up skills that go beyond a rather descriptive knowledge of how to drive. Computer based trainings (CBTs) are assumed to provide new ways of tackling this problem. There are already CBTs available that address relevant issues and are presumed to be effective. However, their evaluations lack evidence for the superiority of the specific features of multimedia based interventions over other forms of training. This shortcoming, in addition to the fact that all available relevant CBTs have been developed within contexts that differs significantly from European conditions in terms of the “average” driving environment as well as the respective educational schemes, has prompted us to develop a new CBT that is intended to complement the existing driver training program by addressing critical cognitive skills. In a first step, we tested the CBTs theoretical validity by comparing the performance in the training itself between learner drivers and experienced drivers. The results show that experienced drivers achieve higher scores in the CBT. We conclude that our application does indeed address relevant cognitive skills that are associated with driving experience
Integrating Kinematic- and Vision-Based Information to Better Understand Driving Behaviour
No full textThis study explored the use of two types of advanced driver assistance systems (ADAS) as tools for observing driving behavior. The first was a kinematic-based ADAS that uses speed and acceleration data to detect driving events such as hard braking, speeding and sharp turning. The second was a visionbased ADAS that uses video data to provide lane departure warnings (LDW), headway warnings (HW) and forward collision warnings (FCW). Data was collected for more than 4,500 trips and 2,200 driving hours during a period of 70 days. The sample consisted of 10 drivers that used both types of ADAS simultaneously. The information collected also included more than 17,000 records of various types of driving events. First, the events rates were estimated by the Poisson and the Poisson-lognormal models. Then, Pearson correlation and factor analysis were implemented to study the relationships among the events and to evaluate whether different types of events converged to describe the same behaviors. Significant correlations were observed between the braking and turning kinematic-based events and the FCW vision-based event, which converged under the same factor. High rates of these events may indicate that the person is driving in an urban style. The LDW, HW and speeding events converged to the second factor, which is more relevant in inter-urban areas. These findings, although based on a small-scale study, point to a potential for the use of commercial ADAS for driving behavior analysis. The integration of kinematic-based and vision-based information can provide deeper understanding of the measured behavior
Exploring the Influence of Light and Cognitive Load on Pupil Diameter in Driving Simulator Studies
No full textPupil diameter can be used as a physiological measure of cognitive load in driving simulator studies. However, pupil size depends on both cognitive load and lighting conditions. In order to accurately estimate cognitive load these two effects must be separated. In our study we introduce illumination only, cognitive only and combined tasks. Based on these we decouple the two effects on pupil diameter and we design a predictor of the pupil’s reaction to light which can be used to estimate changes in pupil diameter that are due to cognitive load
Translating Laboratory Measures to Real-World Outcomes: Application of the UFOV® Test in an Insurance Company Setting
No full textPoor performance on the Useful Field of View (UFOV® test) has been linked to negative driving outcomes, such as crashes. The UFOV® test was given to a sample of drivers 75+ years across the state of Alabama (N=2235) as a means of attaining a reduction in insurance rates if successful on the test. Results revealed that retrospectively, participants who failed the assessment were 1.65 times more likely to have an at-fault crash and 1.66 times more likely to have an at-fault insurance claim in the previous five years as compared to participants who passed the assessment. Prospectively, these same participants were 1.85 times more likely to have an at-fault crash and 2.73 times more likely to have an at-fault claim in the subsequent 1.29 years after assessment as compared to participants who passed the assessment. To the authors’ knowledge, this is the first translational study to investigate the impact of offering an insurance discount for passing such an assessment on prospective at-fault crashes and at-fault insurance claims
Use of a Simulator to Objectively Distinguish Behaviors Between Low-Risk and High-Risk Drivers
No full textThe objective of this study was to validate behavioral differences between two groups of drivers through the use of a driving simulator. Controlled experiments in a driving simulator were used to gather objective and subjective evidence on how drivers reacted to roadway objects and handled various hazardous situations. Low-risk, more experienced drivers were more aware of the mental demands of having to remember and later recall a list of items when compared to high-risk, less experienced drivers. Outcomes of the study may potentially serve as the foundation for a training program that will aim to transfer risk assessment strategies from low-risk drivers to high-risk drivers