729 research outputs found
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The Conspicuity Benefits of Bicycle Taillights in Daylight
No full textBicyclists risk being injured or killed in crashes with motor vehicles, even during the daytime. Therefore, cyclists must help approaching drivers detect and recognize their presence. The present study examined the conspicuity benefits of bicycle taillights during the daytime. Participants’ eye movements were recorded as they searched for vulnerable road users in videos recorded from a driver’s perspective in a moving vehicle. Five of the videos contained a bicyclist who displayed one of five taillight configurations. The distance from which each participant first glanced at the bicyclist was recorded, as was the distance from which the participant pressed a button to indicate that a bicyclist was present. The results indicated that the participants first fixated on the bicyclist at a distance that was 2.7 times greater than the distance at which they responded to recognizing the bicyclist. Additionally, the bicyclist was recognized from significantly greater distances when using a flashing or steady seat post-mounted taillight than when no taillight was displayed. These findings confirm earlier research that bicycle taillights can enhance drivers’ ability to recognize bicyclists during daylight
Age and Secondary Task Engagement in Relation to Safe/Unsafe Driving Behavior and Crash/Non-Crash Events
No full textDriver distraction is thought to play a causal role in automobile crashes. Younger and older drivers have the highest crash risk per mile driven. To get a better understanding of the risk associated with conducting secondary tasks while driving the Naturalistic Driving Study (NDS) dataset, part of the Second Strategic Highway Research Program (SHRP2) was used to run a log-linear model comparing age and secondary task involvement and their relation to Event Severity (Balanced Baseline vs Crash), as well as Maneuver Judgement (Safe vs Unsafe). A significant relationship was found between event severity and maneuver judgement. Additionally, age group and secondary task engagement had a significant effect on event severity, but no significant interaction between age and secondary task was found. Age had a significant effect on maneuver judgement, but secondary task did not. Therefore, maneuver judgement may not be a good substitute for event severity as an outcome variable for predicting crashes
Speed Anticipation Characteristic with Optical Flow for Driver Behavior Assessment of Older Drivers
No full textThe objective of this study is to clarify the relationship between the speed anticipation characteristic with optical flow derived from self-motion and driver behavior of older drivers for future driver assessment. We focused on speed anticipation with optical flow because anticipated speed is assumed to influence behavior at unsignalized intersections with limited visibility, which is an accidentprone situation for the older drivers in Japan. To assess the characteristic, we constructed a novel test by revising a similar test. We conducted an experiment with older drivers that consisted of the novel test and an on-road driving test. The experiment results showed that the speed anticipation characteristic with optical flow had a significant effect on older drivers’ behavior at intersections and drivers who anticipated speed faster drove slower and safer
Comparing Performance when Using a New Style Large Touchscreen Compared to a Traditional In-Vehicle Touchscreen
No full textNew in-vehicle touch screen displays are increasing in size and complexity, and the effect on distraction to the driver associated with their use is unclear. Large touchscreen displays, such as those in the Tesla, provide a richer display environment as well as a larger area compared to traditional in-vehicle touchscreens even when the same capabilities are available. This simulator study examines how performing the same tasks on two different types on in-vehicle displays impacts glance behavior, vehicle control and workload. Results show that the large touchscreen results in longer average glance lengths, a greater percentage of glances of more than 2-seconds, but fewer glances. For vehicle control, there were no differences in lateral control, but the large touchscreen showed less variability in speed and speed range overall, but not uniformly across the tasks. Drivers did not report different levels of workload between the two interfaces. The results point to the need for careful design to minimize the likelihood of long glances as vehicle design moves to larger displays
Recognition of Manual Driving Distraction Through Deep-Learning and Wearable Sensing
No full textThe goal of this study is to design a novel framework incorporating deep-learning techniques and wearable sensors to recognize manual distractions during driving. Manual distraction is defined as hands off the wheel for any reason (e.g. trying to get a cell phone). In this preliminary study, participants were tasked to drive in city street and highway scenarios in a driving simulator. Verbal instructions prompted participants to perform various manual distraction tasks. The motion of driver’s right wrist during driving was recorded by a wearable inertial measurement unit. A deep-learning technique called convolutional neural network (CNN) was then constructed and trained based on 72% of the experiment trials, and evaluated by the remaining 28% of trials. The results indicated that the convolutional neural network is able to recognize the type of manual distraction task based on the right wrist motion with 87.0% accuracy and F1-score of 0.87. The results indicated that there is a good potential to apply deep-learning techniques and wearable sensing to monitor driver’s inattention status
Consumer Confusion with Levels of Vehicle Automation
No full textA consumer-facing automation taxonomy is proposed to address emergent issues of consumer confusion related to automation types and associated role responsibility. A set of surveys were fielded to help understand the extent to which consumers were able to accurately interpret a proposed consumer-facing taxonomy relative to the 6-level SAE J3016 taxonomy. Results show a mixed benefit of the proposed set over the J3016 set. For both term types and definitions, consumers were best able to differentiate the extremes of automation types, leading to the question of whether or not it may be beneficial to provide a simplified representation to communicate functionality. A binary framing (“driving” vs. “riding”) in place of a 6-level taxonomy is proposed to ensure consumer understanding
The Heterogeneity Principle
No full textThe theoretical foundation of the Naturalistic Driving (ND) MixedSafety-Critical Event (SCE) methodology is found in the historical writings of H.W. Heinrich, a 20th century industrial safety engineer. Heinrich espoused the theory that serious accidents, minor ones, and even no-injury operator errors all had identical or highly similar causal mechanisms and that accident consequences were essentially unlinked to causes. This became the basis for today’s ND MixedSCE method, whereby a variety of mostly non-crash avoidance maneuvers (e.g., hard braking, swerves) and other kinematic events (e.g., lane drifts) are aggregated by researchers to form a dependent variable dataset ostensibly representative of important and harmful crashes. This paper examines this approach and finds it to be invalidated by the pervasive causal heterogeneity of crashes and would-be surrogates. Crashes are heterogeneous horizontally by type and vertically by severity. This paper argues instead for the heterogeneity principle as the foundational assumption and guiding tenet for any effort to extrapolate causal evidence from surrogates (e.g., non-crashes or minor crashes) to a different and more important target crash population such as serious crashes
MOVE-IT: Development and Evaluation of Efficient Training Procedures for Elderly Road Users to Support their Driving Competence
No full textEvaluated training measures for improvement of elderly drivers’ driving competency lead to a considerable better driving performance, but so far are time-consuming and costly, making its nationwide implementation difficult. The aim of the present project was to develop and evaluate a modular training program for elderly drivers, which is easy, low-cost and time efficient. Based on an individual profile including driving related performance deficits and the individual need for mobility, a personalized training program is compiled. It includes individualized driving exercises, group sessions to refresh knowledge of traffic rules, consultation regarding the compensation of age-related restrictions and the use of driver assistance systems. For evaluation, a pre-post-design with 30 subjects was realized. The driving performance was measured through different performance parameters and increased through participation. Driving instructors rated the program useful and feasible. Participants were very satisfied with the concept of the training and evaluated it as being helpful. Therefore, this training concept seems to be promising for future use beyond the project work. A scientifically accompanied introduction of the training concept to several driving schools is recommended