The timecourse of driver visual attention in naturalistic driving with adaptive cruise control and forward collision warning (original) (raw)
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Driver visual behavior while using adaptive cruise control on commercial motor vehicles
Transportation Research Part F: Traffic Psychology and Behaviour
This study compared whether drivers spent less time looking at the roadway while cruise control was engaged. The trucks in the study were equipped with commercially available systems that provide adaptive cruise control (ACC), which uses radar to regulate headway in addition to speed when following a lead vehicle. Three metrics were analyzed to assess drivers' eye-glance behavior during periods of traditional cruise control usage, full ACC usage, and manual car-following: total eyes-off-road time (TEORT), durations of glances off-road, and number of glances off-road. iii TABLE OF CONTENTS LIST OF FIGURES .
Effect of active cruise control design on glance behaviour and driving performance���
2005
Minimising driver distraction is a crucial factor in the design of new driver assistance systems and in-vehicle information systems. Therefore two different driver-vehicle interface concepts for an Active Cruise Control (ACC) system were designed and tested with 12 drivers in a static driving simulator. These concepts differed in the location (steering wheel vs. dashboard) and type of controls. Feedback on the ACC settings was given in a simulated Head-Up Display. While driving, participants were required to adjust the desired speed and following distance of the ACC system. The concepts were compared based on objective measurements of task times, driving performance and glance behaviour as well as subjective questionnaires. The type of task had a significant effect on all dependent measures, whereas the control concept had a lesser effect. The results are used to derive guidelines for the general design of the driver-vehicle interface of such driver assistance systems.
PsycEXTRA Dataset
The purpose of this report was to conduct in-depth analyses of driver inattention using the driving data collected in the 100-Car Naturalistic Driving Study. An additional database of baseline epochs was reduced from the raw data and used in conjunction with the crash and near-crash data identified as part of the original 100-Car Study to account for exposure and establish near-crash/crash risk. The analyses presented in this report are able to establish direct relationships between driving behavior and crash and near-crash involvement. Risk was calculated (odds ratios) using both crash and near-crash data as well as normal baseline driving data for various sources of inattention. The corresponding population attributable risk percentages were also calculated to estimate the percentage of crashes and near-crashes occurring in the population resulting from inattention. Additional analyses involved: driver willingness to engage in distracting tasks or driving while drowsy; analyses with survey and test battery responses; and the impact of driver's eyes being off of the forward roadway. The results indicated that driving while drowsy results in a four-to six-times higher near-crash/crash risk relative to alert drivers. Drivers engaging in visually and/or manually complex tasks have a three-times higher near-crash/crash risk than drivers who are attentive. There are specific environmental conditions in which engaging in secondary tasks or driving while drowsy is more dangerous, including intersections, wet roadways, and areas of high traffic density. Short, brief glances away from the forward roadway for the purpose of scanning the driving environment are safe and actually decrease near-crash/crash risk. Even in the cases of secondary task engagement, if the task is simple and requires a single short glance the risk is elevated only slightly, if at all. However, glances totaling more than 2 seconds for any purpose increase near-crash/crash risk by at least two times that of normal, baseline driving.
Were they in the loop during automated driving? Links between visual attention and crash potential
A proposed advantage of vehicle automation is that it relieves drivers from the moment-to-moment demands of driving, to engage in other, non-driving related, tasks. However, it is important to gain an understanding of drivers' capacity to resume manual control, should such a need arise. As automation removes vehicle control-based measures as a performance indicator, other metrics must be explored. This driving simulator study, conducted under the EC-funded AdaptIVe project, assessed drivers' gaze fixations during partially-automated (SAE Level 2) driving, on approach to critical and non-critical events. Using a between-participant design, 75 drivers experienced automation with one of five out-of-the-loop (OOTL) manipulations, which used different levels of screen visibility and secondary tasks to induce varying levels of engagement with the driving task: 1) no manipulation, 2) manipulation by light fog, 3) manipulation by heavy fog, 4) manipulation by heavy fog plus a visual task, 5) no manipulation plus an n-back task. The OOTL manipulations influenced drivers' first point of gaze fixation after they were asked to attend to an evolving event. Differences resolved within one second and visual attention allocation adapted with repeated events, yet crash outcome was not different between OOTL manipulation groups. Drivers who crashed in the first critical event showed an erratic pattern of eye fixations towards the road centre on approach to the event, while those who did not demonstrated a more stable pattern. Automated driving systems should be able to direct drivers' attention to hazards no less than 6 seconds in advance of an adverse outcome.
Assessing the Effects of Driving Inattention on Relative Crash Risk
2005
While driver distraction has been extensively studied in laboratory and empirical field studies, the prevalence of driver distraction on our nation's highways and the relative crash risk is unknown. It has recently become technologically feasible to conduct unobtrusive large-scale naturalistic driving studies as the costs and size of computer equipment and sensor technology have both dramatically decreased.
Cognitive distraction impairs drivers' anticipatory glances: An on-road study
This study assessed the impact of cognitive distraction on drivers’ anticipatory glances. Participants drove an instrumented vehicle and executed a number of secondary tasks associated with increasing levels of mental workload including: listening to the radio or audiobook, talking on a handheld or hands-free cellphone, interacting with a voice-based e-mail/text system, and executing a highly demanding task (Operational Span task; OSPAN). Drivers’ visual scanning behavior was recorded by four different high definition cameras and coded off-line frame-by-frame. Visual scanning behavior at road intersections with crosswalks was targeted because distraction is one of the major causes of accidents at these locations (NHTSA, 2010a). Despite the familiarity of the locations, results showed that as the secondary-task became more cognitively demanding drivers reduced the amount of anticipatory glances to potential hazards locations. For example, while interacting with a high fidelity voice-...
Analysis of Naturalistic Driving Study Data: Safer Glances, Driver Inattention, and Crash Risk
The Second Strategic Highway Research Program America's highway system is critical to meeting the mobility and economic needs of local communities, regions, and the nation. Developments in research and technology-such as advanced materials, communications technology, new data collection technologies, and human factors science-offer a new opportunity to improve the safety and reliability of this important national resource. Breakthrough resolution of significant transportation problems, however, requires concentrated resources over a short time frame. Reflecting this need, the second Strategic Highway Research Program (SHRP 2) has an intense, large-scale focus, integrates multiple fields of research and technology, and is fundamentally different from the broad, mission-oriented, discipline-based research programs that have been the mainstay of the highway research industry for half a century. The need for SHRP 2 was identified in TRB Special Report 260: Strategic Highway Research: Saving Lives, Reducing Congestion, Improving Quality of Life, published in 2001 and based on a study sponsored by Congress through the Transportation Equity Act for the 21st Century (TEA-21). SHRP 2, modeled after the first Strategic Highway Research Program, is a focused, timeconstrained, management-driven program designed to complement existing highway research programs. SHRP 2 focuses on applied research in four areas: Safety, to prevent or reduce the severity of highway crashes by understanding driver behavior; Renewal, to address the aging infrastructure through rapid design and construction methods that cause minimal disruptions and produce lasting facilities; Reliability, to reduce congestion through incident reduction, management, response, and mitigation; and Capacity, to integrate mobility, economic, environmental, and community needs in the planning and designing of new transportation capacity.
Attention allocation patterns in naturalistic driving
Accident Analysis & Prevention, 2013
The key to safe driving is the adequate distribution of the driver's attention to the forward area and to other non-forward focal points. However, thus far, current methods are not able to well quantify the entire process of a driver's attention allocation. Therefore, this study proposed a novel concept of renewal cycles for representing and analyzing driver attention allocation. Using the 100-car naturalistic glance data, this study found that 90.74% of drivers' attention allocations were 2-glance renewal cycles. The findings suggest that the sample drivers usually separated their lapses of attention from the forward direction into several sequences by directing their vision back to the forward direction after each visual shift away from it. In addition, although a markedly smaller number of cycles were more than 3-glances (2.09% renewal cycles), drivers were certainly less aware of the frontal area and at a higher risk of having an accident during such cycles. This finding might have striking implications for accident prevention. This area of study deserves further attention. Among the generated renewal cycles, lots of them repeated frequently, especially cycles related to invehicle distractions. To analyze the different characteristics among various attributes, distribution of the common renewal cycles under different conditions was examined. As expected, drivers displayed different renewal cycles under various road conditions and with various driver intentions. Although these sample drivers were not representative, the preliminary research results were promising and fruitful for potential applications, particularly educating novice drivers.
Driver Glance Behaviour in Intersection Crashes: A SHRP2 Naturalistic Data Analysis
2018
Road traffic crashes are one of the biggest problems in modern history. Over recent years, several attempts have been made to gain an in-depth understanding of crashes and their causation. The introduction of unobtrusive data collection methods in the form of naturalistic driving studies has given traffic safety researchers an unprecedented level of insight into the vehicle and driver during these safety critical situations. This research was started with the aim of utilising this data from naturalistic driving studies to reconstruct crashes in intersections to gain a better understanding of the driver's gaze behaviour. This was done by first developing a toolbox within the software environment of MATLAB. The toolbox used the vehicle kinematic data from the naturalistic driving study SHRP2 or the Second Strategic Highway Research Project. The toolbox was designed to transform the driver's gaze from vehicle coordinates to intersection coordinates. The target vehicle was approximated into the simulation environment with the help of the video data and manual annotation. Factors such the driver's gaze directions, eyes on target and intersection gaze timings were obtained. Well known psychological models such as the Situational Awareness, SEEV model and the more recent Predictive Processing model were evaluated to understand the findings. The results of the research showed that drivers in most of the events analysed had possibly seen and continued tracking the threat from the theoretical point of no return until the crash itself. These results were intriguing in that the drivers were not observed to engage in evasive manoeuvres until too late. A hypothesis was developed with the help of the predictive processing model to understand and explain this behaviour.
Visual Attention in Driving: The Effects of Cognitive Load and Visual Disruption
Human Factors: The Journal of the Human Factors and Ergonomics Society, 2007
According to the National Center for Statistics (NCSA), in 2006 over 6 million motor vehicle crashes occurred in the United States resulting in 42,642 deaths and approximately 2.6 million injuries. Many of these crashes result from a mismatch between the attentional and perceptual capabilities of drivers and the demands of the driving environment. A recent naturalistic study monitored 100 drivers in their own vehicles for 1 year and found approximately 85% of the crashes and near crashes resulted from some attentional failure, including fatigue and distraction . These data demonstrate a fundamental problem that plagues driving safety: People have evolved to 2-10 mph locomotion, but not the demands of 20-100 mph locomotion. This mismatch leads to circumstances in which the demands of driving exceed the capacity of the driver to respond. Recent advances in sensor and computing technology may reduce these mismatches by augmenting the driver's ability to acquire relevant information. For example, radar-based sensors can scan the road ahead and detect cars that might pose a hazard to the driver, and algorithms can process these CONTENTS