Crash dieting: The effects of eating and drinking on driving performance

Previous research suggests that compared to mobile phone use, eating and drinking while driving is more common and is seen as lower risk by drivers. Nevertheless, snacking at the wheel can affect vehicle control to a similar extent as using a hands-free phone, and is actually a causal factor in more crashes. So far, though, there has not been a controlled empirical study of this problem. In an effort to fill this gap in the literature, we used the Brunel University Driving Simulator to test participants on a typical urban scenario. At designated points on the drive, which coincided with instructions to eat or drink, a critical incident was simulated by programming a pedestrian to walk in front of the car. Whilst the driving performance variables measured were relatively unaffected by eating and drinking, perceived driver workload was significantly higher and there were more crashes in the critical incident when compared to driving normally. Despite some methodological limitations of the study, when taken together with previous research, the evidence suggests that the physical demands of eating and drinking while driving can increase the risk of a crash

Evaluation and Validation of Distraction Detection Algorithms on Multiple Data Sources

This study aims to evaluate algorithms designed to detect distracted driving. This includes the comparison of how efficiently they detect the state of distraction and likelihood of a crash. Four algorithms that utilize measures of cumulative glance, past glance behavior, and glance eccentricity were used to understand the distracted state of the driver and were validated on two separate data sources (i.e., simulator and naturalistic data). Additionally, an independent method for distraction detection was designed using data mining methods. This approach utilized measures like steering degree, lane offset, lateral and longitudinal velocity, and acceleration. The results showed a higher likelihood of distracted events when cumulative glances were considered. However, the state of distraction was observed to be higher when glance eccentricity was added. Additionally, it was observed that glance behavior using the four legacy algorithms were better detectors of the state of distraction as compared to the data mining method that used vehicular measures. This research has implications in understanding the state of distraction, predicting the power of different methods, and comparing approaches in different contexts (naturalistic vs simulator). These findings provide the fundamental building blocks towards designing advanced mitigation systems that give drivers feedback in instances of high crash likelihood

Applying psychological science to the CCTV review process: a review of cognitive and ergonomic literature

As CCTV cameras are used more and more often to increase security in communities, police are spending a larger proportion of their resources, including time, in processing CCTV images when investigating crimes that have occurred (Levesley & Martin, 2005; Nichols, 2001). As with all tasks, there are ways to approach this task that will facilitate performance and other approaches that will degrade performance, either by increasing errors or by unnecessarily prolonging the process. A clearer understanding of psychological factors influencing the effectiveness of footage review will facilitate future training in best practice with respect to the review of CCTV footage. The goal of this report is to provide such understanding by reviewing research on footage review, research on related tasks that require similar skills, and experimental laboratory research about the cognitive skills underpinning the task. The report is organised to address five challenges to effectiveness of CCTV review: the effects of the degraded nature of CCTV footage, distractions and interrupts, the length of the task, inappropriate mindset, and variability in people’s abilities and experience. Recommendations for optimising CCTV footage review include (1) doing a cognitive task analysis to increase understanding of the ways in which performance might be limited, (2) exploiting technology advances to maximise the perceptual quality of the footage (3) training people to improve the flexibility of their mindset as they perceive and interpret the images seen, (4) monitoring performance either on an ongoing basis, by using psychophysiological measures of alertness, or periodically, by testing screeners’ ability to find evidence in footage developed for such testing, and (5) evaluating the relevance of possible selection tests to screen effective from ineffective screener

Human factors workplace considerations

Computer workstations assume many different forms and play different functions today. In order for them to assume the effective interface role which they should play they must be properly designed to take into account the ubiguitous human factor. In addition, the entire workplace in which they are used should be properly configured so as to enhance the operational features of the individual workstation where possible. A number of general human factors workplace considerations are presented. This ongoing series of notes covers such topics as achieving comfort and good screen visibility, hardware issues (e.g., mouse maintenance), screen symbology features (e.g., labels, cursors, prompts), and various miscellaneous subjects. These notes are presented here in order to: (1) illustrate how one's workstation can be used to support telescience activities of many other people working within an organization, and (2) provide a single complete set of considerations for future reference

The Driving Simulator Visual Field in Glaucoma – A Novel Task to Test Available Field of View

Glaucoma causes peripheral vision loss and impaired driving performance. We developed a novel driving simulator visual field task (DSVF) in a panoramic driving simulator to map the available field of view under different perceptual task loads in naturalistic settings. Our hypothesis is that “available field of view” will decrease with increasing task load in both glaucoma subjects and controls. This is a cross-sectional study with 28 glaucoma subjects and 19 controls. DSVF (60̊ x 20̊ visual field at 2.5 m) was tested in a high-fidelity interactive driving simulator in 4 different scenarios: a) no distractions b) no driving condition with unrestricted head/eye movements c) driving d) driving with PASAT (Paced Auditory Serial Addition Test). Each test was repeated twice. The main outcome measure was a visual field index (DSVF-VFI). DSVF-VFI was compared to the Humphrey Visual field -HVF-VFI monocularly and binocularly to validate the test. The DSVF task was highly reproducible and comparable to HVF. An A-pillar scotoma appeared in all DSVF trials. In both glaucoma subjects and controls, the DSVF-VFI decreased with increasing task load. The DSVFI decreased significantly more in the glaucoma group as compared to the control group. We developed a predictive formula to predict available field of view while driving from clinic based HVF. Glaucoma subjects were impaired in completing multiple task demands, such as driving and DSVF- either because a) compensation for peripheral vision loss acts as a continuously present load on attention capacity b) glaucoma is associated with diminished cognitive capacity as compared to controls

What do we mean by cognitive load? Towards more accurate definition of the term for better identification by driver monitoring systems

The 2023 European New Car Assessment Programme (Euro NCAP) [9] protocol states that Original Equipment Manufacturers (OEMs) should include Driver Monitoring Systems (DMS) and appropriate technical assessment dossiers for evaluation by driving authorities. This includes demonstrating how the system can identify elements of driver state; driver distractions, fatigue, and unresponsiveness. Whilst visual distractions have been detailed extensively, cognitive distraction has received less attention within these protocols. Part of the reason for this could be the lack of understanding or general consensus on cognitive distraction within the context of driver state. For example, how do we assess driver state, how do we develop ground truths, how much distraction should be considered too much, and what is and is not considered cognitive? To answer these questions, workshop participants will focus on the methods and metrics used to assess cognitive load and the impact this has on driver state and performance; whether during manual driving, monitoring an automated vehicle, or during takeovers after periods of automation

‘A storm of post-it notes’:experiences of perceptual capacity in autism and ADHD

Lab-based tasks suggest autistic people have increased perceptual capacity (i.e., process more information at any one time) compared to non-autistic people. Here, we explored whether this increase is reflected in autistic people’s day-to-day perceptual experiences and, when compared to those with ADHD/neurotypical people, whether commonalities/divergences in these experiences can illuminate differences between neurotypes. UK-based adults (108 autistic, 40 with ADHD, 79 autistic with ADHD, 85 neurotypical) completed an online survey about experiences of attention and distraction. Responses were analysed using thematic analysis. We found that participants of all neurotypes experienced periods of intense focus. Neurodivergent participants reported experiencing a barrage of information; autistic participants found this overwhelming, whereas those with ADHD referred to overload. This finding may reflect increased perceptual capacity for autistic people (adding ecological validity to previous findings regarding increased autistic perceptual capacity) vs. difficulties maintaining attentional priorities for those with ADHD. While differences between neurodivergent and neurotypical people were evident, discrepancies between experiences of neurodivergent groups were more subtle, suggesting that increased perceptual capacity may extend beyond autism. Consequently, perceptual capacity offers a useful framework to promote better understanding of one’s own perceptual experiences, and to guide strategies to ameliorate any challenges encountered

Bridge strike reduction: the design and evaluation of visual warnings

The aim of this investigation was to consider the problem of road vehicles that strike rail-over-road bridges and how such incidents can be reduced. In particular, it examined the design of both the warning markings placed on bridges and the road signs situated some distance in front of the bridge, each warning of reduced clearances ahead. Initially, a literature review was conducted to reveal the nature of the problem, including the history of bridge strikes, previous attempts to quantify why bridges are hit, the cost of strikes, countermeasures to prevent them and the legal restrictions relevant to the area. It was concluded that no single countermeasure had been found to be effective when the cost and the legal restrictions were taken into account.A field assessment of possible causal factors was performed in order to compare a group of bridges that had been frequently struck, against a group of control bridges. It was found that frequently struck bridges generally were in busier environments (as might be expected), and in more visually complex environments where there were, on average, more advertisements nearby - thus more potential distractions were present at these sites. The research then considered what drivers look at when driving towards low bridges,specifically focusing on the amount of visual attention given to warning signs prior to a low bridge, and on the specific areas drivers look at in the final few seconds before reaching the bridge. It was found that the bridge warning signs and bridge markings performed badly on measures of visual attention. In addition, if an advertisement was placed on the top section of a bridge, this was looked at for a large proportion of the time - thus reducing the proportion of time which the drivers gave to other features of the environment. The development and evaluation of alternative bridge warning signs was then considered. Newly created and existing signs were evaluated on tests of comprehension and hazard perception. The results demonstrated that text-based versions of the warning sign with a yellow border performed best The development and evaluation of markings for low bridges were then examined by evaluating newly created and existing markings. The research focussed on their capacity to make a bridge appear lower than it really was - so influencing drivers' judgement of height when they approach such a bridge. The current low bridge marking standard achieved inferior scores on the experimental measures employed when compared to several of the alternative bridge marking designs that were developed. Finally, the investigation examined driver responses to both the bridge signs and markings. Using a virtual reality road scene, an experiment was performed which assessed if the existing and modified designs of the signs and markings identified earlier had any behavioural effects upon drivers as they approached the 'virtual' bridges. The addition of warning signs before the bridge was found to have no significant influence on subjects' decisions regarding stopping before the bridge. However, the type of markings displayed on the bridge did significantly affect their responses

Microscopic Modeling of Driver Behavior Based on Modifying Field Theory for Work Zone Application

Because many freeways in the U.S. and abroad are being reconstructed or rehabilitated, it becomes increasingly important to plan and design freeway work zones with the utmost in safety and efficiency. Central to the effective design of work zones is being able to understand how drivers behave as they approach and enter a work zone area. While simple and complex microscopic models have been used over the years to analyze driver behavior, most models were not designed for application in work zones and thus do not capture the interdependencies between lane-changing and car-following vehicle movements along with the drivers’ cognitive and physical characteristics. With the use of psychology’s field theory, this dissertation develops a framework for creating vector-based, explanatory, deterministic microscopic models, to enhance our understanding of driver behavior in work zones and better aid freeway planners and designers. In field theory, an agent (i.e. the driver) views a field (i.e. the area surrounding the vehicle) filled with stimuli and perceives forces associated with each stimuli once these stimuli are internalized. Based on this theory, the new modeling framework, Modified Field Theory (MFT), is designed to directly incorporate drivers’ perceptions to roadway stimuli along with vehicle movements for drivers of different cognitive and physical abilities. From this framework, specific microscopic models, such as a simple freeway work zone car following model, can be created. It is postulated that models derived from this framework would more accurately reflect the driver decision-making process, naturally modeling the effects of external stimuli such as innovative geometric configurations, lane closures, and technology applications such as variable message boards. A simple freeway work zone car following model was created using the MFT framework. Two MFT car-following agents were created and calibrated. The second agent (Agent 2) followed the first agent (Agent 1) through a one-lane segment of freeway. Car-following data for Agent 2 was plotted on a graph of relative speed vs. distance to the lead vehicle, showing car-following behavior. Car-following behavior for Agent 2 was validated against Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center (TFHRC) Living Laboratory data for simple freeway work zone car-following (Driver 15). The car-following behavior of Agent 2 replicated the “spiraling” trend observed in Driver 15. Unlike other models (such as Wiedemann), this model does not ‘force’ these trends to occur; these trends occur naturally, as a result of the perception-reaction time delay and the nature of the forces involved. Additionally, unusual car following trends reported for Driver 15 were replicated in Modified Field Theory when conditions surrounding each event were synthetically recreated. Results demonstrated that the Modified Field Theory framework can successfully replicate the process by which a driver scans the driving environment and reacts to their surroundings. Microscopic models can successfully be created using this framework. Results demonstrated that models created from this framework naturally recreate behavioral trends observed in empirical data, and that these models are capable of replicating driving behavior in unusual scenarios, such as the car following behavior of a subject vehicle when the lead vehicle has a strong sudden acceleration event. Before this model can be applied to work zones, other calibration and validation efforts are required