Factors that influence visual attention and their effects on safety in driving: an eye movement tracking approach

Statistics show that a high percentage of road related accidents are due to factors that cause impaired driving. Since information extraction in driving is predominantly a visual task, visual distraction and its implications are therefore important safety issues. The main objective of this research is to study some of the implications of demands to human’s attention and perception and how it affects performance of tasks such as driving. Specifically, the study aims to determine the changes that occur in the visual behavior of drivers with different levels of driving experience by tracking the movement of the eye; examine the effects of different levels of task complexity on visual fixation strategies and visual stimulus recognition; investigate the effects of secondary task on attentional and visual focus and its impact on driving performance; and evaluate the implications of the use of information technology device (cellular phone) while driving on road safety. Thirty-eight students participated in the study consisting of two experiments. In the first experiment, the participants performed two driving sessions while wearing a head mounted eye tracking device. The second experiment involved driving while engaging in a cellular phone conversation. Fixation location, frequency, duration and saccadic path, were used to analyze eye movements. The study shows that differences in visual behavior of drivers exist; wherein drivers with infrequent driving per week fixated more on the dashboard area than on the front view (F(3,26) = 3.53, p\u3c0.05), in contrast to the driver with more frequent use of vehicle per week where higher fixations were recorded in the front/center view (F(3,26) = 4.26). The degree of visual distraction contributes to the deterioration of driving resulting to 55% more driving errors committed. Higher time where no fixation was detected was observed when driving with distraction (from 96% to 91% for drivers with less frequency of vehicle use and 55% to 44% for drivers with more frequent use of vehicle). The number of pre-identified errors committed increased from 64 to 81, due to the effect of visual tunneling. This research presents objective data that strengthens the argument on the detrimental effects of distraction in driving

A driving simulator study to explore the effects of text size on the visual demand of in-vehicle displays

Modern vehicles increasingly utilise a large display within the centre console, often with touchscreen capability, to enable access to a wide range of driving and non-driving-related functionality. The text provided on such displays can vary considerably in size, yet little is known about the effects of different text dimensions on how drivers visually sample the interface while driving and the potential implications for driving performance and user acceptance. A study is described in which sixteen people drove motorway routes in a medium-fidelity simulator and were asked to read text of varying sizes (9 mm, 8 mm, 6.5 mm, 5 mm, or 4 mm) from a central in-vehicle display. Pseudo-text was used as a stimulus to ensure that participants scanned the text in a consistent fashion that was unaffected by comprehension. There was no evidence of an effect of text size on the total time spent glancing at the display, but significant differences arose regarding how glances were distributed. Specifically, larger text sizes were associated with a high number of relatively short glances, whereas smaller text led to a smaller number of long glances. No differences were found in driving performance measures (speed, lateral lane position). Drivers overwhelmingly preferred the ‘compromise’ text sizes (6.5 mm and 8 mm). Results are discussed in relation to the development of large touchscreens within vehicles

The development of improvements to drivers' direct and indirect vision from vehicles - phase 1

This research project concerning "The development of improvements to drivers' direct and indirect vision from vehicles" has been designed to be conducted in two phases: . Phase 1 whose aim is to scope the existing knowledge base in order to prioritise and direct activities within Phase 2; . Phase 2 whose aim is to investigate specific driver vision problems prioritised in Phase 1 and determine solutions to them. This report details the activities, findings and conclusions resulting from the Phase 1 tasks undertaken

Has the time come for an older driver vehicle?

The population of the world is growing older. As people grow older they are more likely to experience declines that can make operating a personal automobile more difficult. Once driving abilities begin to decline, older adults are often faced with decreased mobility. Due to the preference for and pervasiveness of the personal automobile for satisfying mobility needs, there is a global necessity to keep older adults driving for as long as they can safely do so. In this report we explore the question: Has the time come for an older driver vehicle? Great gains in safe mobility could be made by designing automobiles that take into account, and help overcome, some of the deficits in abilities common in older people. The report begins by providing a background and rationale for an older driver vehicle, including discussions of relevant trends, age-related declines in functional abilities, and the adverse consequences of decreased mobility. The next section discusses research and issues related to vehicle design and advanced technology with respect to older drivers. The next section explores crashworthiness issues and the unique requirements for older adults. The following section discusses the many issues related to marketing a vehicle that has been designed for older drivers. The report concludes that there is a clear global opportunity to improve the safety, mobility, and quality of life of older adults by designing vehicles and vehicle technologies that help overcome common age-related deficits. The marketing of these vehicles to older consumers, however, will be challenging and will likely require further market research. The development of vehicle design features, new automotive technologies, and crashworthiness systems in the future should be guided by both knowledge of the effects of frailty/fragility of the elderly on crash outcomes, as well as knowledge of common drivingrelated declines in psychomotor, visual, and cognitive abilities. Design strategies that allow for some degree of customization may be particularly beneficial. It is clear that training and education efforts for using new vehicle features will need to be improved.The University of Michigan Sustainable Worldwide Transportationhttp://deepblue.lib.umich.edu/bitstream/2027.42/89960/1/102821.pd

A Survey on Datasets for Decision-making of Autonomous Vehicle

Autonomous vehicles (AV) are expected to reshape future transportation systems, and decision-making is one of the critical modules toward high-level automated driving. To overcome those complicated scenarios that rule-based methods could not cope with well, data-driven decision-making approaches have aroused more and more focus. The datasets to be used in developing data-driven methods dramatically influences the performance of decision-making, hence it is necessary to have a comprehensive insight into the existing datasets. From the aspects of collection sources, driving data can be divided into vehicle, environment, and driver related data. This study compares the state-of-the-art datasets of these three categories and summarizes their features including sensors used, annotation, and driving scenarios. Based on the characteristics of the datasets, this survey also concludes the potential applications of datasets on various aspects of AV decision-making, assisting researchers to find appropriate ones to support their own research. The future trends of AV dataset development are summarized

A comparative study of using Augmented Reality interfaces for vehicle navigation

Augmented Reality (AR) is technology that provides a view of real world environment with which has augmented or virtual components. In this thesis I explore how AR can be used for in-vehicle applications. AR systems can be used for navigation applications, combining this with capabilities like monitoring of data relevant to the driver could be a powerful tool for in vehicle assistance in automobiles. Some research is being done on using AR in automobiles for in-vehicle assistance using different technologies like see-through head mounted displays (HMD) or using projectors to use the windshield as a see through, heads up display (HUD). With all the research being done on AR display technologies in vehicles, a concern that arises is the possibility of the AR components distracting the driver from their normal driving activities. Less research has been done on comparing between different AR display types. For my master thesis, I investigated the effectiveness of three technologies to show AR content: • using an HMD similar to Google Glass • using the Windshield as a display • using a dashboard mounted console Based on the results of the study, it was found that the Windshield based AR HUD was superior over the fixed console based HDD (AR Lens) and the Head Mounted Display. The Windshield Display performed superior to the other displays in terms of ratio of number of navigational errors, maintaining the speed limit and ability to detect objects in the surrounding. It was also preferred by the subjects over the other displays. The AR Lens performed relatively average in the test study and performed higher than the HMD for most of the tests. The HMD showed comparatively better results than the AR Lens in maintaining the speed limit but was the least preferred by most of the participants

Highly Automated Driving, Secondary Task Performance, and Driver State

Objective: a driving simulator study compared the effect of changes in workload on performance in manual and highly automated driving. Changes in driver state were also observed by examining variations in blink patterns. Background: With the addition of a greater number of advanced driver assistance systems in vehicles, the driver’s role is likely to alter in the future from an operator in manual driving to a supervisor of highly automated cars. Understanding the implications of such advancements on drivers and road safety is important. Method: a total of 50 participants were recruited for this study and drove the simulator in both manual and highly automated mode. As well as comparing the effect of adjustments in driving-related workload on performance, the effect of a secondary Twenty Questions Task was also investigated. Results: in the absence of the secondary task, drivers’ response to critical incidents was similar in manual and highly automated driving conditions. The worst performance was observed when drivers were required to regain control of driving in the automated mode while distracted by the secondary task. Blink frequency patterns were more consistent for manual than automated driving but were generally suppressed during conditions of high workload. Conclusion: highly automated driving did not have a deleterious effect on driver performance, when attention was not diverted to the distracting secondary task. Application: as the number of systems implemented in cars increases, an understanding of the implications of such automation on drivers’ situation awareness, workload, and ability to remain engaged with the driving task is important