25,393 research outputs found

    Driving into the sunset: Supporting cognitive functioning in older drivers

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    Copyright @ 2011 Mark S. Young and David Bunce - This article has been made available through the Brunel Open Access Publishing Fund.The rise in the aging driver population presents society with a significant challenge-how to maintain safety and mobility on the roads. On the one hand, older drivers pose a higher risk of an at-fault accident on a mile-for-mile basis; on the other hand, independent mobility is a significant marker of quality of life in aging. In this paper, we review the respective literatures on cognitive neuropsychology and ergonomics to suggest a previously unexplored synergy between these two fields. We argue that this conceptual overlap can form the basis for future solutions to what has been called "the older driver problem." Such solutions could be found in a range of emerging driver assistance technologies offered by vehicle manufacturers, which have the potential to compensate for the specific cognitive decrements associated with aging that are related to driving.Support was received from the Leverhulme Trust, UK

    The Elderly: A Descriptive study of the perceptions of the elderly and their driving abilities

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    This study advances the understanding of older driver’s perceptions on their driving abilities. It focuses on examining a deeper and more detailed understanding of the different challenges the elderly are experiencing, in respect to driving and retention of their license. Additionally, it is important for others (such as family, doctors, social workers etc.) to interact with the elderly and assist them in receiving services if they are no longer capable of driving a vehicle, as well as talk with them if they are struggling with giving up their license and consequently their independence. Specifically, the analysis focuses on which gender is a safer driver, if older drivers believe there should be a proper age when driving should be terminated, and what proper steps they take in order to continue their own safety as well as the safety of others on the road. Conclusions underscore the implications for professional practice, policy and research when aging adults who continue to keep a drivers license when they no longer should, placing them in the category of being a concern for society. This sample shows that 83.3% still maintain an active driver’s license. The study shows that older drivers sometimes follow the legal speed limit. Findings from the study include sample shows that maintain an active driver’s license

    User expectations of partial driving automation capabilities and their effect on information design preferences in the vehicle

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    Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system's status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers' expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone. [Abstract copyright: Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

    Multisensory legal machines and legal act production

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    This paper expands on the concept of legal machine which was presented first at IRIS 2011 in Salzburg. The research subjects are (1) the creation of institutional facts by machines, and (2) multimodal communication of legal content to humans. Simple examples are traffic lights and vending machines. Complicated examples are computer-based information systems in organisations, form proceedings workflows, and machines which replace officials in organisations. The actions performed by machines have legal importance and draw legal consequences. Machines similarly as humans can be imposed status-functions of legal actors. The analogy of machines with humans is in the focus of this paper. Legal content can be communicated by machines and can be perceived by all of our senses. The content can be expressed in multimodal languages: textual, visual, acoustic, gestures, aircraft manoeuvres, etc. The concept of encapsulatation of human into machine is proposed. Herein humanintended actions are communicated through the machine’s output channel. Encapsulations can be compared with deities and mythical creatures that can send gods’ messages to people through the human mouth. This paper also aims to identify law production patterns by machines

    Human Factor Aspects of Traffic Safety

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    Analysis of Disengagements in Semi-Autonomous Vehicles: Drivers’ Takeover Performance and Operational Implications

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    This report analyzes the reactions of human drivers placed in simulated Autonomous Technology disengagement scenarios. The study was executed in a human-in-the-loop setting, within a high-fidelity integrated car simulator capable of handling both manual and autonomous driving. A population of 40 individuals was tested, with metrics for control takeover quantification given by: i) response times (considering inputs of steering, throttle, and braking); ii) vehicle drift from the lane centerline after takeover as well as overall (integral) drift over an S-turn curve compared to a baseline obtained in manual driving; and iii) accuracy metrics to quantify human factors associated with the simulation experiment. Independent variables considered for the study were the age of the driver, the speed at the time of disengagement, and the time at which the disengagement occurred (i.e., how long automation was engaged for). The study shows that changes in the vehicle speed significantly affect all the variables investigated, pointing to the importance of setting up thresholds for maximum operational speed of vehicles driven in autonomous mode when the human driver serves as back-up. The results shows that the establishment of an operational threshold could reduce the maximum drift and lead to better control during takeover, perhaps warranting a lower speed limit than conventional vehicles. With regards to the age variable, neither the response times analysis nor the drift analysis provide support for any claim to limit the age of drivers of semi-autonomous vehicles

    Automotive automation: Investigating the impact on drivers' mental workload

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    Recent advances in technology have meant that an increasing number of vehicle driving tasks are becoming automated. Such automation poses new problems for the ergonomist. Of particular concern in this paper are the twofold effects of automation on mental workload - novel technologies could increase attentional demand and workload, alternatively one could argue that fewer driving tasks will lead to the problem of reduced attentional demand and driver underload. A brief review of previous research is presented, followed by an overview of current research taking place in the Southampton Driving Simulator. Early results suggest that automation does reduce workload, and that underload is indeed a problem, with a significant proportion of drivers unable to effectively reclaim control of the vehicle in an automation failure scenario. Ultimately, this research and a subsequent program of studies will be interpreted within the framework of a recently proposed theory of action, with a view to maximizing both theoretical and applied benefits of this domain

    Looking to the future of visual assessment using driving simulation

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    Visual function is considered uniquely important for driving because it provides multiple critical sources of information that when combined ensures successful steering. There are, however, additional cognitive functions that are essential for the driver to be able to dynamically respond to the world and make predictions about the scene, as well as the behaviour of other road users. Given the complexity of driving through a busy urban environment it should be no surprise that simple tests of visual acuity seem to have weak explanatory power in terms of increased crash risk when driving. Despite this, fitness to drive still includes a formal assessment of visual acuity, with poor scores being used to revoke the driving licence. The 'gold standard' measure of driving ability remains the on-road driving test but compared to visual tests they are fairly uncontrolled, susceptible to great variation depending on the road conditions, and are unable to reliably detect subtle visual deficits. To address some of the limitations of these existing tests we use examples from two simulator settings (steering control and hazard detection) that highlight the merits of using driving simulation in order to control the visual conditions and probe specific functional capabilities of drivers. When used in conjunction with visual tests these methods will not only determine whether the core functions of driving are intact but also be able to provide richer feedback to individuals about the nature of their deficits. There are many exciting possibilities using simulation techniques to establish predictive relationships between routine visual testing and driving performance, ultimately aiming for better, more reliable assessment of fitness to drive

    The ‘frontal lobe’ project: A double-blind, randomized controlled study of the effectiveness of higher level driving skills training to improve frontal lobe (executive) function related driving performance in young drivers

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    The current study was undertaken in order to evaluate the effectiveness of higher level skills training on safe driving behaviour of 36 teenage drivers. The participants, who attended the Driver Training Research camp in Taupo (NZ) over a two week period, were 16 to 17 years old and had a valid restricted driver licence. The study focused on four main aims. Firstly, the behavioural characteristics of the sample and their attitudes to risk taking and driving were examined. Results showed that speeding was the most anticipated driving violation, and high levels of confidence were associated with a higher number of crashes and a greater propensity for risk taking. Many, often male participants, also rated their driving skills as superior to others and thought they would be less likely than others to be involved in an accident. Secondly, the relationship between driving performance and executive functioning, general ability and sustained attention was evaluated. Overall, better driving performance and more accurate self-evaluation of driving performance was related to higher levels of executive functions, in particular, working memory, and cognitive switching. In addition, higher general ability and greater ability to sustain attention were also linked to better performance on the driving related assessments. The third focus of this study was to compare the effects of both, higher level and vehicle handling skills training on driving performance, confidence levels and attitudes to risk. While both types of training improved direction control, speed choice and visual search, along with number of hazards detected and actions in relation to hazards, statistically significant improvement on visual search was seen only after higher level skills training. Vehicle handling skills training significantly improved direction control and speed choice. In addition, confidence levels in their driving skills were significantly lowered and attitudes to speeding, overtaking and close following had improved significantly in the participants after the higher level driving skills training. The final aspect to this study was to examine the effects of the training over the following 6 month period based on self-reported driving behaviour. The response rate of participants however, was not sufficient to reach any meaningful conclusion on any long-term training effects. A pilot study using GPSbased data trackers to assess post-training driving behaviour revealed some promising results for future driver training evaluation studies. The overall implications of the results are discussed in relation to improving the safety of young drivers in New Zealand
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