990 resultados para Advanced Driving Simulator


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This paper reports on the implementation of a non-invasive electroencephalography-based brain-computer interface to control functions of a car in a driving simulator. The system is comprised of a Cleveland Medical Devices BioRadio 150 physiological signal recorder, a MATLAB-based BCI and an OKTAL SCANeR advanced driving experience simulator. The system utilizes steady-state visual-evoked potentials for the BCI paradigm, elicited by frequency-modulated high-power LEDs and recorded with the electrode placement of Oz-Fz with Fz as ground. A three-class online brain-computer interface was developed and interfaced with an advanced driving simulator to control functions of the car, including acceleration and steering. The findings are mainly exploratory but provide an indication of the feasibility and challenges of brain-controlled on-road cars for the future, in addition to a safe, simulated BCI driving environment to use as a foundation for research into overcoming these challenges.

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The use of intelligent transport systems is proliferating across the Australian road network, particularly on major freeways. New technology allows a greater range of signs and messages to be displayed to drivers. While there has been a long history of human factors analyses of signage, no evaluation has been conducted on this novel, sometimes dynamic, signage or potential interactions when co-located. The purpose of this driving simulator study was to investigate drivers’ behavioural changes and comprehension resulting from the co-location of Lane Use Management Systems with static signs and (Enhanced) Variable Message Signs on Queensland motorways. A section of motorway was simulated, and nine scenarios were developed which presented a combination of signage cases across levels of driving task complexity. Two higher-risk road user groups were targeted for this research on an advanced driving simulator: older (65+ years, N=21) and younger (18-22 years, N=20) drivers. Changes in sign co-location and task complexity had small effect on driver comprehension of the signs and vehicle dynamics variables, including difference with the posted speed limit, headway, standard deviation of lane keeping and brake jerks. However, increasing the amount of information provided to drivers at a given location (by co-locating several signs) increased participants’ gaze duration on the signs. With co-location of signs and without added task complexity, a single gaze was over 2s for more than half of the population tested for both groups, and up to 6 seconds for some individuals.

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Distraction resulting from mobile phone use whilst driving has been shown to increase the reaction times of drivers, thereby increasing the likelihood of a crash. This study compares the effects of mobile phone conversations on reaction times of drivers responding to traffic events that occur at different points in a driver’s field of view. The CARRS-Q Advanced Driving Simulator was used to test a group of young drivers on various simulated driving tasks including a traffic event that occurred within the driver’s central vision—a lead vehicle braking suddenly—and an event that occurred within the driver’s peripheral—a pedestrian entering a zebra crossing from a footpath. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), and while engaged in hands-free and handheld phone conversations. The drivers were aged between 21 to 26 years and split evenly by gender. Differences in reaction times for an event in a driver’s central vision were not statistically significant across phone conditions, probably due to a lower speed selection by the distracted drivers. In contrast, the reaction times to detect an event that originated in a distracted driver’s peripheral vision were more than 50% longer compared to the baseline condition. A further statistical analysis revealed that deterioration of reaction times to an event in the peripheral vision was greatest for distracted drivers holding a provisional licence. Many critical events originate in a driver’s periphery, including vehicles, bicyclists, and pedestrians emerging from side streets. A reduction in the ability to detect these events while distracted presents a significant safety concern that must be addressed.

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The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q Advanced Driving Simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver’s peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21 to 26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver’s age, license type (Provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.

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Safety at railway level crossings (RLX) is one part of a wider picture of safety within the whole transport system. Governments, the rail industry and road organisations have used a variety of countermeasures for many years to improve RLX safety. New types of interventions are required in order to reduce the number of crashes and associated social costs at railway crossings. This paper presents the results of a large research program which aimed to assess the effectiveness of emerging Intelligent Transport Systems (ITS) interventions, both on-road and in-vehicle based, to improve the safety of car drivers at RLXs in Australia. The three most promising technologies selected from the literature review and focus groups were tested in an advanced driving simulator to provide a detailed assessment of their effects on driver behaviour. The three interventions were: (i) in-vehicle visual warning using a GPS/smartphone navigation-like system, (ii) in-vehicle audio warning and; (iii) on-road intervention known as valet system (warning lights on the road surface activated as a train approaches). The effects of these technologies on 57 participants were assessed in a systematic approach focusing on the safety of the intervention, effects on the road traffic around the crossings and driver’s acceptance of the technology. Given that the ITS interventions were likely to provide a benefit by improving the driver’s awareness of the crossing status in low visibility conditions, such conditions were investigated through curves in the track before arriving at the crossing. ITS interventions were also expected to improve driver behaviour at crossings with high traffic (blocking back issue), which were also investigated at active crossings. The key findings are: (i) interventions at passive crossings are likely to provide safety benefits; (ii) the benefits of ITS interventions on driver behaviour at active crossings are limited; (iii) the trialled ITS interventions did not show any issues in terms of driver distraction, driver acceptance or traffic delays; (iv) these interventions are easy to use, do not increase driver workload substantially; (v) participants’ intention to use the technology is high and; (vi) participants saw most value in succinct messages about approaching trains as opposed to knowing the RLX locations or the imminence of a collision with a train.

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Braking is a crucial driving task with a direct relationship with crash risk, as both excess and inadequate braking can lead to collisions. The objective of this study was to compare the braking profile of young drivers distracted by mobile phone conversations to non-distracted braking. In particular, the braking behaviour of drivers in response to a pedestrian entering a zebra crossing was examined using the CARRS-Q Advanced Driving Simulator. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free, and handheld. In addition to driving the simulator, each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The drivers were 18–26 years old and split evenly by gender. A linear mixed model analysis of braking profiles along the roadway before the pedestrian crossing revealed comparatively increased decelerations among distracted drivers, particularly during the initial 20 kph of deceleration. Drivers’ initial 20 kph deceleration time was modelled using a parametric accelerated failure time (AFT) hazard-based duration model with a Weibull distribution with clustered heterogeneity to account for the repeated measures experiment design. Factors found to significantly influence the braking task included vehicle dynamics variables like initial speed and maximum deceleration, phone condition, and driver-specific variables such as licence type, crash involvement history, and self-reported experience of using a mobile phone whilst driving. Distracted drivers on average appear to reduce the speed of their vehicle faster and more abruptly than non-distracted drivers, exhibiting excess braking comparatively and revealing perhaps risk compensation. The braking appears to be more aggressive for distracted drivers with provisional licenses compared to drivers with open licenses. Abrupt or excessive braking by distracted drivers might pose significant safety concerns to following vehicles in a traffic stream.

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Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18 to 26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 seconds in time headway when a driver is engaged in hands-free phone conversation and a 0.75 seconds increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

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Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

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Driving on an approach to a signalized intersection while distracted is relatively risky, as potential vehicular conflicts and resulting angle collisions tend to be relatively more severe compared to other locations. Given the prevalence and importance of this particular scenario, the objective of this study was to examine the decisions and actions of distracted drivers during the onset of yellow lights. Driving simulator data were obtained from a sample of 69 drivers under baseline and handheld cell phone conditions at the University of Iowa – National Advanced Driving Simulator. Explanatory variables included age, gender, cell phone use, distance to stop-line, and speed. Although there is extensive research on drivers’ responses to yellow traffic signals, the examinations have been conducted from a traditional regression-based approach, which do not necessary provide the underlying relations and patterns among the sampled data. In this paper, we exploit the benefits of both classical statistical inference and data mining techniques to identify the a priori relationships among main effects, non-linearities, and interaction effects. Results suggest that the probability of yellow light running increases with the increase in driving speed at the onset of yellow. Both young (18–25 years) and middle-aged (30–45 years) drivers reveal reduced propensity for yellow light running whilst distracted across the entire speed range, exhibiting possible risk compensation during this critical driving situation. The propensity for yellow light running for both distracted male and female older (50–60 years) drivers is significantly higher. Driver experience captured by age interacts with distraction, resulting in their combined effect having slower physiological response and being distracted particularly risky.

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Travel speed is one of the most critical parameters for road safety; the evidence suggests that increased vehicle speed is associated with higher crash risk and injury severity. Both naturalistic and simulator studies have reported that drivers distracted by a mobile phone select a lower driving speed. Speed decrements have been argued to be a risk compensatory behaviour of distracted drivers. Nonetheless, the extent and circumstances of the speed change among distracted drivers are still not known very well. As such, the primary objective of this study was to investigate patterns of speed variation in relation to contextual factors and distraction. Using the CARRS-Q high-fidelity Advanced Driving Simulator, the speed selection behaviour of 32 drivers aged 18-26 years was examined in two phone conditions: baseline (no phone conversation) and handheld phone operation. The simulator driving route contained five different types of road traffic complexities, including one road section with a horizontal S curve, one horizontal S curve with adjacent traffic, one straight segment of suburban road without traffic, one straight segment of suburban road with traffic interactions, and one road segment in a city environment. Speed deviations from the posted speed limit were analysed using Ward’s Hierarchical Clustering method to identify the effects of road traffic environment and cognitive distraction. The speed deviations along curved road sections formed two different clusters for the two phone conditions, implying that distracted drivers adopt a different strategy for selecting driving speed in a complex driving situation. In particular, distracted drivers selected a lower speed while driving along a horizontal curve. The speed deviation along the city road segment and other straight road segments grouped into a different cluster, and the deviations were not significantly different across phone conditions, suggesting a negligible effect of distraction on speed selection along these road sections. Future research should focus on developing a risk compensation model to explain the relationship between road traffic complexity and distraction.

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The paper presents initial findings from an Austroads funded project NT1782 Ability to Absorb Information through Electronic and Static Signs. The paper aims to investigate how easily messages displayed on co-located signs can be absorbed, and if drivers can absorb messages and take appropriate action without any adverse impact on the safety and efficiency of driving. Co-location of three types of signs under motorway conditions was investigated: direction signs (DS), variable message signs (VMS) and variable speed limits/lane control signs (VSL/LCS). The authors reviewed global wide practices and research evidence on different types of sign co-locations. It was found that dual co-location of VSL/LCS, VMS and/or DS is a practical arrangement which has been widely practised overseas and in Australia. Triple co-location of VSL/LCS, VMS and DS is also practised overseas but is still new to the Australian driving community. The NT1782 project also employed an advanced driving simulator (ADS) to further investigate the possible impacts of sign co-location on drivers’ responses in an emergency situation and there were no obviously adverse impacts have been identified from the ADS study. The authors consolidated all findings and concluded that although there is no clear evidence showing that triple co-location gives rise to riskier behaviour, this proposition should be viewed with caution. Further evaluation of triple co-location in a real-life setting is called for.

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While mobile phones have become ubiquitous in modern society, the use of mobile phones while driving is increasing at an alarming rate despite the associated crash risks. A significant safety concern is that driving while distracted by a mobile phone is more prevalent among young drivers, a less experienced driving cohort with elevated crash risk. The objective of this study was to examine the gap acceptance behavior of distracted young drivers at roundabouts. The CARRS-Q Advanced Driving Simulator was used to test participants on a simulated gap acceptance scenario at roundabouts. Conflicting traffic from the right approach of a four-legged roundabout were programmed to have a series of vehicles having the gaps between them proportionately increased from two to six seconds. Thirty-two licensed young drivers drove the simulator under three phone conditions: baseline (no phone conversation), hands-free and handheld phone conversations. Results show that distracted drivers started responding to the gap acceptance scenario at a distance closer to the roundabout and approached the roundabout at slower speeds. They also decelerated at faster rates to reduce their speeds prior to gap acceptance compared to non-distracted drivers. Although accepted gap sizes were not significantly different across phone conditions, differences in the safety margins at various gap sizes—measured by Post Encroachment Time (PET) between the driven vehicle and the conflicting vehicle—were statistically significant across phone conditions. PETs for distracted drivers were smaller across different gap sizes, suggesting a lower safety margin taken by distracted drivers compared to non-distracted drivers. The results aid in understanding how cognitive distraction resulting from mobile phone conversations while driving influences driving behavior during gap acceptance at roundabouts.

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Passively protected railway crossings are a major rail safety issue in Australia. Such crossings cannot be upgraded as such crossings are too numerous and the cost involved is prohibitive. Advanced Driver Assistance Systems (ADAS) have been shown to improve road safety and are widely used. These systems could be a solution to improve safety of passively protected crossings at a lower cost. Such complementary ADAS could result in driver’s over-trust due to the absence of Humane Machine Interface reflecting the quality of the information or the state of the ADAS (failure status). This paper demonstrates that driver’s exposure to crossing exhibiting fail-safe and non-fail safe properties could result in improperly allocating trust between technologies. We conducted a driving simulator study where participants (N=58) were exposed to three types of level crossing warning system on passive and active crossings. The results show that a significant proportion of participants over-trust the ADAS. Such drivers exhibit the same driving performance with the ADAS as when exposed to infrastructure based active crossing protection. They do not take the necessary safety precautions as they have a faster speed approach, reduced number of gaze toward the rail tracks and fail to stop at the crossing.

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Social and psychological theories have provided a plethora of evidence showing that the physical difficulty to express appropriate social interactions between drivers expresses itself in aggression, selfish driving and anti-social behaviour. Therefore there is a need to improve interactions between drivers and allow clearer collective decision making between them. Personal characteristics and the driving situations play strong roles in driver’s aggression. Our approach is centered around the driving situation as opposed to focusing on personality characteristics. It examines aggression and manipulates contextual variables such as driver’s eye contact exchanges. This paper presents a new unobtrusive in-vehicle system that aims at communicating drivers’ intentions, elicit social responses and increasing mutual awareness. It uses eye gaze as a social cue to affect collective decision making with the view to contribute to safe driving. The authors used a driving simulator to design a case control experiment in which eye gaze movements are conveyed with an avatar. Participants were asked to drive through different types of intersections. An avatar representing the head of the other driver was displayed and driver behaviour was analysed. Significant eye gaze pattern difference where observed when an avatar was displayed. Drivers cautiously refer to the avatar when information is required on the intention of others (e.g. when they do not have the right of way). The majority of participants reported the perception of “being looked at”. The number of glances and time spent gazing at the avatar did not indicate an unsafe distraction by standards of in-vehicle device ergonomic design. Avatars were visually consulted primarily in less demanding driving situations, which underlines their non-distractive nature.