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Driving Simulation

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Total results: 232

Impacts of touch screen size, user interface design, and subtask boundaries on in-car task’s visual demand and driver distraction

Year: 2020

Authors: H Grahn,T Kujala

Visual distraction by secondary in-car tasks is a major contributing factor in traffic incidents. In-car user interface design may mitigate these negative effects but to accomplish this, design factors’ visual distraction potential should be better understood. The effects of touch screen size, user interface design, and subtask boundaries on in-car task's visual demand and visual distraction potential were studied in two driving simulator experiments with 48 participants. Multilevel modeling was utilized to control the visual demands of driving and individual differences on in-car glance durations. The 2.5” larger touch screen slightly decreased the in-car glance durations and had a diminishing impact on both visual demand and visual distraction potential of the secondary task. Larger relative impact was discovered concerning user interface design: an automotive-targeted application decreased the visual demand and visual distraction potential of the in-car tasks compared to the use of regular smartphone applications. Also, impact of subtask boundaries was discovered: increase in the preferred number of visual or visual-manual interaction steps during a single in-car glance (e.g., pressing one button vs. typing one word) increased the duration of the in-car glance and its visual distraction potential. The findings also emphasize that even if increasing visual demand of a task – as measured by in-car glance duration or number of glances – may increase its visual distraction potential, these two are not necessarily equal.

Simulator
Software

2 versions available

Improving drivers’ hazard perception and performance using a less visually-demanding interface

Year: 2020

Authors: G Cohen

In-vehicle devices and infotainment systems occasionally lead to driver distraction, and as a result, increase the risk of missing on-road information. In the current study, a novel multi-touch interface for an in-vehicle infotainment system was evaluated, which potentially requires less visual attention and thus may reduce distraction and increase safety. The interface was compared with a functionally similar control interface in terms of hazard perception metrics and mental workload. Twenty-two participants drove a simulated route once with each system. During each drive, which included eight potentially-hazardous scenarios, participants were instructed to interact with one of the in-vehicle interfaces to perform phone calls or to navigate to specified destinations. Eye-gaze data were collected throughout the drive to evaluate whether participants detected the hazards while interacting with the in-vehicle interface, how much time they needed to identify them, and for how long they engaged with the secondary task. Additionally, after each drive, participants completed a NASA R-TLX questionnaire to evaluate their subjective workload during their engagement with the secondary tasks. Participants using the multi-touch interface needed less time to complete each secondary task and were quicker at identifying potential hazards around them. However, the probability of detecting hazards was similar for both interfaces. Finally, when using the multi-touch interface, participants reported lower subjective workload. The use of a multi-touch interface was found to improve drivers’ performance in terms of identifying hazards quicker than the control condition. The road safety and driver distraction implications of this novel interface are discussed.

Simulator
Software

10 versions available

Multimodal features for detection of driver stress and fatigue

Year: 2020

Authors: A Němcová, V Svozilová, K Bucsuházy

Driver fatigue and stress significantly contribute to higher number of car accidents worldwide. Although, different detection approaches have been already commercialized and used by car producers (and third party companies), research activities in this field are still needed in order to increase the reliability of these alert systems. Also, in the context of automated driving, the driver mental state assessment will be an important part of cars in future. This paper presents state-of-the-art review of different approaches for driver fatigue and stress detection and evaluation. We describe in details various signals (biological, car and video) and derived features used for these tasks and we discuss their relevance and advantages. In order to make this review complete, we also describe different datasets, acquisition systems and experiment scenarios.

Eye Tracking Glasses
Simulator

3 versions available

New technologies for improving driver response efficiency in risk prevention from traffic environment

Year: 2020

Authors: O Lindov,A Omerhodžić

Risk in traffic or traffic environment is constant, always present and can never be completely eliminated. In urban areas, the highest percentage of risky traffic situations is related to pedestrians and their specificities in traffic participation. Pedestrians as vulnerable road users participate in different functions, i.e. behaviors and modes of movement. Due to the flexibility and the ability to change speeds and movements relatively easily, pedestrians often cause incident and risky traffic situations. The timely detection of pedestrians by motor vehicle drivers is one of the key parameters that directly affects the available response capabilities of motor vehicle drivers to take safety actions in order to avoid pedestrian conflict. This paper presents the basics of the concept and capabilities of new technologies for monitoring and exploring drivers’ views in order to generalize conclusions to improve the effectiveness of drivers’ response in the prevention of traffic risks. Custom hardware and software components will be used to monitor the driver’s view for research and analysis purposes.

Eye Tracking Glasses
Software

1 version available:

Research on drivers’ visual characteristics in different curvatures and turning conditions of the extra-long urban underwater tunnels

Year: 2020

Authors: F Jiao, Z Du,S Wang, L Yang, Y Ni

In order to study driver’s visual characteristics under different curvatures and turning conditions in extra-long urban underwater tunnels, fixation and saccade were herein regarded as the main research objectives. In this study, we carried out real vehicle testing on curved sections with 5 different radii and straight sections of the extra-long urban underwater tunnels. The driver’s fixation characteristics were studied by using fixation distribution, fixation time, fixation frequency, fixation time ratio, and frequency ratio. The driver’s saccade characteristics were investigated by selecting the saccade angle, saccade time, saccade frequency, saccade time ratio, and frequency ratio. Accordingly, mathematical models of the driver’s fixation time, fixation frequency, saccade time, and saccade frequency under different curvatures and turning conditions in the extra-long urban underwater tunnel were established. Combined with the change of visual distance, sight distance, and sight zone, driver’s visual characteristics in the extra-long urban underwater tunnel were further analyzed. The results demonstrated that the smaller the radius of the tunnel, the more focused driver’s fixation time, the greater the psychological pressure, and the lower the safety when driving. Under the same radius, driver’s tension and risk factors were higher during turning left, while driver’s driving mentality was more relaxed and driving situation was further stable in the right-turn.

Eye Tracking Glasses
Simulator

2 versions available

Scanpath analysis into the wild: the spatiotemporal distribution of fixations as an indicator of driver’s mental workload

Year: 2020

Authors: FD Nocera, O Ricciardi, S Mastrangelo

Past studies using the distribution of eye fixations as an indicator of mental workload are limited to simulations and laboratory tasks. Hence, this assessment strategy has not yet been proven useful in real-world settings. In order to bridge this gap, in this study eye movements of a group of individuals were recorded while driving a car in a suburban road. Drivers’ scanpaths during driving and during driving while performing mundane secondary tasks were compared in this study. A more grouped pattern of fixations was expected in the dual-task condition than in the driving-only condition. As expected, results showed the effectiveness the spatiotemporal distribution of fixations in correctly discriminating between task load conditions, therefore indicating its usefulness for assessing mental workload also in complex real-world tasks.

Eye Tracking Glasses
Software

4 versions available

Take-Over Time Modeling and Prediction for Conditional Driving Automation

Year: 2020

Authors: S Hwang

Conditional driving automation represents a pivotal milestone in the journey towards fully autonomous systems. At this intermediate level of automation, human drivers are periodically required to take over control from the automated system when specific conditions or scenarios are encountered. One of the key challenges in ensuring safety and effectiveness in such systems is understanding and predicting the human driver's take-over time (TOT) - the time it takes for a driver to respond to a takeover request. This dissertation focuses on modeling and predicting TOT by examining various factors that influence human performance during takeover events. By leveraging data from driving simulators and on-road experiments, the research delves into the effects of driver awareness, driving environment complexity, and the nature of the takeover request on TOT. The findings provide crucial insights for designing better human-machine interfaces and optimizing the transition process in conditional driving automation.

Eye Tracking Glasses
Simulator

2 versions available

The effect of visual HMIs of a system assisting manual drivers in manoeuvre coordination in system limit and system failure situations

Year: 2020

Authors: AK Kraft, C Maag, MI Cruz,M Baumann

Ambiguous situations in traffic often require communication and cooperation between road users. In order to resolve these situations and increase cooperative driving behavior in situations of merging or turning left, manual drivers could be assisted by an advanced driver assistance system (ADAS) for cooperative driving. This simulator study investigated the behavior of drivers confronted with system limits and failures of such a system. The ADAS used in this study informed the driver about an upcoming cooperation situation and gave advice on how to behave (e.g. reduce speed, change lane). Two test situations were implemented: a system freeze and an unexpected event, which could not be detected by the system. In order to find the most fitting HMI solution, the place of presentation (head-up display (HUD) vs. instrument cluster) as well as the form of presentation (dynamic vs. symbolic) were varied. The results indicated that the most fitting HMI solution to support the driver in a complex coordinated driving situation is a dynamic HUD, mainly due to the positive effect on glance behavior. However, advantages of both forms of presentation were revealed, as each form of presentation increased the probability of recognition for one of the test situations. The fewest collisions took place with the dynamic form of presentation.

Simulator
Software

6 versions available

The effects of a predictive HMI and different transition frequencies on acceptance, workload, usability, and gaze behavior during urban automated driving

Year: 2020

Authors: T Hecht, S Kratzert,K Bengler

Automated driving research as a key topic in the automotive industry is currently undergoing change. Research is shifting from unexpected and time-critical take-over situations to human machine interface (HMI) design for predictable transitions. Furthermore, new applications like automated city driving are getting more attention and the ability to engage in non-driving related activities (NDRA) starting from SAE Level 3 automation poses new questions to HMI design. Moreover, future introduction scenarios and automated capabilities are still unclear. Thus, we designed, executed, and assessed a driving simulator study focusing on the effect of different transition frequencies and a predictive HMI while freely engaging in naturalistic NDRA. In the study with 33 participants, we found transition frequency to have effects on workload and acceptance, as well as a small impact on the usability evaluation of the system. Trust, however, was not affected. The predictive HMI was used and accepted, as can be seen by eye-tracking data and the post-study questionnaire, but could not mitigate the above-mentioned negative effects induced by transition frequency. Most attractive activities were window gazing, chatting, phone use, and reading magazines. Descriptively, window gazing and chatting gained attractiveness when interrupted more often, while reading magazines and playing games were negatively affected by transition rate.

Eye Tracking Glasses
Simulator

7 versions available

The impact of auditory continual feedback on take-overs in Level 3 automated vehicles

Year: 2020

Authors: G Cohen

Objective: To implement auditory continual feedback into the interface design of a Level 3 automated vehicle and to test whether gaze behavior and reaction times of drivers improved in take-over situations. Background: When required to assume manual control in take-over situations, drivers of Level 3 automated vehicles are less likely than conventional drivers to spot potential hazards, and their reaction time is longer. Therefore, it is crucial that the interface of Level 3 automated vehicles will be designed to improve drivers’ performance in take-over situations. Method: In two experiments, participants drove a simulated route in a Level 3 automated vehicle for 35 min with one imminent take-over event. Participants’ gaze behavior and performance in an imminent take-over event were monitored under one of three auditory interface designs: (1) Continual feedback. A system that provides verbal driving-related feedback; (2) Persistent feedback. A system that provides verbal driving-related feedback and a persistent beep; and (3) Chatter feedback. A system that provides verbal non-driving-related feedback. Also, there was a control group without feedback. Results: Under all three auditory feedback designs, the number of drivers' on-road glances increased compared to no feedback, but none of the designs shortened reaction time to the imminent event. Conclusion: Increasing the number of on-road glances during automated driving does not necessarily improve drivers’ attention to the road and their reaction times during take-overs. Application: Possible implications for the effectiveness of auditory continual feedback should be considered when designing interfaces for Level 3 automated vehicles.

Eye Tracking Glasses
Simulator

7 versions available