driving task
Recently Published Documents


TOTAL DOCUMENTS

345
(FIVE YEARS 100)

H-INDEX

31
(FIVE YEARS 3)

2022 ◽  
Vol 19 (1) ◽  
pp. 1-18
Author(s):  
Björn Blissing ◽  
Fredrik Bruzelius ◽  
Olle Eriksson

Driving simulators are established tools used during automotive development and research. Most simulators use either monitors or projectors as their primary display system. However, the emergence of a new generation of head-mounted displays has triggered interest in using these as the primary display type. The general benefits and drawbacks of head-mounted displays are well researched, but their effect on driving behavior in a simulator has not been sufficiently quantified. This article presents a study of driving behavior differences between projector-based graphics and head-mounted display in a large dynamic driving simulator. This study has selected five specific driving maneuvers suspected of affecting driving behavior differently depending on the choice of display technology. Some of these maneuvers were chosen to reveal changes in lateral and longitudinal driving behavior. Others were picked for their ability to highlight the benefits and drawbacks of head-mounted displays in a driving context. The results show minor changes in lateral and longitudinal driver behavior changes when comparing projectors and a head-mounted display. The most noticeable difference in favor of projectors was seen when the display resolution is critical to the driving task. The choice of display type did not affect simulator sickness nor the realism rated by the subjects.


2022 ◽  
Vol 12 (2) ◽  
pp. 807
Author(s):  
Huafei Xiao ◽  
Wenbo Li ◽  
Guanzhong Zeng ◽  
Yingzhang Wu ◽  
Jiyong Xue ◽  
...  

With the development of intelligent automotive human-machine systems, driver emotion detection and recognition has become an emerging research topic. Facial expression-based emotion recognition approaches have achieved outstanding results on laboratory-controlled data. However, these studies cannot represent the environment of real driving situations. In order to address this, this paper proposes a facial expression-based on-road driver emotion recognition network called FERDERnet. This method divides the on-road driver facial expression recognition task into three modules: a face detection module that detects the driver’s face, an augmentation-based resampling module that performs data augmentation and resampling, and an emotion recognition module that adopts a deep convolutional neural network pre-trained on FER and CK+ datasets and then fine-tuned as a backbone for driver emotion recognition. This method adopts five different backbone networks as well as an ensemble method. Furthermore, to evaluate the proposed method, this paper collected an on-road driver facial expression dataset, which contains various road scenarios and the corresponding driver’s facial expression during the driving task. Experiments were performed on the on-road driver facial expression dataset that this paper collected. Based on efficiency and accuracy, the proposed FERDERnet with Xception backbone was effective in identifying on-road driver facial expressions and obtained superior performance compared to the baseline networks and some state-of-the-art networks.


Author(s):  
Michaela M. Keener ◽  
Kimberly I. Tumlin ◽  
Nicholas R. Heebner

Abstract Background Loss of hand strength is a predictor of mortality in aging populations. Despite reliance on the hands to participate in equestrian driving activity, no existing studies focus on associations of hand strength to athletic performance. Therefore, this study 1) established baseline handgrip of equestrian combined drivers in standing and task-specific positions, 2) determined endurance of task-specific handgrip, 3) compared handgrip strength to normative data, and 4) evaluated associations of handgrip and equestrian-specific variables. Methods There were 51 combined drivers (9 males, 42 females) ages 21–78 who completed a survey, standing handgrip, and grip strength and endurance in a task-specific position. Sixty-three percent of participants were 50 years or older. The dynamometer grip bar was normalized by hand size for standing tests; to duplicate sport-specific tasks, the bar was set to the closest setting. Significances were determined at p < 0.05. Results Drivers with more than 30 years of experience demonstrated highest summed standing (73.1 ± 5.2 kg) and summed sitting (59.9 ± 6.3 kg) grip strength. Females 60-years and older had greater handgrip endurance (Χ2 = 8.323, df = 2, p = .0156) in non-dominant (left) hands. Males (60%) reported more cold weather fatigue than females. Glove wearing was associated with bilateral endurance balance; a higher proportion of endurance balance between dominant and non-dominant (49% high-high and 29% low-low; Χ2 = 11.047, df = 1, p = .0009) was realized. There were no associations of handgrip and prior injury. Conclusions Our results have implications in understanding task-specific and normative grip strengths in aging equestrian populations. Bilateral balance in handgrip strength and endurance is important particularly in maintaining strength in non-dominant hands over time. Equestrian driving sport promotes greater endurance in older females. Strength can be improved by participating in combined driving, and engagement in this sport over several years’ benefits hand strength over time. This cohort of equestrian participants provides evidence that participating in hand-specific activities promotes greater strength, which has been previously shown to improve aging outcomes.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giovanni M. Di Liberto ◽  
Michele Barsotti ◽  
Giovanni Vecchiato ◽  
Jonas Ambeck-Madsen ◽  
Maria Del Vecchio ◽  
...  

AbstractDriving a car requires high cognitive demands, from sustained attention to perception and action planning. Recent research investigated the neural processes reflecting the planning of driving actions, aiming to better understand the factors leading to driving errors and to devise methodologies to anticipate and prevent such errors by monitoring the driver’s cognitive state and intention. While such anticipation was shown for discrete driving actions, such as emergency braking, there is no evidence for robust neural signatures of continuous action planning. This study aims to fill this gap by investigating continuous steering actions during a driving task in a car simulator with multimodal recordings of behavioural and electroencephalography (EEG) signals. System identification is used to assess whether robust neurophysiological signatures emerge before steering actions. Linear decoding models are then used to determine whether such cortical signals can predict continuous steering actions with progressively longer anticipation. Results point to significant EEG signatures of continuous action planning. Such neural signals show consistent dynamics across participants for anticipations up to 1 s, while individual-subject neural activity could reliably decode steering actions and predict future actions for anticipations up to 1.8 s. Finally, we use canonical correlation analysis to attempt disentangling brain and non-brain contributors to the EEG-based decoding. Our results suggest that low-frequency cortical dynamics are involved in the planning of steering actions and that EEG is sensitive to that neural activity. As a result, we propose a framework to investigate anticipatory neural activity in realistic continuous motor tasks.


Vehicles ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 821-839
Author(s):  
Anil Erkan ◽  
Sebastian Babilon ◽  
David Hoffmann ◽  
Timo Singer ◽  
Tsoni Vitkov ◽  
...  

The purpose of this work is to determine as a function of velocity the minimal roadway luminance that is required to be judged as being bright enough for a driver to perform a nighttime driving task with an adequate feeling of safety. In this context, it shall also be evaluated which areas of the vehicle forefield are most crucial for the driver’s general brightness perception. A field study with 23 subjects and dimmable LED headlights was conducted, in which the subjects were given the task to assess their perceived brightness for different luminance levels caused by the headlights’ low-beam distribution in the vehicle’s forefield on a 5-step rating scale. The experiments were repeated for three different driving velocities of 0 km h−1 (static case), 30 km h−1, and 60 km h−1, respectively. Results for the static case indicate that, for the roadway to be perceived as bright enough by 50% of the subjects, an average roadway luminance of 0.88 cd m−2 is required in an area up to 32 m in front of the vehicle. Furthermore, a significant effect of driving speed is observed. For example, at 60 km h−1, the luminance must be increased to 1.54 cd m−2 to be still perceived as sufficiently bright by 50% of the subjects.


2021 ◽  
Vol 16 ◽  
pp. 288-296
Author(s):  
Panagiotis Lemonakis ◽  
Eleni Misokefalou ◽  
Nikolaos Eliou ◽  
Myrofora Koroni

While car drivers consist the vast majority of road users, motorcycle drivers are considered among the most vulnerable ones with significant participation in accidents. The present study investigates the role of elements that permanently exist in the road environment and affect motorcyclist’s behavior since their usefulness requires visual contact between them and the rider during a certain period of time. Therefore, on such an occasion the riders do not monitor the road ahead which is considered as a fundamental driving task and hence the visual search and scan is not directed to the frontal view. The main objective of this paper is to identify and evaluate certain aspects of motorcyclists’ behavior influenced by exterior factors, such as observation of vertical signage or advertisement signs, by using naturalistic data. Motorcyclist’s visual behavior is evaluated via a continuous recording of his gaze, which acts as the main indicator regarding the rider’s performance, with the use of special equipment under naturalistic riding conditions. The selection of a naturalistic method permits continuous data recording, producing real-time data. Thus, the results are reliable and valid to the maximum possible extent. This research is based on a medium-scale experimental procedure that took place in three different road sections in Western Greece. A number of 11 motorcyclists participated in the study. The present research may be used as a tool to improve road infrastructure and to identify attitudes that pose a risk to rider’s safety aiming to the creation of a safer road environment, which will lead to less fatal and serious accidents.


2021 ◽  
Author(s):  
Fatima Maria Felisberti ◽  
Thiago P Fernandes

Background: High cognitive load during driving is often disruptive and one of the main causes of road accidents. Surprisingly, we know little about the effect (if any) of cognitive load immediately before driving, and even less about the effect of driving (with its own cognitive load) on subsequent performance in cognitive tasks. Method: The effect of cognitive load on a subsequent driving task was examined in Study 1 (n = 31). Participants completed a battery of cognitive tests with low or moderate cognitive demands and their driving performance on a simulator was assessed on two consecutive days (speed, distance from the car ahead, and lane keeping ability). Study 2 (n = 98) examined the effect of a cognitively demanding driving task on the performance of follow up cognitive task, the multi-source interference task (MSIT). In that study, accuracy, and reaction time to MSIT were compared in two conditions: no driving vs post-driving.Results: A moderate level of cognitive load pre-driving led to a modest increase in the distance kept from the car ahead, while a demanding period of driving led to a significant increase in cognitive performance when compared to the control condition (e.g., prior driving).Conclusion: The findings suggest that increases in cognitive processing during periods of demanding mental activity mobilise attentional processes which are likely to remain active for a short period of time benefiting subsequent cognitive performance.


2021 ◽  
Vol 15 ◽  
Author(s):  
Sayako Ueda ◽  
Toshihisa Sato ◽  
Takatsune Kumada

The partial restriction of a driver’s visual field by the physical structure of the car (e.g., the A-pillar) can lead to unsafe situations where steering performance is degraded. Drivers require both environmental information and visual feedback regarding operation consequences. When driving with a partially restricted visual field, and thus restricted visual feedback, drivers may predict operation consequences using a previously acquired internal model of a car. To investigate this hypothesis, we conducted a tracking and driving task in which visual information was restricted to varying degrees. In the tracking task, participants tracked a moving target on a computer screen with visible and invisible cursors. In the driving task, they drove a real car with or without the ability to see the distant parts of a visual field. Consequently, we found that the decrease in tracking performance induced by visual feedback restriction predicted the decrease in steering smoothness induced by visual field restriction, suggesting that model-based prediction was used in both tasks. These findings indicate that laboratory-based task performance can be used to identify drivers with low model-based prediction ability whose driving behavior is less optimal in restricted vision scenarios, even before they obtain a driver’s license. However, further studies are required to examine the underlying neural mechanisms and to establish the generalizability of these findings to more realistic settings.


2021 ◽  
Vol 12 ◽  
Author(s):  
Carlos Hugo Criado del Valle

Habitual offender drivers are required to recover points lost on their driving license by attending reeducation courses, an experience that may, upon reflection of the incident in question, induce feelings of guilt or shame for the infractions they committed. A simulated driving task studied optimistic offender drivers to analyze the extent to which the controllability of the situational context influenced their use of internal and external factors in counterfactual thoughts and emotions such as guilt and shame. The study involved 160 drivers, of whom 54 were categorized as repeat offender drivers while 106 drivers attended courses for advanced professional driving licenses. The participants drove along a route in a driving simulator, which had been previously adjusted for the difficulty to generate a perception of high or low control. Based on the outcome obtained by the participants in this stage, each driver had to report which resources they required to improve their outcomes. Different factor ANOVAs were used to analyze our findings. The results indicated that optimistic offenders, unlike other groups (i.e., optimistic non-offender and pessimistic non-offender), thought that their results could have been better if external factors had been present (i.e., upward counterfactuals), both under conditions of high and low control. They believed their results would have been worse had it not been for their internal resources (i.e., downward counterfactuals), especially under conditions of low control. Concerning emotions of guilt and shame, offender optimists had the lowest values in both conditions compared with the other groups. We may contend that optimistic offender drivers thought they could have obtained better outcomes if external factors had been involved. In the low control condition, they justified that if it were not for such internal skills, their results could have been worse. When they generated such thoughts, the emotions of guilt and shame were minimal.


2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A50-A50
Author(s):  
I Marando ◽  
R Matthews ◽  
L Grosser ◽  
C Yates ◽  
S Banks

Abstract Sustained operations expose individuals to long work periods, which deteriorates their ability to sustain attention. Biological factors, including sleep deprivation and time of day, have been shown to play a critical role in the ability to sustain attention. However, a gap in the literature exists regarding external factors, such as workload. Therefore, the aim of this study was to investigate the combined effect of sleep deprivation, time of day, and workload on sustained attention. Twenty-one participants (18–34y, 10 F) were exposed to 62 hours of sleep deprivation within a controlled laboratory environment. Every 8 hours, sustained attention was measured using a 30-minute monotonous driving task, and subjective workload was measured using the NASA-Task Load Index (TLX). Workload, defined as time on task was assessed by splitting the drive into two 15-minute loops. A mixed model ANOVA revealed significant main effects of day (sleep deprivation) and time of day on lane deviation, number of crashes, speed deviation and time outside the safe zone (all p&lt;.001). There was a significant main effect of workload (time on task) on lane deviation (p=.042), indicating that a longer time on task resulted in greater lane deviation. NASA-TLX scores significantly increased with sleep deprivation (p&lt;.001), indicating that subjective workload increased with sleep loss even though the task remained constant. Workload, sleep deprivation and time of day produced a deterioration in sustained attention. With this, countermeasures that not only consider sleep deprivation and time of day, but also workload (time on task) can be considered.


Sign in / Sign up

Export Citation Format

Share Document