scholarly journals Drivers’ Attention Strategies before Eyes-off-Road in Different Traffic Scenarios: Adaptation and Anticipation

2021 ◽  
Vol 18 (7) ◽  
pp. 3716
Author(s):  
Zhuofan Liu ◽  
Wei Yuan ◽  
Yong Ma
Keyword(s):  
Visual Attention ◽  
Driving Simulator ◽  
Test Drive ◽  
Urban Road ◽  
Strong Shift ◽  
Related Information ◽  
Road Users ◽  
Urban Rural ◽  
Within Subjects ◽  
Driving Task

The distribution of drivers’ visual attention prior to diverting focus from the driving task is critical for safety. The object of this study is to investigate drivers’ attention strategy before they occlude their vision for different durations under different driving scenarios. A total of 3 (scenarios) × 3 (durations) within-subjects design was applied. Twenty-three participants completed three durations of occlusion (0, 1, and 2 s) test drive in a motion-based driving simulator under three scenarios (urban, rural, motorway). Drivers’ occlusion behaviour, driving behaviour, and visual behaviour in 6 s before occlusion was analyzed and compared. The results showed that drivers tended to slow down and increased their attention on driving task to keep safety in occlusion 2 s condition. The distribution of attention differed among different driving scenarios and occlusion durations. More attention was directed to Forward position and Speedometer in occlusion conditions, and a strong shift in attention from Forward position to Road users and Speedometer was found in occlusion 2 s condition. Road users was glanced more frequently in urban road with a higher percentage of attention transitions from Forward position to Road users. While gaze switching to Speedometer with a higher intensity was found on motorway. It suggests that drivers could adapt their visual attention to driving demand and anticipate the development of upcoming situations by sampling enough driving-related information before eyes-off-road. Moreover, the adaptation and anticipation are in accordance with driving situation and expected eyes-off-road duration. Better knowledge about attentional strategies before attention away from road contributes to more efficient and safe interaction with additional tasks.

scholarly journals Drivers’ Visual Search Behavior Toward Vulnerable Road Users at Junctions as a Function of Cycling Experience

2018 ◽  
Vol 60 (7) ◽  
pp. 889-901 ◽  
Author(s):  
Chloe Jade Robbins ◽  
Peter Chapman
Keyword(s):  
Visual Search ◽  
Visual Attention ◽  
Road Safety ◽  
Driving Simulator ◽  
Search Behavior ◽  
Road Users ◽  
Stop Sign ◽  
Vulnerable Road Users ◽  
Assistive Systems ◽  
Disproportionate Number

Objectives: The current study investigated the behavior and visual attention of two groups of drivers with differing pedal cycling experience (pedal cyclists and nonpedal cyclists) towards vulnerable road users at junctions in a driving simulator. Background: Pedal cyclists and motorcyclists are involved in a disproportionate number of crashes given the distance they travel, with a high proportion of these crashes occurring at junctions. Many studies have found that car drivers who also hold a motorcycle license have increased awareness towards motorcycles. Methods: The task involved approaching a T-junction and turning right when it was deemed to be safe. In Study 1, the junction was controlled by a give way sign, and in Study 2, the junction was controlled by a stop sign. Each T-junction contained a target vehicle (car, motorcycle, or pedal cycle), approaching from a near, medium, or far distance from the junction. Results: Participants did not look at pedal cycles approaching from a far distance for as long as they looked at approaching motorcycles and cars, despite all vehicles travelling at identical speeds. No differences were found between pedal cyclists and nonpedal cyclists on any visual attention measures, indicating that pedal cycling experience was not associated with differences in drivers’ attention toward pedal cycles. Conclusions: Findings have implications for road safety, demonstrating subtle differences in drivers’ everyday visual attention toward differing vehicle types. Applications: This research has the potential to inform the development of in-car technical assistive systems, improving the safety of vulnerable road users at junctions.

scholarly journals TVA in the wild: Applying the theory of visual attention to game-like and less controlled experiments

2021 ◽  
Vol 3 (1) ◽  
pp. 1-46
Author(s):  
Alexander Krüger ◽  
Jan Tünnermann ◽  
Lukas Stratmann ◽  
Lucas Briese ◽  
Falko Dressler ◽  
...  
Keyword(s):  
Visual Attention ◽  
Computer Games ◽  
Driving Simulator ◽  
Formal Theory ◽  
Partial Report ◽  
Visual Encoding ◽  
In The Wild ◽  
Series Of Experiments ◽  
Attentional Weight ◽  
Sufficient Precision

Abstract As a formal theory, Bundesen’s theory of visual attention (TVA) enables the estimation of several theoretically meaningful parameters involved in attentional selection and visual encoding. As of yet, TVA has almost exclusively been used in restricted empirical scenarios such as whole and partial report and with strictly controlled stimulus material. We present a series of experiments in which we test whether the advantages of TVA can be exploited in more realistic scenarios with varying degree of stimulus control. This includes brief experimental sessions conducted on different mobile devices, computer games, and a driving simulator. Overall, six experiments demonstrate that the TVA parameters for processing capacity and attentional weight can be measured with sufficient precision in less controlled scenarios and that the results do not deviate strongly from typical laboratory results, although some systematic differences were found.

A Driving Simulator Study of the Performance Effects of Low Blood Alcohol Concentration

1996 ◽  
Vol 40 (18) ◽  
pp. 943-946 ◽  
Author(s):  
R. Wade Allen ◽  
Zareh Parseghian ◽  
Anthony C. Stein
Keyword(s):  
Divided Attention ◽  
Driving Simulator ◽  
Blood Alcohol Concentration ◽  
Large Body ◽  
Alcohol Concentration ◽  
Blood Alcohol ◽  
Performance Effects ◽  
Driving Task ◽  
Simulator Study ◽  
And Performance

There is a large body of research that documents the impairing effect of alcohol on driving behavior and performance. Some of the most significant alcohol influence seems to occur in divided attention situations when the driver must simultaneously attend to several aspects of the driving task. This paper describes a driving simulator study of the effect of a low alcohol dose, .055 BAC (blood alcohol concentration %/wt), on divided attention performance. The simulation was mechanized on a PC and presented visual and auditory feedback in a truck cab surround. Subjects were required to control speed and steering on a rural two lane road while attending to a peripheral secondary task. The subject population was composed of 33 heavy equipment operators who were tested during both placebo and drinking sessions. Multivariate Analysis of Variance showed a significant and practical alcohol effect on a range of variables in the divided attention driving task.

The Effects of Telematics on Driver Distraction

2002 ◽  
Vol 46 (22) ◽  
pp. 1868-1870 ◽  
Author(s):  
Patrick Siebert ◽  
Mustapha Mouloua ◽  
Kendra Burns ◽  
Jennifer Marino ◽  
Lora Scagliola ◽  
...  
Keyword(s):  
Secondary Task ◽  
Cell Phone ◽  
Driving Simulator ◽  
Systems Design ◽  
Driver Distraction ◽  
Cellular Phones ◽  
Driver Safety ◽  
A Cell ◽  
Driving Task ◽  
Simulated Driving Task

This study used both cellular phones and analogue radio to measure driver distraction and workload in a low fidelity driving simulator. Thirty-four participants performed a simulated driving task while using either a cell phone or a radio in conjunction with a secondary task assessing their spare attentional capacity. The results showed that more lane deviations were made during the cell phone and radio tuning use than both of the pre-allocation and Post-allocation phases. The secondary task errors were also higher during both the cell phone and radio tuning allocation phase than the pre-allocation and post-allocation phases. These findings indicate the greater workload load levels associated with the use of telemetric devices. These findings have major implications for driver safety and telemetric systems design.

scholarly journals Real-Time Human in the Loop MBS Simulation in the Fraunhofer Robot-Based Driving Simulator

2014 ◽  
Vol 61 (2) ◽  
pp. 270-285 ◽  
Author(s):  
Michael Kleer ◽  
Andrey Gizatullin ◽  
Klaus Dreßler ◽  
Steffen Müller
Keyword(s):  
Real Time ◽  
Driving Simulator ◽  
Practical Significance ◽  
Time Model ◽  
Test Drive ◽  
The Real ◽  
Transport Delay ◽  
Human In The Loop ◽  
Acceleration Signal ◽  
Time Calculation

Abstract The paper encompasses the overview of hardware architecture and the systems characteristics of the Fraunhofer driving simulator. First, the requirements of the real-time model and the real-time calculation hardware are defined and discussed in detail. Aspects like transport delay and the parallel computation of complex real-time models are presented. In addition, the interfacing of the models with the simulator system is shown. Two simulator driving tests, including a fully interactive rough terrain driving with a wheeled excavator and a test drive with a passenger car, are set to demonstrate system characteristics. Furthermore, the simulator characteristics of practical significance, such as simulator response time delay, simulator acceleration signal bandwidth obtained from artificial excitation and from the simulator driving test, will be presented and discussed.

Physiological Indicators of Driver Workload During Car-Following Scenarios and Takeovers in Highly Automated Driving

2021 ◽  
Author(s):  
Vishnu Radhakrishnan ◽  
Natasha Merat ◽  
Tyron Louw ◽  
Rafael Goncalves ◽  
Wei Lyu ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Electrodermal Activity ◽  
Automated Driving ◽  
Physiological Indicators ◽  
Car Following ◽  
Time Headway ◽  
Driver Workload ◽  
Driving Task ◽  
Vehicle Automation ◽  
Lead Vehicle

This driving simulator study, conducted as a part of Horizon2020-funded L3Pilot project, investigated how different car-following situations affected driver workload, within the context of vehicle automation. Electrocardiogram (ECG) and electrodermal activity (EDA)-based physiological metrics were used as objective indicators of workload, along with self-reported workload ratings. A total of 32 drivers were divided into two equal groups, based on whether they engaged in a non-driving related task (NDRT) during automation or monitored the drive. Drivers in both groups were exposed to two counterbalanced experimental drives, lasting ~18 minutes each, of Short (0.5 s) and Long (1.5 s) Time Headway conditions during automated car-following (ACF), which was followed by a takeover that happened with or without a lead vehicle. We observed that the workload on the driver due to the NDRT was significantly higher than both monitoring the drive during ACF and manual car-following (MCF). Furthermore, the results indicated that shorter THWs and the presence of a lead vehicle can significantly increase driver workload during takeover scenarios, potentially affecting the safety of the vehicle. This warrants further research into understanding safe time headway thresholds to be maintained by automated vehicles, without placing additional mental or attentional demands on the driver. To conclude, our results indicated that ECG and EDA signals are sensitive to variations in workload, and hence, warrants further investigation on the value of combining these two signals to assess driver workload in real-time, to help the system respond appropriately to the limitations of the driver and predict their performance in driving task if and when they have to resume manual control of the vehicle.

scholarly journals Information Needs and Visual Attention during Urban, Highly Automated Driving—An Investigation of Potential Influencing Factors

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 62 ◽  
Author(s):  
Alexander Feierle ◽  
Simon Danner ◽  
Sarah Steininger ◽  
Klaus Bengler
Keyword(s):  
Visual Attention ◽  
Information Needs ◽  
Driving Simulator ◽  
Automation System ◽  
Automated Driving ◽  
Navigation Data ◽  
Levels Of Automation ◽  
Machine Interface ◽  
The Individual ◽  
Highly Automated Driving

During highly automated driving, the passenger is allowed to conduct non-driving related activities (NDRA) and no longer has to act as a fallback at the functional limits of the driving automation system. Previous research has shown that at lower levels of automation, passengers still wish to be informed about automated vehicle behavior to a certain extent. Due to the aim of the introduction of urban automated driving, which is characterized by high complexity, we investigated the information needs and visual attention of the passenger during urban, highly automated driving. Additionally, there was an investigation into the influence of the experience of automated driving and of NDRAs on these results. Forty participants took part in a driving simulator study. As well as the information presented on the human–machine interface (system status, navigation information, speed and speed limit), participants requested information about maneuvers, reasons for maneuvers, environmental settings and additional navigation data. Visual attention was significantly affected by the NDRA, while the experience of automated driving had no effect. Experience and NDRA showed no significant effect on the need for information. Differences in information needs seem to be due to the requirements of the individual passenger, rather than the investigated factors.

Impact of Cognitive Distractions on Drivers’ Hazard Anticipation Behavior in Complex Scenarios

2019 ◽  
Vol 2673 (9) ◽  
pp. 440-451 ◽  
Author(s):  
Yalda Ebadi ◽  
Donald L. Fisher ◽  
Shannon C. Roberts
Keyword(s):  
Response Time ◽  
Cell Phone ◽  
Driving Simulator ◽  
Mock Cell ◽  
Cell Phone Use ◽  
Road Users ◽  
Driving Skill ◽  
Cognitive Distraction ◽  
Negative Effect ◽  
Vulnerable Road Users

Distraction is one of the main causes of traffic crashes. The effect of cell phones, a major contributor to cognitive distraction, on response time has tested in many simulator studies. Response time is not the only driving skill affected by cell phone conversations, however. Specifically, it is known that cell phone usage contributes to a reduction in hazard anticipation skills at intersections, and there are many other scenarios where cell phone conversations could have a detrimental effect. The objective of this study is to determine whether cognitive distractions associated with cell phone use affect hazard anticipation, not only at intersections but also in other scenarios which contain latent hazards. Twenty-four drivers navigated 18 scenarios on a driving simulator twice, with their eye movements continuously monitored. During one drive, participants performed a hands-free mock cell phone task while driving; on the other drive, they navigated through the virtual world without any additional tasks apart from the primary task of driving. The scenarios were classified into two types: intersection and non-intersection. Using a logistic regression model within the framework of generalized estimation equations, it was determined that the proportion of anticipatory glances toward potential hazards was reduced significantly for all scenarios when drivers were engaged in a mock cell phone task. Perhaps the most disturbing finding is that this was true both at work zones and at marked midblock crosswalks, scenarios which often endanger vulnerable road users. In summary, the study found a negative effect of cognitive distraction on latent hazard anticipation.

Comparison of Primary and Secondary Task Measures as a Function of Simulated Vehicle Dynamics and Driving Conditions

1978 ◽  
Vol 20 (2) ◽  
pp. 233-244 ◽  
Author(s):  
Walter W. Wierwille ◽  
James C. Gutmann
Keyword(s):  
Task Performance ◽  
Vehicle Dynamics ◽  
Secondary Task ◽  
Driving Simulator ◽  
Driving Performance ◽  
Independent Variables ◽  
Moving Base ◽  
High Workload ◽  
Driving Task ◽  
Task Measure

In a previously reported experiment involving a moving base driving simulator with computer-generated display, secondary task measures of workload showed significant increases as a function of large changes in vehicle dynamics and disturbance levels. Because the secondary task measures appeared less sensitive than desired, driving performance measures recorded during the same experiment were later analyzed. Particular emphasis in examining the driving performance data was placed on (1) determining the degree of intrusion of the secondary task on the driving task as a function of the independent variables, and (2) on comparing the sensitivity of the primary and secondary task measures. The results showed the secondary task does intrude significantly upon the driving task performance at low workload levels, but that it does not significantly intrude at high workload levels. Also, when the four primary task measures were analyzed for sensitivity to the independent variables, new information was obtained indicating greater sensitivity than is obtained with the single secondary task measure. Steering ratio, for example, is found to affect performance at high disturbance levels—a result not obtained in examining the secondary task by itself. The merits of primary and secondary task performance analysis are discussed, and suggestions are made for future work.

Statistical Analysis of a Steering Assist Controller Using Driving Simulator Data

2005 ◽  
Author(s):  
Liang-Kuang Chen ◽  
A. Galip Ulsoy
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Model Uncertainty ◽  
Driving Simulator ◽  
Lateral Position ◽  
High Gain ◽  
Position Error ◽  
Driver Model ◽  
Stability Margins ◽  
Driving Task

Human-in-the-loop driving simulator experiments are conducted to evaluate a proposed robust steering assist controller designed based upon driver uncertainty modeling. A nominal controller that is designed without consideration of driver model uncertainty is also tested for comparison. Two types of experiments are proposed. A long driving task with nominal configurations and a short driving task with initially large lateral position error. The data is analyzed using both time domain and frequency domain metrics. In the time domain, the standard deviation of lateral position error and percentage of road departure are used. In the frequency domain, the stability margins and crossover frequency are used. The driving simulator results indicate that statistically the designed robust controller shows improvements in the short driving experiments. The improvements in the long driving experiments are less evident due to driver adaptation. The non-robust nominal controller suffers from high gain and should be avoided. The benefits of considering driver model uncertainty in the design of vehicle steering assist controllers is, therefore, justified.

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