Comparison of Computer-Generated and Simulated Motion Picture Displays in a Driving Simulation

1975 ◽  
Vol 17 (6) ◽  
pp. 577-590 ◽  
Author(s):  
Walter W. Wierwille ◽  
Peter P. Fung
Keyword(s):  
Motion Picture ◽  
Driving Simulator ◽  
Lane Changing ◽  
Motion Cues ◽  
Lane Changes ◽  
Physical Motion ◽  
Dependent Variables ◽  
Simulated Motion ◽  
Four Levels ◽  
Lane Keeping

An automotive driving simulator with a computer-generated display system, three axes of physical motion (roll, yaw, and lateral translation), sound, and vibration cues was used to investigate and compare human psychomotor response and vehicle response to different types of displays and motion cues. Subjects drove the simulator under four levels of displays; three being simulated preprogrammed motion picture displays (MPDS), one being the standard computer-generated display (CGDS). Motion and no-motion conditions were instituted at each display level. Each data run included lane-keeping and lane-changing tasks for various simulated highway conditions. During lane changes under MPDS conditions, both preprogrammed and nonpreprogrammed simulator conditions were examined. Seven dependent variables were used to measure performance. Results of the experiment show that one level of the simulated preprogrammed MPDS produced performance similar to that of a CGDS in all seven measures, whereas the other levels differed significantly. This suggests that using a properly instrumented preprogrammed MPDS will not compromise experimental results for certain research and educational experiments, and that in many cases an economical simulation using an MPDS would be adequate.

scholarly journals The Influence of Motion and Audio Cues on Driver Performance in an Automobile Simulator

1975 ◽  
Vol 17 (5) ◽  
pp. 488-501 ◽  
Author(s):  
Robert C. Mclane ◽  
Walter W. Wierwille
Keyword(s):  
Performance Measures ◽  
Driving Simulator ◽  
Visual Display ◽  
Control Group ◽  
Motion Cues ◽  
Physical Motion ◽  
Audio Cues ◽  
Driver Performance ◽  
Simulator Design ◽  
Student Subjects

A highway driving simulator with a computer-generated visual display, physical motion cues of roll, yaw, and lateral translation, and velocity-dependent sound/vibration cues was used to investigate the influence of these cues on driver performance. Forty-eight student subjects were randomly allocated to six experimental groups. Each group of eight subjects experienced a unique combination of the motion and audio cues. The control group received a full simulation condition while each of the remaining five groups performed with certain combinations of motion and sound deleted. Each driver generated nine minutes of continuous data from which five performance measures were derived. Results indicate that the performance measures of yaw, lateral, and velocity deviation are significantly affected by the deletion of cues. In support of the hypothesis that driver performance is augmented by the addition of motion cues, statistically significant negative correlations were obtained between the number of motion cues present and the measures of yaw and lateral deviation. With respect to motion and audio cues, recommendations are made regarding simulator design criteria.

Drivers’ Gaze Behaviors are Influenced by Vehicle Position

2020 ◽  
Vol 64 (1) ◽  
pp. 1625-1629 ◽  
Author(s):  
Yuki Okafuji ◽  
Takahiro Wada ◽  
Toshihito Sugiura ◽  
Kazuomi Murakami ◽  
Hiroyuki Ishida
Keyword(s):  
Driving Simulator ◽  
Lateral Position ◽  
Gaze Behavior ◽  
Lateral Deviation ◽  
Simulated Driving ◽  
The Gaze ◽  
Fixation Distance ◽  
Long Time ◽  
Vehicle Position ◽  
Lane Keeping

Drivers’ gaze behaviors in naturalistic and simulated driving tasks have been investigated for decades. Many studies focus on driving environment to explain a driver’s gaze. However, if there is a great need to use compensatory steering for lane-keeping, drivers could preferentially acquire information directly required for the task. Therefore, we assumed that a driver’s gaze behavior was influenced not only by the environment but also the vehicle position, especially the lateral position. To verify our hypothesis, we carried out a long-time driving simulator experiment, and the gaze behaviors of two participating drivers were analyzed. Results showed that gaze behavior—the fixation distance and the lateral deviation of the fixation—was influenced by the lateral deviation of the vehicle. Consequently, we discussed processes that determined drivers’ gaze behaviors.

Visual, Perceptual, and Cognitive Measures as Predictors of Collision Detection in Older Drivers

1997 ◽  
Vol 41 (2) ◽  
pp. 1018-1022
Author(s):  
Christina L. James ◽  
Kathryn Wochinger ◽  
W. Spencer James ◽  
Deborah Boehm-Davis
Keyword(s):  
Collision Detection ◽  
Driving Simulator ◽  
Age Groups ◽  
Cognitive Test ◽  
Age Group ◽  
Cognitive Measures ◽  
Error Type ◽  
Vehicle Collisions ◽  
Independent Variables ◽  
Dependent Variables

This experiment examined whether visual, perceptual, or cognitive measures predicted the ability to detect vehicle collisions in intersections. Sixty subjects, comprised of three age groups balanced by gender, were presented dynamic intersection approaches in a part-task driving simulator. The subjects were asked to project the forward progress of crossing traffic and to indicate whether any of the crossing vehicles would conflict with their vehicle. Independent variables included visual, perceptual, and cognitive test batteries. Dependent variables included accuracy in collision detection and error type. Results showed that all three batteries predicted accuracy, but that the perceptual battery was the most predictive for each age group.

scholarly journals Improved Road Safety at Work Zones using Advanced Traveler Information Systems

2020 ◽  
Author(s):  
Mustafa Suhail Almallah ◽  
Qinaat Hussain ◽  
Wael K. M Alhajyaseen ◽  
Tom Brijs
Keyword(s):  
Traffic Safety ◽  
Driving Simulator ◽  
Work Zone ◽  
Speed Limit ◽  
Work Zones ◽  
Treatment Scenario ◽  
Lane Changing ◽  
Variable Message Signs ◽  
Study Results ◽  
Message Signs

Work zones are road sections where road construction or maintenance activities take place. These work zones usually have different alignment and furniture than the original road and thus temporary lower speeds are adopted at these locations. However, drivers usually face difficulty in adopting the new speed limit and maneuvering safely due to the change in alignment. Therefore, work zones are commonly considered as hazardous locations with higher crash rates and severities as reported in the literature. This study aims to investigate the effectiveness of a variable message signs (VMSs) based system for work zone advance warning area. The proposed system aims at enhancing driver adaptation of the reduced speed limit, encourage early lane changing maneuvers and improve the cooperative driving behavior in the pre-work zone road section. The study was conducted using a driving simulator at the College of Engineering of Qatar University. Seventy volunteers holding a valid Qatari passenger car driving license participated in this study. In the simulator experiment, we have two scenarios (control and treatment). The control scenario was designed based on the Qatar Work Zone Traffic Management Guide (QWZTMG), where the length of the advance warning area is 1000 m. Meanwhile, the treatment scenario contains six newly designed variable message signs where two of them were animation-based. The VMSs were placed at the same locations of the static signs in the control scenario. Both scenarios were tested for two situations. In the first situation, the participants were asked to drive on the left lane while in the second situation, they were instructed to drive on the second lane. The study results showed that the proposed system was effective in motivating drivers to reduce their traveling speed in advance. Compared to the control scenario, drivers’ mean speed was significantly 6.3 and 11.1 kph lower in the VMS scenario in the first and second situations, respectively. Furthermore, the VMS scenario encouraged early lane changing maneuvers. In the VMS scenario, drivers changed their lanes in advance by 150 m compared to the control scenario. In addition, the proposed system was effective in motivating drivers to keep larger headways with the frontal merging vehicle. Taking into account the results from this study, we recommend the proposed VMS based system as a potentially effective treatment to improve traffic safety at work zones.

scholarly journals Improving Usefulness of Automated Driving by Lowering Primary Task Interference through HMI Design

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Frederik Naujoks ◽  
Yannick Forster ◽  
Katharina Wiedemann ◽  
Alexandra Neukum
Keyword(s):  
Driving Simulator ◽  
Primary Task ◽  
Automated Driving ◽  
Task Interference ◽  
Driving System ◽  
Lane Changes ◽  
Speech Output ◽  
Driving Time ◽  
Standard Information ◽  
Machine Interface

During conditionally automated driving (CAD), driving time can be used for non-driving-related tasks (NDRTs). To increase safety and comfort of an automated ride, upcoming automated manoeuvres such as lane changes or speed adaptations may be communicated to the driver. However, as the driver’s primary task consists of performing NDRTs, they might prefer to be informed in a nondistracting way. In this paper, the potential of using speech output to improve human-automation interaction is explored. A sample of 17 participants completed different situations which involved communication between the automation and the driver in a motion-based driving simulator. The Human-Machine Interface (HMI) of the automated driving system consisted of a visual-auditory HMI with either generic auditory feedback (i.e., standard information tones) or additional speech output. The drivers were asked to perform a common NDRT during the drive. Compared to generic auditory output, communicating upcoming automated manoeuvres additionally by speech led to a decrease in self-reported visual workload and decreased monitoring of the visual HMI. However, interruptions of the NDRT were not affected by additional speech output. Participants clearly favoured the HMI with additional speech-based output, demonstrating the potential of speech to enhance usefulness and acceptance of automated vehicles.

scholarly journals The potential of physical motion cues

2016 ◽  
Author(s):  
Pedro Garcia Garcia ◽  
Enrico Costanza ◽  
Sarvapali D. Ramchurn ◽  
Jhim Kiel M. Verame
Keyword(s):  
Motion Cues ◽  
Physical Motion

Enhancing the Performance of a Model to Predict Driving Distraction with the Random Forest Classifier

2021 ◽  
pp. 036119812110186
Author(s):  
Samira Ahangari ◽  
Mansoureh Jeihani ◽  
Anam Ardeshiri ◽  
Md Mahmudur Rahman ◽  
Abdollah Dehzangi
Keyword(s):  
Random Forest ◽  
Driving Simulator ◽  
Situational Awareness ◽  
True Positive Rate ◽  
The United States ◽  
Driving Performance ◽  
Lane Changing ◽  
Wide Range ◽  
Positive Rate ◽  
Better Than

Distracted driving is known to be one of the main causes of crashes in the United States, accounting for about 40% of all crashes. Drivers’ situational awareness, decision-making, and driving performance are impaired as a result of temporarily diverting their attention from the primary task of driving to other unrelated tasks. Detecting driver distraction would help in adapting the most effective countermeasures. To tackle this problem, we employed a random forest (RF) classifier, one of the best classifiers that has attained promising results for a wide range of problems. Here, we trained RF using the data collected from a driving simulator, in which 92 participants drove under six different distraction scenarios of handheld calling, hands-free calling, texting, voice command, clothing, and eating/drinking on four different road classes (rural collector, freeway, urban arterial, and local road in a school zone). Various driving performance measures such as speed, acceleration, throttle, lane changing, brake, collision, and offset from the lane center were investigated. Using the RF method, we achieved 76.5% prediction accuracy on the independent test set, which is over 8.2% better than results reported in previous studies. We also obtained a 76.6% true positive rate, which is 14% better than those reported in previous studies. Such results demonstrate the preference of RF over other machine learning methods to identify driving distractions.

Importance of Introducing Motion Cues in a Driving Simulator

2011 ◽  
Author(s):  
Alina Capustiac ◽  
Benjamin Hesse ◽  
Dieter Schramm ◽  
Dorel Banabic
Keyword(s):  
Driving Simulator ◽  
Motion Cues

Driving Performance under Nighttime Conditions of Visual Degradation

1967 ◽  
Vol 9 (5) ◽  
pp. 427-432 ◽  
Author(s):  
Francisco Matanzo ◽  
Thomas H. Rockwell
Keyword(s):  
Driving Performance ◽  
Task Group ◽  
Vehicle Speed ◽  
Dependent Variables ◽  
Visual Degradation ◽  
Four Levels ◽  
Instrumented Vehicle ◽  
Lane Position ◽  
Nighttime Driving ◽  
Very High

Nighttime driving performance was studied in relation to four different driving tasks and four levels of visual degradation. Four matched but task-differentiated groups of four Ss each drove an instrumented vehicle at night on a superhighway. The four levels of visual degradation presented the roadway to the driver at overall luminance levels of 5.228 mL, 2.688 mL, 0.755 mL, and 0.168 mL. The two dependent variables were vehicle speed and vehicle distance from the white shoulder line. The visual degradation caused the Ss to slow down and position the vehicle slightly farther away from the shoulder. It was found that a driver also is capable of driving at a constant speed and of maintaining a constant lane position at very high degrees of visual degradation. These results were explained by the different instructions given to each task group.

Integrated Strategy for Automatic Lane-Changing Decision and Trajectory Planning in Dynamic Scenario

2020 ◽  
Author(s):  
Meng Ren ◽  
Guangqiang Wu
Keyword(s):  
Neural Network ◽  
Trajectory Planning ◽  
Driving Simulator ◽  
Back Propagation ◽  
Lateral Acceleration ◽  
Vehicle Speed ◽  
Lane Changing ◽  
Planning Strategy ◽  
Integrated Strategy ◽  
Dynamic Scenario

Abstract Automatic lane change is a necessary part for autonomous driving. This paper proposes an integrated strategy for automatic lane-changing decision and trajectory planning in dynamic scenario. The Back Propagation Neural Network (BPNN) is used in decision-making layer, whose prediction accuracy of the discretionary lane-changing is 94.22%. The planning layer determines the adjustable range of the average vehicle speed based on the size of the “lane-changing demand”, which is obtained based on the data of hidden layer in neural network, and then dynamically optimizes the lane-changing curve according to the vehicle speed and the current scenario. In order to verify the rationality of the proposed lane-changing architecture, simulation experiments based on a driving simulator is performed. The experiments show that the vehicle’s maximum lateral acceleration under the proposed lane-changing trajectory at a speed of 70km/h is about 0.1g, which means the vehicle has better comfort during lane-changing. At the same time, the proposed lane-changing trajectory is more in line with the human driver’s lane-changing trajectory compared with that of other planning strategy. Meanwhile, the planning strategy can also support the lane-changing trajectory planning on a curved road.

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