scholarly journals A Driving Simulation to Analysis and Quantitative Comparison of Driving Behavior of Guide Signs at Intersections

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Tianzheng Wei ◽  
Tong Zhu ◽  
Chenxin Li ◽  
Haoxue Liu
Keyword(s):  
Quantitative Evaluation ◽  
Evaluation Method ◽  
Driving Simulator ◽  
Current System ◽  
Driving Behavior ◽  
Driving Simulation ◽  
Analysis Method ◽  
Safe Driving ◽  
Amount Of Information ◽  
Significant Difference

Guide signs are an important source for drivers to obtain road information. However, the evaluation methods for the effectiveness of guide signs are not unified. The quantitative model for evaluating guide signs needs to be constructed to unify the current system of guide signs. This study aims to take the commonly used guide signs in China as the research object to explore the evaluation method of guide signs at intersections. Eight kinds of guide signs were designed and made based on the common layout (layout 1 and layout 2) and the amount of information on signs (3–6). Thirty-four drivers were recruited to organize a driving simulation based on the visual cognitive tasks. Drivers’ legibility time and driver behavior were obtained by using the driving simulator and E-Prime program. A comprehensive quantitative evaluation model of guide signs was established based on the factor analysis method and grey correlation analysis method from the perspective of safe driving. The results show that there is no significant difference in the SD of speed and the SD of acceleration under the influence of various guide signs. The average vehicle speed and acceleration decrease, and the lateral offset distance of the vehicle increases with the amount of information on guide signs increasing. The quantitative evaluation results of guide signs show that the visual security decreases with the increase of the amount of information on guide signs. And layout 2 has better performance than layout 1 when the amount of information on guide signs is the same. This study not only explores the change rule of driving behavior under the influence of guide signs, but also provides a reference for the selection of guide signs.

The Validity of Three New Driving Simulator Scenarios: Detecting Differences in Driving Performance by Difficulty and Driver Gender and Age

2020 ◽  
pp. 001872082093752
Author(s):  
Hillary Maxwell ◽  
Bruce Weaver ◽  
Sylvain Gagnon ◽  
Shawn Marshall ◽  
Michel Bédard
Keyword(s):  
Discriminant Validity ◽  
Driving Simulator ◽  
Age Groups ◽  
Driving Behavior ◽  
Driving Simulation ◽  
Driving Simulators ◽  
Safe Driving ◽  
Convergent And Discriminant Validity ◽  
Gender And Age ◽  
Driver Assessment

Objective We explored the convergent and discriminant validity of three driving simulation scenarios by comparing behaviors across gender and age groups, considering what we know about on-road driving. Background Driving simulators offer a number of benefits, yet their use in real-world driver assessment is rare. More evidence is needed to support their use. Method A total of 104 participants completed a series of increasingly difficult driving simulation scenarios. Linear mixed models were estimated to determine if behaviors changed with increasing difficulty and whether outcomes varied by age and gender, thereby demonstrating convergent and discriminant validity, respectively. Results Drivers adapted velocity, steering, acceleration, and gap acceptance according to difficulty, and the degree of adaptation differed by gender and age for some outcomes. For example, in a construction zone scenario, drivers reduced their mean velocities as congestion increased; males drove an average of 2.30 km/hr faster than females, and older participants drove more slowly than young (5.26 km/hr) and middle-aged drivers (6.59 km/hr). There was also an interaction between age and difficulty; older drivers did not reduce their velocities with increased difficulty. Conclusion This study provides further support for the ability of driving simulators to elicit behaviors similar to those seen in on-road driving and to differentiate between groups, suggesting that simulators could serve a supportive role in fitness-to-drive evaluations. Application Simulators have the potential to support driver assessment. However, this depends on the development of valid scenarios to benchmark safe driving behavior, and thereby identify deviations from safe driving behavior. The information gained through simulation may supplement other forms of assessment and possibly eliminate the need for on-road testing in some situations.

scholarly journals Cognitive and motor deficits contribute to longer braking time in stroke

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Neha Lodha ◽  
Prakruti Patel ◽  
Joanna M. Shad ◽  
Agostina Casamento-Moran ◽  
Evangelos A. Christou
Keyword(s):  
Selective Attention ◽  
Driving Simulator ◽  
Maximum Voluntary Contraction ◽  
Driving Behavior ◽  
Motor Deficits ◽  
Control Group ◽  
Stroke Survivors ◽  
Safe Driving ◽  
Stroke Group ◽  
Motor Accuracy

Abstract Background Braking is a critical determinant of safe driving that depends on the integrity of cognitive and motor processes. Following stroke, both cognitive and motor capabilities are impaired to varying degrees. The current study examines the combined impact of cognitive and motor impairments on braking time in chronic stroke. Methods Twenty stroke survivors and 20 aged-matched healthy controls performed cognitive, motor, and simulator driving assessments. Cognitive abilities were assessed with processing speed, divided attention, and selective attention. Motor abilities were assessed with maximum voluntary contraction (MVC) and motor accuracy of the paretic ankle. Driving performance was examined with the braking time in a driving simulator and self-reported driving behavior. Results Braking time was 16% longer in the stroke group compared with the control group. The self-reported driving behavior in stroke group was correlated with braking time (r = − 0.53, p = 0.02). The stroke group required significantly longer time for divided and selective attention tasks and showed significant decrease in motor accuracy. Together, selective attention time and motor accuracy contributed to braking time (R2 = 0.40, p = 0.01) in stroke survivors. Conclusions This study provides novel evidence that decline in selective attention and motor accuracy together contribute to slowed braking in stroke survivors. Driving rehabilitation after stroke may benefit from the assessment and training of attentional and motor skills to improve braking during driving.

scholarly journals Effectiveness of Variable Message Signs on Driving Behavior Based on a Driving Simulation Experiment

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xuedong Yan ◽  
Jiawei Wu
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Simulation Experiment ◽  
Driving Simulator ◽  
Driving Behavior ◽  
Driving Simulation ◽  
Traffic Information ◽  
Variable Message Signs ◽  
Information Format ◽  
Message Signs

Variable message signs (VMSs), as one of the important ITS devices, provide real-time traffic information of road network to drivers in order to improve route choice and relieve the traffic congestion. In this study, the effectiveness of VMS on driving behavior was tested based on a driving simulation experiment. A road network with three levels of VMS location to route-diverging intersection and three types of VMS information format was designed in a high fidelity driving simulator platform. Fifty-two subjects who were classified by driver age, gender, and vocation successfully completed this experiment. The experimental results showed that driver characteristics, VMS location, and information format profoundly influence driving behaviors. Based on the research findings, it is suggested that VMS would be positioned between 150 m and 200 m upstream of the diverging point to balance the VMS effects on traffic safety and operation and the graphic information VMS format is better than the format with text massage only.

scholarly journals Driving Simulator Validity of Driving Behavior in Work Zones

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yanning Zhang ◽  
Zhongyin Guo ◽  
Zhi Sun
Keyword(s):  
Delay Time ◽  
Driving Simulator ◽  
Driving Behavior ◽  
Controlled Environment ◽  
Analysis Method ◽  
Work Zones ◽  
Relative Validity ◽  
Car Following ◽  
Driving Behaviors ◽  
Driving Scenario

Driving simulation is an efficient, safe, and data-collection-friendly method to examine driving behavior in a controlled environment. However, the validity of a driving simulator is inconsistent when the type of the driving simulator or the driving scenario is different. The purpose of this research is to verify driving simulator validity in driving behavior research in work zones. A field experiment and a corresponding simulation experiment were conducted to collect behavioral data. Indicators such as speed, car-following distance, and reaction delay time were chosen to examine the absolute and relative validity of the driving simulator. In particular, a survival analysis method was proposed in this research to examine the validity of reaction delay time. The result indicates the following: (1) most indicators are valid in driving behavior research in the work zone. For example, spot speed, car-following distance, headway, and reaction delay time show absolute validity. (2) Standard deviation of the car-following distance shows relative validity. Consistent with previous researches, some driving behaviors appear to be more aggressive in the simulation environment.

scholarly journals Glaucomatous visual fields and neurocognitive function are independently associated with poor lane maintenance during driving simulation

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
David E. Anderson ◽  
John P. Bader ◽  
Emily A. Boes ◽  
Meghal Gagrani ◽  
Lynette M. Smith ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Vehicle Control ◽  
Driving Behavior ◽  
Driving Performance ◽  
Driving Simulation ◽  
Sensor Data ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Neurocognitive Performance ◽  
Loss Severity

Abstract Background Driving simulators are a safe alternative to on-road vehicles for studying driving behavior in glaucoma drivers. Visual field (VF) loss severity is associated with higher driving simulator crash risk, though mechanisms explaining this relationship remain unknown. Furthermore, associations between driving behavior and neurocognitive performance in glaucoma are unexplored. Here, we evaluated the hypothesis that VF loss severity and neurocognitive performance interact to influence simulated vehicle control in glaucoma drivers. Methods Glaucoma patients (n = 25) and suspects (n = 18) were recruited into the study. All had > 20/40 corrected visual acuity in each eye and were experienced field takers with at least three stable (reliability > 20%) fields over the last 2 years. Diagnosis of neurological disorder or cognitive impairment were exclusion criteria. Binocular VFs were derived from monocular Humphrey VFs to estimate a binocular VF index (OU-VFI). Montreal Cognitive Assessment (MoCA) was administered to assess global and sub-domain neurocognitive performance. National Eye Institute Visual Function Questionnaire (NEI-VFQ) was administered to assess peripheral vision and driving difficulties sub-scores. Driving performance was evaluated using a driving simulator with a 290° panoramic field of view constructed around a full-sized automotive cab. Vehicle control metrics, such as lateral acceleration variability and steering wheel variability, were calculated from vehicle sensor data while patients drove on a straight two-lane rural road. Linear mixed models were constructed to evaluate associations between driving performance and clinical characteristics. Results Patients were 9.5 years older than suspects (p = 0.015). OU-VFI in the glaucoma group ranged from 24 to 98% (85.6 ± 18.3; M ± SD). OU-VFI (p = .0066) was associated with MoCA total (p = .0066) and visuo-spatial and executive function sub-domain scores (p = .012). During driving simulation, patients showed greater steering wheel variability (p = 0.0001) and lateral acceleration variability (p < .0001) relative to suspects. Greater steering wheel variability was independently associated with OU-VFI (p = .0069), MoCA total scores (p = 0.028), and VFQ driving sub-scores (p = 0.0087), but not age (p = 0.61). Conclusions Poor vehicle control was independently associated with greater VF loss and worse neurocognitive performance, suggesting both factors contribute to information processing models of driving performance in glaucoma. Future research must demonstrate the external validity of current findings to on-road performance in glaucoma.

scholarly journals Cognitive and Motor Deficits Contribute to Longer Braking Time in Stroke

2020 ◽  
Author(s):  
Neha Lodha ◽  
Prakruti Patel ◽  
Joanna M Shad ◽  
Agostina Casamento-Moran ◽  
Evangelos A Christou
Keyword(s):  
Selective Attention ◽  
Driving Simulator ◽  
Maximum Voluntary Contraction ◽  
Driving Behavior ◽  
Motor Deficits ◽  
Control Group ◽  
Stroke Survivors ◽  
Safe Driving ◽  
Stroke Group ◽  
Motor Accuracy

Abstract Braking is a critical determinant of safe driving that depends on the integrity of cognitive and motor processes. Following stroke, both cognitive and motor capabilities are impaired to varying degrees. The current study examines the combined impact of cognitive and motor impairments on braking time in chronic stroke. METHODS: Twenty stroke survivors and 20 aged-matched healthy controls performed cognitive, motor, and simulator driving assessments. Cognitive abilities were assessed with processing speed, divided attention, and selective attention. Motor abilities were assessed with maximum voluntary contraction (MVC) and motor accuracy of the paretic ankle. Driving performance was examined with the braking time in a driving simulator and self-reported driving behavior. RESULTS: Braking time was 16% longer in stroke group compared with the control group. The self-reported driving behavior in stroke group was correlated with braking time (r = -0.53, p = 0.02). The stroke group required significantly longer time for divided and selective attention task and showed significant decrease in motor accuracy. Together, selective attention time and motor accuracy contributed to braking time (R2 = 0.40, p = 0.01) in stroke survivors. CONCLUSIONS: This study provides novel evidence that decline in selective attention and motor accuracy together contribute to slowed braking in stroke survivors. Driving rehabilitation after stroke may benefit from the assessment and training of attentional and motor skills to improve braking during driving.

scholarly journals Cognitive and Motor Deficits Contribute to Longer Braking Time in Stroke 

2020 ◽  
Author(s):  
Neha Lodha ◽  
Prakruti Patel ◽  
Joanna M Shad ◽  
Agostina Casamento-Moran ◽  
Evangelos A Christou
Keyword(s):  
Selective Attention ◽  
Driving Simulator ◽  
Maximum Voluntary Contraction ◽  
Driving Behavior ◽  
Motor Deficits ◽  
Control Group ◽  
Stroke Survivors ◽  
Safe Driving ◽  
Stroke Group ◽  
Motor Accuracy

Abstract BACKGROUND: Braking is a critical determinant of safe driving that depends on the integrity of cognitive and motor processes. Following stroke, both cognitive and motor capabilities are impaired to varying degrees. The current study examines the combined impact of cognitive and motor impairments on braking time in chronic stroke. METHODS: Twenty stroke survivors and 20 aged-matched healthy controls performed cognitive, motor, and simulator driving assessments. Cognitive abilities were assessed with processing speed, divided attention, and selective attention. Motor abilities were assessed with maximum voluntary contraction (MVC) and motor accuracy of the paretic ankle. Driving performance was examined with the braking time in a driving simulator and self-reported driving behavior. RESULTS: Braking time was 16% longer in stroke group compared with the control group. The self-reported driving behavior in stroke group was correlated with braking time (r = -0.53, p = 0.02). The stroke group required significantly longer time for divided and selective attention task and showed significant decrease in motor accuracy. Together, selective attention time and motor accuracy contributed to braking time (R2 = 0.40, p = 0.01) in stroke survivors. CONCLUSIONS: This study provides novel evidence that decline in selective attention and motor accuracy together contribute to slowed braking in stroke survivors. Driving rehabilitation after stroke may benefit from the assessment and training of attentional and motor skills to improve braking during driving.

Driving Simulator System to Evaluate Driver’s Workload Using ADAS in Different Driving Contexts

2017 ◽  
Author(s):  
Giandomenico Caruso ◽  
Daniele Ruscio ◽  
Dedy Ariansyah ◽  
Monica Bordegoni
Keyword(s):  
Driving Simulator ◽  
Driving Simulation ◽  
Human Cognition ◽  
Driving Safety ◽  
Physiological Data ◽  
Driver Assistance Systems ◽  
Safe Driving ◽  
Dangerous Driving ◽  
Vehicle Technology ◽  
Physiological Sensors

The advancement of in-vehicle technology for driving safety has considerably improved. Current Advanced Driver-Assistance Systems (ADAS) make road safer by alerting the driver, through visual, auditory, and haptic signals about dangerous driving situations, and consequently, preventing possible collisions. However, in some circumstances the driver can fail to properly respond to the alert since human cognition systems can be influenced by the driving context. Driving simulation can help evaluating this aspect since it is possible to reproduce different ADAS in safe driving conditions. However, driving simulation alone does not provide information about how the change in driver’s workload affects the interaction of the driver with ADAS. This paper presents a driving simulator system integrating physiological sensors that acquire heart’s activity, blood volume pulse, respiration rate, and skin conductance parameters. Through a specific processing of these measurements, it is possible to measure different cognitive processes that contribute to the change of driver’s workload while using ADAS, in different driving contexts. The preliminary studies conducted in this research show the effectiveness of this system and provide guidelines for the future acquisition and the treatment of the physiological data to assess ADAS workload.

scholarly journals Evaluation of cybersickness in virtual reality in driving simulator

2021 ◽  
Vol 30 (2) ◽  
pp. 11-16
Author(s):  
Ana Agić ◽  
◽  
Lidija Mandić ◽  
Keyword(s):  
Virtual Reality ◽  
Virtual Environment ◽  
Side Effect ◽  
Driving Simulator ◽  
The Body ◽  
Driving Simulation ◽  
Blurred Vision ◽  
Significant Difference ◽  
Upset Stomach ◽  
Electroencephalogram Eeg

Virtual reality (VR) devices are becoming a more popular and widespread tool for learning, gaming and entertainment purposes. One of familiar problems of emerging in VR is side effect known as cybersickness, which can be a nuisance for consumers of VR content. This occurrence can be explained as visual and vestibular conflict. The problem with cybersickness lies within the fact that the body is stationary, but eyes perceive motion in virtual reality, also known as vection. Cybersickness symptoms that often occur include blurred vision, headache, vertigo, upset stomach and other. Aim of this research is to observe changes in cybersickness symptoms in two tested conditions (2D display and VR). In this paper, subjective and objective metric of evaluation regarding cybersickness in VR driving simulation are used. Subjective metric is survey and objective metric is electroencephalogram (EEG). Results of the survey indicate which symptoms of cybersickness are more pronounced during driving in virtual environment compared with classic 2D screen experience. Statistically significant difference was found for 6 variables, which include vertigo, blurred vision and headache. Objective metric showed that highest average beta wave was in VR setting, as well as beta/alpha ratio, which is associated with stress and excitement.

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