Development of Hi-Fidelity Driving Simulator for Measuring Driving Behavior

2001 ◽  
Vol 13 (4) ◽  
pp. 409-418 ◽  
Author(s):  
Motoyuki Akamatsu ◽  
◽  
Masayuki Okuwa ◽  
Masaaki Onuki ◽  
◽  
...  
Keyword(s):  
Traffic Control ◽  
Driving Simulator ◽  
Intelligent System ◽  
Mental Workload ◽  
Driving Behavior ◽  
Simulator Sickness ◽  
Motion Platform ◽  
The Road ◽  
Vehicle Cabin ◽  
Instrumented Vehicle

A hi-fidelity driving simulator has been developed to measure driving behavior. Since the driver is an important component of Intelligent System (i.e., human factor), it is necessary to measure and investigate the driving behavior either with ITS or without ITS. As the driving behavior is situation dependent behavior, there is a great advantage from using the driving simulator because various situational (e.g., traffic situation) and environmental factors can be controlled. The driving simulator is composed of a 290 degree screen and a hexapod motion platform with a fully instrumented vehicle cabin. The road environment for the simulator was a town area with a complex road network and various buildings. The traffic control system can control a traffic scenario with 81 vehicles and 72 pedestrians. Since simulator sickness was one of main concerns of using the hi-fidelity driving simulator, we developed the Simplified Simulator Sickness Questionnaire (SSSQ) to evaluate the subjective severity of simulator sickness. The SSSQ consisted of three subscores for nausea, oculomotor, and disorientation symptoms. A preliminary experiment was conducted to investigate the change in severity of the sickness and the mental workload using SSSQ and NASA-TLX when simulator driving was repeated twelve times. We found that the severity of simulator sickness and the workload decreased with repeated simulator drives. When focusing on the change among three simulator drives within one day, the Nausea subscore decreased but the Oculomotor subscore increased.

Advance Information on the Road: A Simulator Study of the Effect of Road Markings

1976 ◽  
Vol 18 (6) ◽  
pp. 521-532 ◽  
Author(s):  
Harald Witt ◽  
Carl G. Hoyos
Keyword(s):  
Driving Simulator ◽  
Driving Behavior ◽  
Speed Profile ◽  
The Road ◽  
Positive Effects ◽  
Road Signs ◽  
Advance Information ◽  
Simulator Study ◽  
On The Road ◽  
Accident Statistics

Accident statistics and studies of driving behavior have shown repeatedly that curved roads are hazardous. It was hypothesized that the safety of curves could be improved by indicating in advance the course of the road in a more effective way than do traditional road signs. A code of sequences of stripes put on right edge of the pavement was developed to indicate to the driver the radius of the curve ahead. The main characteristic of this code was the frequency of transitions from code elements to gaps between elements. The effect of these markings was investigated on a driving simulator. Twelve subjects drove on simulated roads of different curvature and with different placement of the code in the approach zone. Some positive effects of the advance information could be observed. The subjects drove more steadily, more precisely, and with a more suitable speed profile.

scholarly journals Validity of Mental Workload Measures in a Driving Simulation Environment

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Francesco Galante ◽  
Fabrizio Bracco ◽  
Carlo Chiorri ◽  
Luigi Pariota ◽  
Luigi Biggero ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Mental Workload ◽  
Critical Issue ◽  
Simulation Environment ◽  
Driving Simulators ◽  
The Road ◽  
Mixed Support ◽  
Vehicle Systems ◽  
Driving Task ◽  
On The Road

Automated in-vehicle systems and related human-machine interfaces can contribute to alleviating the workload of drivers. However, each new functionality can also introduce a new source of workload, due to the need to attend to new tasks and thus requires careful testing before being implemented in vehicles. Driving simulators have become a viable alternative to on-the-road tests, since they allow optimal experimental control and high safety. However, for each driving simulator to be a useful research tool, for each specific task an adequate correspondence must be established between the behavior in the simulator and the behavior on the road, namely, the simulator absolute and relative validity. In this study we investigated the validity of a driving-simulator-based experimental environment for research on mental workload measures by comparing behavioral and subjective measures of workload of the same large group of participants in a simulated and on-road driving task on the same route. Consistent with previous studies, mixed support was found for both types of validity, although results suggest that allowing more and/or longer familiarization sessions with the simulator may be needed to increase its validity. Simulator sickness also emerged as a critical issue for the generalizability of the results.

scholarly journals Research on the classification for road traffic visibility based on the characteristics of driving behaviour – a driving simulator experiment

2020 ◽  
Vol 3 (1) ◽  
pp. 30-36
Author(s):  
Kun Wang ◽  
Weihua Zhang ◽  
Zhongxiang Feng ◽  
Cheng Wang
Keyword(s):  
Traffic Safety ◽  
Driving Simulator ◽  
Road Traffic ◽  
Driving Behavior ◽  
Control Measures ◽  
Content Type ◽  
The Road ◽  
Road Traffic Safety ◽  
Fine Classification

Purpose The purpose of this paper is to perform fine classification of road traffic visibility based on the characteristics of driving behavior under different visibility conditions. Design/methodology/approach A driving simulator experiment was conducted to collect data of speed and lane position. ANOVA was used to explore the difference in driving behavior under different visibility conditions. Findings The results show that only average speed is significantly different under different visibility conditions. With the visibility reducing, the average vehicle speed decreases. The road visibility conditions in a straight segment can be divided into five levels: less than 20, 20-30, 35-60, 60-140 and more than 140 m. The road visibility conditions in a curve segment can be also divided into four levels: less than 20, 20-30, 35-60 and more than 60 m. Originality/value A fine classification of road traffic visibility has been performed, and these classifications help to establish more accurate control measures to ensure road traffic safety under low-visibility conditions.

Evaluation of Novel Urban Rail Level Crossing Designs Using Driving Simulation

2016 ◽  
Vol 60 (1) ◽  
pp. 1921-1925 ◽  
Author(s):  
G. J. M. Read ◽  
A. Clacy ◽  
M. Thomas ◽  
M. R. H. Van Mulken ◽  
N. Stevens ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Safety Concern ◽  
Driving Behavior ◽  
Subjective Ratings ◽  
Level Crossing ◽  
The Road ◽  
Design Concepts ◽  
Space Design ◽  
Shared Space ◽  
Urban Rail

Rail level crossings (RLXs) are a public safety concern internationally. The design of the RLX environment has been implicated in many recent crashes. In this study we evaluated three novel RLX design concepts using a driving simulator. Participants completed four drives, each incorporating one of the RLX designs (one baseline and three novel designs) in both train coming and train not coming mode. Measures of speed and braking on approach were analyzed, along with subjective measures of workload and usability. Superior driving behavior and subjective ratings were achieved for a design that incorporated an in-vehicle device while the lowest subjective ratings were given in relation to a shared space design that incorporated a simplified crossing environment and sharing of the road environment between motorized and non-motorized users. The implications for RLX safety are discussed.

Senior Driver Performance on Airport Road Access Wayfinding Design

2019 ◽  
Vol 16 (12) ◽  
pp. 4937-4942
Author(s):  
Nur Khairiel Anuar ◽  
Rohafiz Sabar ◽  
Mazli Mutazam
Keyword(s):  
Road Safety ◽  
Driving Simulator ◽  
Driving Behavior ◽  
Age Group ◽  
Traffic Light ◽  
Simulated Driving ◽  
The Road ◽  
Road Design ◽  
Driver Performance ◽  
Study Participants

The purpose of this study was to evaluate the wayfinding and signage provisions, sensitivity of senior driving behavior and road safety. Three scenario types were designed using driving simulator to simplify the airport navigation and driving complexity of the road designs to the airport. An assorted road furniture was included on alternative airport road access to provide a variety of wayfinding complexity. Fifteen experience car drivers in range of age 50–54, 55–59 and over 60 years were selected to perform the study. Participants were asked to drove for approximately 20 minutes to complete the simulated driving. The types of errors (parameter) of simulated driving were identified, evaluated and compared to the age group. Results were analyzed by ANOVA and discussed with reference to the use of driving simulator. The ANOVA confirmed that senior drivers’ age group have no significant effect on the airport road design, wayfinding and all research parameters; risk of collisions, exceed the speed limit, traffic light tickets, centerline crossings and road edge excursions.

Pink Elephants on the Road: Visual Illusions and Distortions when Driving during Significant Sleep Deprivation

2020 ◽  
Vol 64 (1) ◽  
pp. 1360-1364
Author(s):  
Curtis M. Craig ◽  
Nichole L. Morris ◽  
Katelyn R. Schwieters ◽  
Conrad Iber
Keyword(s):  
Sleep Deprivation ◽  
Driving Simulator ◽  
Mental Workload ◽  
Visual Illusions ◽  
Safe Driving ◽  
The Road ◽  
Time Period ◽  
Visual Phenomena ◽  
On The Road ◽  
Study Participants

Visual hallucinations, illusions, and distortions have been observed in individuals undergoing severe periods of extended wakefulness. However, the incidence of these perceptual phenomena occurring during applied domains such as driving have been underreported. This study investigates effects of a 30-hour period of extended wakefulness during which participants abstained from stimulants and were not allowed to sleep or nap. Participants drove every 4 hours during this period on an uneventful 30-minute driving route in a fullcab high fidelity driving simulator. At the end of the study, participants reported whether they experienced significant visual illusions or distortions, and when the events occurred. Participants reported visual distortions and illusions during drives comprising a time period between 22 and 30 hours awake. Furthermore, self-reported mental workload and extroversion predicted the likelihood of experiencing the visual phenomena. Potential mechanisms for this relationship and possible consequences for safe driving performance during significant sleep deprivation are discussed.

Driving Performance as a Function of Time on the Road

1987 ◽  
Vol 31 (7) ◽  
pp. 766-769
Author(s):  
Thomas A. Ranney ◽  
Valerie J. Gawron
Keyword(s):  
Reaction Time ◽  
Driving Simulator ◽  
Lateral Acceleration ◽  
Time Variability ◽  
Reaction Time Variability ◽  
The Road ◽  
Driving Time ◽  
On The Road ◽  
Instrumented Vehicle ◽  
Fatigue Driving

The effects of driving time were examined in two experiments, both involving two-hour drives. Experiment 1 used a fully instrumented vehicle on a closed course under nighttime conditions. Experiment 2 used an interactive driving simulator. In Experiment 1 effects of driving time were increases in the frequency of right-side lane departures, decreased speed, and increased speed variability, all consistent with decreased arousal associated with fatigue. Driving time effects in Experiment 2 included increased reaction time and reaction-time variability to signs as well increases in speed, lateral acceleration and in overall performance as reflected in pay, indicating compensation for the effects of fatigue. Differences between the experiments were examined as possible explanations for differences in results.

scholarly journals Bicyclist-evoked arousal and greater attention to bicyclists independently promote safer driving

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Andy Jeesu Kim ◽  
Hananeh Alambeigi ◽  
Tara Goddard ◽  
Anthony D. McDonald ◽  
Brian A. Anderson
Keyword(s):  
Real World ◽  
Driving Simulator ◽  
Orienting Response ◽  
Driving Behavior ◽  
Self Report ◽  
Physiological Measures ◽  
The Road ◽  
Negative Arousal ◽  
Negative Perceptions ◽  
Arousal Response

AbstractWhile attention has consistently been shown to be biased toward threatening objects in experimental settings, our understanding of how attention is modulated when the observer is in an anxious or aroused state and how this ultimately affects behavior is limited. In real-world environments, automobile drivers can sometimes carry negative perceptions toward bicyclists that share the road. It is unclear whether bicyclist encounters on a roadway lead to physiological changes and attentional biases that ultimately influence driving behavior. Here, we examined whether participants in a high-fidelity driving simulator exhibited an arousal response in the presence of a bicyclist and how this modulated eye movements and driving behavior. We hypothesized that bicyclists would evoke a robust arousal and orienting response, the strength of which would be associated with safer driving behavior. The results revealed that encountering a bicyclist evoked negative arousal by both self-report and physiological measures. Physiological and eye-tracking measures were themselves unrelated, however, being independently associated with safer driving behavior. Our findings offer a real-world demonstration of how arousal and attentional prioritization can lead to adaptive behavior.

scholarly journals Predicting Compliance with Speed Limits using Speed Limit Credibility Perception and Risk Perception Data

2020 ◽  
Vol 2674 (9) ◽  
pp. 450-461
Author(s):  
Yao Yao ◽  
Oliver Carsten ◽  
Daryl Hibberd
Keyword(s):  
Risk Perception ◽  
Driving Simulator ◽  
Learning Algorithm ◽  
Warning System ◽  
Personal Characteristics ◽  
Driving Behavior ◽  
Speed Limit ◽  
Speed Limits ◽  
The Road ◽  
Boosted Decision Tree

The link between attitudes and behavior shows that driving behavior can be predicted by personal characteristics and individual attitudes, as has been shown in previous research. This study aimed to predict the level of compliance with speed limits by individual drivers by using attitudes data including speed limit credibility perception and risk perception on eight rural single carriageway layouts. This study investigated how the road layout and roadside environment affect speed limit credibility perception and risk perception, and investigated which machine learning algorithm can be used to predict driving behavior based on experimental evidence. This study was carried out in a well-controlled experimental design by using a questionnaire and a driving simulator. The simulated road environment only considered rural single carriageway which has higher risk factors than other road types. The results show that a boosted decision tree algorithm can establish a driving behavior model based on drivers’ credibility perception and risk perception. This result can be used to predict driving behavior in advance for in-vehicle warning system design.

Effect of Changing a Traffic Control Device Color on Driver Behavior and Perception across Different Age Groups

2021 ◽  
pp. 036119812110111
Author(s):  
Hatem Abou-Senna ◽  
Mohamed El-Agroudy ◽  
Mustapha Mouloua ◽  
Essam Radwan
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Driving Simulator ◽  
Age Groups ◽  
The United States ◽  
Time Of Day ◽  
General Purpose ◽  
Traffic Density ◽  
Driving Conditions ◽  
And Performance

The use of express lanes (ELs) in freeway traffic management has seen increasing popularity throughout the United States, particularly in Florida. These lanes aim at making the most efficient transportation system management and operations tool to provide a more reliable trip. An important component of ELs is the channelizing devices used to delineate the separation between the ELs and the general-purpose lane. With the upcoming changes to the FHWA Manual on Uniform Traffic Control Devices, this study provided an opportunity to recommend changes affecting safety and efficiency on a nationwide level. It was important to understand the impacts on driver perception and performance in response to the color of the EL delineators. It was also valuable to understand the differences between demographics in responding to delineator colors under different driving conditions. The driving simulator was used to test the responses of several demographic groups to changes in marker color and driving conditions. Furthermore, participants were tested for several factors relevant to driving performance including visual and subjective responses to the changes in colors and driving conditions. Impacts on driver perception were observed via eye-tracking technology with changes to time of day, visibility, traffic density, roadway surface type, and, crucially, color of the delineating devices. The analyses concluded that white was the optimal and most significant color for notice of delineators across the majority of subjective and performance measures, followed by yellow, with black being the least desirable.

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