Analysis of Driving Behaviors Based on GMM by Using Driving Simulator with Navigation Plugin

2015 ◽  
pp. 141-156
Author(s):  
Naoto Mukai
Keyword(s):  
Driving Simulator ◽  
Driving Behaviors

Traffic accident and emission reduction through intermittent release measures for heavy fog weather

2015 ◽  
Vol 29 (25) ◽  
pp. 1550148 ◽  
Author(s):  
Jing Shi ◽  
Jin-Hua Tan
Keyword(s):  
Traffic Safety ◽  
Emission Reduction ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Driving Simulator ◽  
Emission Characteristics ◽  
Driving Behaviors ◽  
Ca Model ◽  
Reduce Emissions

Heavy fog weather can increase traffic accidents and lead to freeway closures which result in delays. This paper aims at exploring traffic accident and emission characteristics in heavy fog, as well as freeway intermittent release measures for heavy fog weather. A driving simulator experiment is conducted for obtaining driving behaviors in heavy fog. By proposing a multi-cell cellular automaton (CA) model based on the experimental data, the role of intermittent release measures on the reduction of traffic accidents and CO emissions is studied. The results show that, affected by heavy fog, when cellular occupancy [Formula: see text], the probability of traffic accidents is much higher; and CO emissions increase significantly when [Formula: see text]. After an intermittent release measure is applied, the probability of traffic accidents and level of CO emissions become reasonable. Obviously, the measure can enhance traffic safety and reduce emissions.

scholarly journals Testing the Effectiveness of a Mixed-Method Pilot Intervention in Reducing Risky Driving Due to Aggression and Stress

Safety ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 11
Author(s):  
Maria Papadakaki ◽  
Nikolaos Stamou ◽  
Stefanos Bessas ◽  
Stavroula Lioliou ◽  
Jooannes Chliaoutakis
Keyword(s):  
Mixed Method ◽  
Large Scale ◽  
Driving Simulator ◽  
Intervention Group ◽  
Cognitive Restructuring ◽  
Driving Performance ◽  
Control Group ◽  
Driving Behaviors ◽  
Experiential Instruction ◽  
Pilot Intervention

The study aimed at testing the effectiveness of a mixed-method pilot intervention in reducing risky self-reported driving performance, upon addressing stress and aggression while driving. The study recruited individuals who had performed these behaviors during the year preceding the study and allocated them into an intervention (n = 10) and a control group (n = 30). A pre-and postintervention evaluation design was employed to explore changes in risky self-reported driving behaviors, 12 months after the intervention. The intervention involved 2 h of experiential instruction and 1 h of cognitive restructuring using a driving simulator and scenarios appropriate for the processing of driving stress, aggression, and risk. The intervention group displayed significant improvements in the scales of “Hazard Monitoring” (p = 0.037) and “Covered Violations” (p = 0.049) at the postintervention level. No statistically significant differences were identified in terms of self-reported driving performance between the intervention and the control group at postintervention level. Launching large-scale experimental surveys with broadened cognitive restructuring approaches seems important to deepen our understanding of the behavioral change processes and increase the effectiveness of future interventions.

scholarly journals Driving Performance Evaluation Correlated to Age and Visual Acuities Based on VR Technologies

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Sooncheon Hwang ◽  
Sunhoon Kim ◽  
Dongmin Lee
Keyword(s):  
Visual Acuity ◽  
Driving Simulator ◽  
Driving Behavior ◽  
Driving Performance ◽  
Present System ◽  
The South ◽  
Dynamic Visual Acuity ◽  
South Korean ◽  
Driving Behaviors ◽  
License System

There is currently much debate regarding the effectiveness of the driver license system in South Korea, due to the numerous traffic crashes caused by drivers who are suspected of having insufficient physical and mental abilities. Through the present system, it is quite difficult to identify such drivers indirectly through physical tests, such as visual acuity tests, since the correlation of such results with driving performance remains unclear. The objective of this study was to investigate the relationship between driving performance and visual acuities for improving the South Korean driver license system. In this study, two investigations were conducted: static and dynamic visual acuity examinations and driving performance tests based on a virtual reality (VR) system. The driving performance was evaluated with a driving simulator, based on driving behaviors in different experimental scenarios, including daytime and nighttime driving on a rural highway, and unexpected incident situations. Here, we produce statistically significant evidence that reduced visual acuity impairs driving performance, and driving behaviors differ significantly among groups with different vision capabilities, especially dynamic vision. Visual acuities, typically dynamic visual acuity, greatly influenced driving behavior, as measured by the standard deviation of speeds and vehicle LPs, and this was especially notable in curved road segments in daytime experiment. These experimental results revealed that the driving performance of participants with impaired dynamic visual acuity was deficient and unsafe. This confirmed that dynamic visual acuity levels are significant determinants of driving behavior, and they well explain driver performance levels. These findings suggest that the South Korean driver license system should include a test of dynamic visual acuity to create better and safer driving.

Driving Simulator Study: Eco-Driving Training System Based on Individual Characteristics

2019 ◽  
Vol 2673 (8) ◽  
pp. 463-476
Author(s):  
Ying Yao ◽  
Xiaohua Zhao ◽  
Jianming Ma ◽  
Chang Liu ◽  
Jian Rong
Keyword(s):  
Driving Simulator ◽  
Individual Characteristics ◽  
Training System ◽  
Video Training ◽  
Taxi Drivers ◽  
Professional Drivers ◽  
Customized Training ◽  
Driving Behaviors ◽  
Scene Management ◽  
Evaluation Algorithm

This research sought to establish an eco-driving training system based on a driving simulator. The eco-driving training system contained five modules: human machine interface, data management, scene management, mode management, and evaluation algorithm management. It was proposed to base the new eco-driving training system on drivers’ individual characteristics. This system first asked drivers to conduct a diagnostic drive on a stretch of roadway in a driving simulator. The data on each driver’s non-ecological driving behaviors under different events were collected. Then each driver was given a customized training course based on an evaluation of his/her driving behaviors during the diagnostic drive. This training process is called eco-driving training based on individual characteristics (EDTIC). Eighty taxi drivers were recruited and divided into two groups for eco-driving training. One group was trained by watching videos, and the other was trained by the EDTIC training. An analysis of results shows that the EDTIC training was significantly more effective than traditional video training. Under the EDTIC training, all driving behaviors improved and emissions and fuel consumption were greatly reduced; the reduction was as great as 8.3–8.4%. The EDTIC training was proven effective at improving the eco-driving behavior of taxi drivers (i.e., professional drivers), and it could also be employed to train other professional drivers (bus and truck drivers) and non-professional drivers.

scholarly journals Isolating the Effect of Off-Road Glance Duration on Driving Performance: An Exemplar Study Comparing HDD and HUD in Different Driving Scenarios

2021 ◽  
pp. 001872082110314
Author(s):  
Missie Smith ◽  
Kiran Bagalkotkar ◽  
Joseph L. Gabbard ◽  
David R. Large ◽  
Gary Burnett
Keyword(s):  
Visual Attention ◽  
User Interfaces ◽  
Human Performance ◽  
Driving Simulator ◽  
Driving Performance ◽  
Behavioral Changes ◽  
The Road ◽  
Driving Behaviors ◽  
Novel Method ◽  
The Impact

Objective We controlled participants’ glance behavior while using head-down displays (HDDs) and head-up displays (HUDs) to isolate driving behavioral changes due to use of different display types across different driving environments. Background Recently, HUD technology has been incorporated into vehicles, allowing drivers to, in theory, gather display information without moving their eyes away from the road. Previous studies comparing the impact of HUDs with traditional displays on human performance show differences in both drivers’ visual attention and driving performance. Yet no studies have isolated glance from driving behaviors, which limits our ability to understand the cause of these differences and resulting impact on display design. Method We developed a novel method to control visual attention in a driving simulator. Twenty experienced drivers sustained visual attention to in-vehicle HDDs and HUDs while driving in both a simple straight and empty roadway environment and a more realistic driving environment that included traffic and turns. Results In the realistic environment, but not the simpler environment, we found evidence of differing driving behaviors between display conditions, even though participants’ glance behavior was similar. Conclusion Thus, the assumption that visual attention can be evaluated in the same way for different types of vehicle displays may be inaccurate. Differences between driving environments bring the validity of testing HUDs using simplistic driving environments into question. Application As we move toward the integration of HUD user interfaces into vehicles, it is important that we develop new, sensitive assessment methods to ensure HUD interfaces are indeed safe for driving.

scholarly journals Implementing Surrogate Safety Measures in Driving Simulator and Evaluating the Safety Effects of Simulator-Based Training on Risky Driving Behaviors

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Eunhan Ka ◽  
Do-Gyeong Kim ◽  
Jooneui Hong ◽  
Chungwon Lee
Keyword(s):  
Driving Simulator ◽  
Driver Education ◽  
Risky Driving ◽  
Safety Measures ◽  
Novice Drivers ◽  
Elderly Drivers ◽  
Driving Behaviors ◽  
Commercial Drivers ◽  
Surrogate Safety Measures ◽  
Risky Driving Behaviors

Human errors cause approximately 90 percent of traffic accidents, and drivers with risky driving behaviors are involved in about 52 percent of severe traffic crashes. Driver education using driving simulators has been used extensively to obtain a quantitative evaluation of driving behaviors without causing drivers to be at risk for physical injuries. However, since many driver education programs that use simulators have limits on realistic interactions with surrounding vehicles, they are limited in reducing risky driving behaviors associated with surrounding vehicles. This study introduces surrogate safety measures (SSMs) into simulator-based training in order to evaluate the potential for crashes and to reduce risky driving behaviors in driving situations that include surrounding vehicles. A preliminary experiment was conducted with 31 drivers to analyze whether the SSMs could identify risky driving behaviors. The results showed that 15 SSMs were statistically significant measures to capture risky driving behaviors. This study used simulator-based training with 21 novice drivers, 16 elderly drivers, and 21 commercial drivers to determine whether a simulator-based training program using the SSMs is effective in reducing risky driving behaviors. The risky driving behaviors by novice drivers were reduced significantly with the exception of erratic lane-changing. In the case of elderly drivers, speeding was the only risky driving behavior that was reduced; the others were not reduced because of their difficulty with manipulating the pedals in the driving simulator and their defensive driving. Risky driving behaviors by commercial drivers were reduced overall. The results of this study indicated that the SSMs can be used to enhance drivers’ safety, to evaluate the safety of traffic management strategies as well as to reduce risky driving behaviors in simulator-based training.

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.

Positive Bias in Teenage Drivers With ADHD Within a Simulated Driving Task

2015 ◽  
Vol 22 (12) ◽  
pp. 1150-1157 ◽  
Author(s):  
Gregory A. Fabiano ◽  
Nicole K. Schatz ◽  
Kevin F. Hulme ◽  
Karen L. Morris ◽  
Rebecca K. Vujnovic ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Behavior Disorder ◽  
Driving Performance ◽  
Driving Ability ◽  
Disruptive Behavior Disorder ◽  
Global Rating ◽  
Positive Bias ◽  
Driving Behaviors ◽  
Teenage Drivers ◽  
Youth With Adhd

Objective: Youth with ADHD exhibit positive bias, an overestimation of ability, relative to external indicators. The positive bias construct is understudied in adolescents, particularly in the domain of driving. Study is needed as youth with ADHD experience greater negative outcomes in driving relative to typically developing teens. Method: Positive bias on a driving simulator task was investigated with 172 teenagers with ADHD, combined type. Youth participated in a driving simulation task and rated driving performance afterward. Results: Compared with external ratings of driving performance, youth overestimated driving competence for specific driving behaviors as well as globally. The global rating demonstrated a greater degree of positive bias. Greater positive bias on global ratings of driving ability also predicted greater rates of risky driving behaviors during the simulator exercise independent from disruptive behavior disorder symptoms. Conclusion: Results inform prevention and intervention efforts for teenage drivers with ADHD.

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