scholarly journals Influence of Landscape Design on Driving Behavior Based on Slope Illusion

2022 ◽  
Vol 2022 ◽  
pp. 1-7
Author(s):  
Hao Li ◽  
Yueyang Zhang
Keyword(s):  
Simulation Experiment ◽  
Driving Simulator ◽  
Lateral Position ◽  
Driving Behavior ◽  
Driving Safety ◽  
Plant Spacing ◽  
Negative Consequences ◽  
Driving Behaviors ◽  
Speed Perception ◽  
Driving Stability

In a continuous downhill section of a mountain highway, factors such as road alignment, roadside environment, and other visual characteristics will impact the slope illusion drivers experience and engage in unsafe driving behaviors. To improve the negative consequences of slope illusion and driving safety in continuous downhill sections, the effects of plant spacing, height, roadside distance, and color on driving behavior were all studied by simulating the plant landscape in a virtual environment. A driving simulator and UC-win/road software were used to conduct an indoor driving simulation experiment, and parameters such as speed and lateral position offset were used as the evaluation indices of driving stability to reflect the driver’s speed perception ability with subjective equivalent speeds. The results show that a plant landscape with appropriate plant spacing, height, roadside separation, and color is conducive to improving driving stability. Furthermore, a landscape with a height of 3 m, spacing of 10 m, roadside spacing of 0.75 m, and appropriate color matching can enhance the slope perception ability and speed perception ability of drivers, which is conducive to improving the driving safety of continuous downhill sections.

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.

Looking at Mind Wandering During Driving Through the Windows of PCA and t-SNE

2018 ◽  
Vol 62 (1) ◽  
pp. 1863-1867 ◽  
Author(s):  
Areen Alsaid ◽  
John D. Lee ◽  
Daniel M. Roberts ◽  
Daniela Barrigan ◽  
Carryl L. Baldwin
Keyword(s):  
Performance Measures ◽  
Principal Component ◽  
Mind Wandering ◽  
Lateral Position ◽  
Driving Behavior ◽  
Driving Safety ◽  
Steering Wheel ◽  
Attentional State ◽  
Reduction Techniques ◽  
Dimensionality Reduction Techniques

Mind wandering is a poorly understood phenomenon that can undermine driving safety. Driving performance measures have been found to be associated with mind wandering (e.g., steering wheel movements, standard deviation of lateral position, and speed variation). However, no one measure can fully describe the driver behavior associated with mind wandering. Therefore, in this paper we explore the effect of mind wandering on nine steering measures with data collected from a study that included nine drivers over two sessions of driving over five days. Participants were periodically probed to report their attentional state–whether they were mind wandering or focusing on the task. We used two dimensionality-reduction techniques—Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE)—to visualize the dimensions underlying the nine measures. Comparing PCA to t-SNE highlights the benefits of t-SNE in revealing the fine structure that differentiates driving behavior. These visualizations show that a) driver engagement increased during roadway curve segments, and b) mind wandering manifests itself through several types of steering behavior.

scholarly journals Influence of multiscale visual information on driver’s perceived speed in highway tunnels

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881896
Author(s):  
Zhanji Zheng ◽  
Zhigang Du ◽  
Qiaojun Xiang ◽  
Guojun Chen
Keyword(s):  
High Frequency ◽  
Visual Information ◽  
Driving Simulator ◽  
Driving Safety ◽  
Small Scale ◽  
Psychophysical Experiment ◽  
Vehicle Speed ◽  
Medium Frequency ◽  
Medium Scale ◽  
Speed Perception

Speed illusion is the leading contributing factor to traffic accidents in highway tunnels. This study aimed to estimate the influence of visual information at different scales and frequencies on drivers’ visual perception and driving safety in highway tunnels. The speed perception of drivers was measured using the stimulus of subjectively equivalent speeds as an index. Thirty drivers were recruited to conduct a psychophysical experiment on speed perception using a driving simulator. The large-, medium- and small-scale visual information in a frequency range of 0.1–32 Hz were used in the experimental scene to generate scenes for comparison. The results show that high-frequency visual information (2–32 Hz) might lead to driver overestimation of vehicle speed in tunnels, while medium-frequency (0.4–1 Hz) and low-frequency (0.1–0.2 Hz) visual information contribute to speed underestimation. The medium-scale information had the largest speed overestimation effect, followed by large- and small-scale information (significant differences of 2–8 Hz). Medium-scale visual information below 8 Hz had the lowest degree of dispersion of speed perception. Therefore, the use of integrated high-frequency, medium-scale visual information and medium-frequency, large- and small-scale visual information is suggested to reduce the speed illusion of drivers and ensure driving safety.

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 Increased visual and cognitive demands emphasize the importance of meeting visual needs at all distances while driving

2020 ◽  
Author(s):  
Amigale Patoine ◽  
Laura Mikula ◽  
Sergio Mejía-Romero ◽  
Jesse Michaels ◽  
Océane Keruzore ◽  
...  
Keyword(s):  
Visual Acuity ◽  
Cognitive Load ◽  
Driving Simulator ◽  
Negative Impact ◽  
Visual Quality ◽  
Driving Behavior ◽  
Driving Safety ◽  
Quality Degradation ◽  
Driving Scenario ◽  
The Impact

ABSTRACTHaving an optimal quality of vision as well as adequate cognitive capacities is known to be essential for driving safety. However, the interaction between vision and cognitive mechanisms while driving remains unclear. We hypothesized that, in a context of high cognitive load, reduced visual acuity would have a negative impact on driving behavior, even when the acuity corresponds to the legal threshold for obtaining a driving license in Canada, and that the impact observed on driving performance would be greater with the increase in the threshold of degradation of visual acuity. In order to investigate this relationship, we examined driving behavior in a driving simulator under optimal and reduced vision conditions through two scenarios involving different levels of cognitive demand. These were: 1. a simple rural driving scenario with some pre-programmed events and 2. a highway driving scenario accompanied by a concurrent task involving the use of a navigation device. Two groups of visual quality degradation (lower/ higher) were evaluated according to their driving behavior. The results support the hypothesis: Driving behavior was less stable under reduced visual quality in the context of a high cognitive load and this effect was exacerbated when visual quality was more severely altered. These results support the idea that visual quality degradation impacts driving behavior when combined with a high mental workload driving environment while specifying that this impact is not present in the context of low cognitive load driving condition.

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.

Using Real-Time and Post Hoc Feedback to Improve Driving Safety for Novice Drivers

2016 ◽  
Vol 60 (1) ◽  
pp. 1936-1940 ◽  
Author(s):  
Sheila G. Klauer ◽  
Tina B. Sayer ◽  
Peter Baynes ◽  
Gayatri Ankem
Keyword(s):  
Real Time ◽  
Motor Vehicle ◽  
Driving Behavior ◽  
Driving Safety ◽  
Risky Driving ◽  
Novice Drivers ◽  
Safe Driving ◽  
Driving Behaviors ◽  
Post Hoc ◽  
Risky Driving Behaviors

Introduction. Motor vehicle crashes remain the leading cause of fatalities among teens in the U.S. (National Center for Injury Prevention and Control, 2013). Prior research suggests that real-time and post hoc feedback can improve teen driver behavior. The Driver Coach Study (DCS) aimed to improve teens’ safe driving habits by providing them real-time feedback and post hoc feedback to a broader range of risky driving behaviors that have never been used in previous studies. Exposure data were also collected so that rates of risky driving behaviors over time could be assessed. Post hoc feedback, which included an electronic report card of risky driving behavior as well as video clips, was provided to both teens and parents via email and secure website link. Method. Ninety-two teen/parent dyads were recruited in southwest Virginia to have a data acquisition system (DAS) installed in their vehicles within two weeks of receiving their learner’s permit. Data were collected through the nine-month (minimum) learner’s permit phase plus seven months of provisional licensure. Feedback was only provided for the first six months of post licensure, then turned off to assess whether teenagers returned to unsafe driving behavior. Trained data coders reviewed 15 seconds of video surrounding each risky driving maneuver, and recorded driver errors such as poor vehicle control, poor speed selection, drowsiness, etc., for each event. Results. In this paper, the relationship between driver coaching and driver errors will be examined across the six-month feedback phase and also compared to the seventh month when feedback was turned off. Conclusions. This study has implications for the design of future monitoring and feedback systems, as it is currently unknown whether these devices can improve novice drivers’ crash rates.

scholarly journals State Machine Approach for Lane Changing Driving Behavior Recognition

Automation ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 68-79
Author(s):  
Ruth David ◽  
Sandra Rothe ◽  
Dirk Söffker
Keyword(s):  
Driving Simulator ◽  
Driving Behavior ◽  
State Machine ◽  
The State ◽  
Behavior Recognition ◽  
Lane Changing ◽  
Recognition Model ◽  
Driving Behaviors ◽  
Current State ◽  
Driving Assistance

Research in understanding human behavior is a growing field within the development of Advanced Driving Assistance Systems (ADASs). In this contribution, a state machine approach is proposed to develop a driving behavior recognition model. The state machine approach is a behavior model based on the current state and a given set of inputs. Transitions to different states occur or we remain in the same state producing outputs. The transition between states depends on a set of environmental and driving variables. Based on a heuristic understanding of driving situations modeled as states, as well as one of the related actions modeling the state, using an assumed relation between them as the state machine topology, in this paper, a crisp approach is applied to adapt the model to real behaviors. An important aspect of the contribution is to introduce a trainable state machine-based model to describe drivers’ lane changing behavior. Three driving maneuvers are defined as states. The training of the model is related to the definition/tuning of transition variables (and state definitions). Here, driving data are used as the input for training. The non-dominated sorting genetic algorithm II is used to generate the optimized transition threshold. Comparing the data of actual human driving behaviors collected using driving simulator experiments and the calculated driving behaviors, this approach is able to develop a personalized behavior recognition model. The newly established algorithm presents an easy to apply, reliable, and interpretable AI approach.

Effectiveness of Warning Piles on Driving Behavior on the Curve of Low-Grade Highway

2021 ◽  
pp. 036119812199635
Author(s):  
Yibing Liu ◽  
Xiaohua Zhao ◽  
Jia Li ◽  
Yang Bian ◽  
Jianming Ma
Keyword(s):  
Theoretical Basis ◽  
Driving Simulator ◽  
Engineering Application ◽  
Lateral Position ◽  
Driving Behavior ◽  
Low Grade ◽  
Vehicle Speed ◽  
Speed Increase ◽  
Lane Position ◽  
Rural Highway

To develop a scientific and practicable guideline for implementing warning piles on Chinese low-grade highways, it is necessary to study the effect of warning piles on driving performance in different road alignments and environments. Based on a driving simulator, this paper evaluates the effect of unilateral and bilateral warning piles on vehicle speed and lateral position on a two-lane rural highway curve with different road geometries. The results show a significant effect of bilateral warning piles on speed control, which becomes more obvious as the radius of the curve decreases and the superelevation increases. In sharp curves, vehicle speed increases rapidly in the second half of the curve, and bilateral warning piles could significantly control speed increase to prevent danger. Meanwhile, the effect of bilateral warning piles on keeping vehicles in a safer lane position is also statistically significant in the second half of the curve. With a decreasing radius and an increasing superelevation, the value of the maximum lateral position will increase. Bilateral warning piles could reduce the lateral position to keep the vehicle on a stable track. Moreover, bilateral warning piles could also perform better at night. This paper studies both unilateral and bilateral warning piles’ effects on driving behavior in different road geometries, thus providing a theoretical basis for the engineering application of warning piles.

scholarly journals Driving simulator study of the relationship between motion strategy preference and self-reported driving behavior

SIMULATION ◽  
2021 ◽  
pp. 003754972199971
Author(s):  
Carolina Rengifo ◽  
Jean-Rémy Chardonnet ◽  
Hakim Mohellebi ◽  
Damien Paillot ◽  
Andras Kemeny
Keyword(s):  
Motion Perception ◽  
Driving Simulator ◽  
Principal Component ◽  
Lateral Position ◽  
Driving Behavior ◽  
Driving Simulators ◽  
Motion Cueing ◽  
Perception Model ◽  
Positive Correlations

Faithful motion restitution in driving simulators normally focuses on track monitoring and maximizing the platform workspace by leaving aside the principal component—the driver. Therefore, in this work we investigated the role of the motion perception model on motion cueing algorithms from a user’s viewpoint. We focused on the driving behavior influence regarding motion perception in a driving simulator. Participants drove a driving simulator with two different configurations: (a) using the platform dynamic model and (b) using a supplementary motion perception model. Both strategies were compared and the participants’ data were classified according to the strategy they preferred. To this end, we developed a driving behavior questionnaire aiming at evaluating the self-reported driving behavior influence on participants’ motion cueing preferences. The results showed significant differences between the participants who chose different strategies and the scored driving behavior in the hostile and violations factors. In order to support these findings, we compared participants’ behaviors and actual motion driving simulator indicators such as speed, jerk, and lateral position. The analysis revealed that motion preferences arise from different reasons linked to the realism or smoothness in motion. Also, strong positive correlations were found between hostile and violation behaviors of the group who preferred the strategy with the supplementary motion perception model, and objective measures such as jerk and speed on different road segments. This indicates that motion perception in driving simulators may depend not only on the type of motion cueing strategy, but may also be influenced by users’ self-reported driving behaviors.

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