Effects of Driving Simulator Fidelity on the Driving Behavior of Emergency Braking

Tu, Huizhao; Zhang, K; Liu, H; Sun, Lijun

doi:10.1061/9780784414255.028

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…The researchers found that participants applied more braking force in each successive trial without motion cues; however, braking force remained stable with motion cues. By constructing two scenarios with sunny and foggy weather, respectively, Tu et al found that the motion cues have no effect on acceleration behavior and expected speed, but they did significantly affect deceleration behavior, especially in conditions of thick fog ( 25 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Effect of Motion Cues on Highway Driving Performance in Simulated Driving

Wang

Hurwitz

et al. 2023

Transportation Research Record: Journal of the Transportation R

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The motion system is a major component of a driving simulator. It provides motion cues in various directions with different degrees of freedom (DOF). Different DOF could influence response variables widely used in highway design safety evaluation conducted in simulators. Few studies, though, have comprehensively explored the effect of driving simulator motion cues on driving performance. The high-fidelity Tongji University Driving Simulator (TUDS) was used to separately compare five dependent variables: speed, speed change, lane deviation, longitudinal acceleration, and lateral acceleration. The Wilcoxon signed-rank test was used to examine the difference for each variable using 8-DOF and fixed-base motion system configurations for nine types of combined highway alignments. A subjective assessment of participants’ driving experience was conducted, and the chi-square test for each term was used to compare the difference in motion system fidelity and adverse reactions between the two configurations. Results show that: (1) speed and lateral acceleration are more likely to be significantly affected by motion cues than speed change, lane deviation, and longitudinal acceleration; (2) the horizontal curve with up-grade is the type of combined alignment where speed and lateral acceleration are mostly affected; (3) characteristics of the five variables in different combined alignments vary between the two simulators; (4) the 8-DOF motion system provides better perceived motion fidelity than the fixed-base system does, and the 8-DOF simulator causes less discomfort and tiredness in simulator sickness; and (5) the presence of motion cues is suggested for highways with complex combined curves when focusing on speed and lateral acceleration.

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Section: Literature Reviewmentioning

confidence: 99%

Effect of Motion Cues on Highway Driving Performance in Simulated Driving

Wang

Hurwitz

et al. 2023

Transportation Research Record: Journal of the Transportation R

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“…Many researchers have analyzed the braking behaviors in some urgent scenarios related to potential accidents (Wu et al 2018;Li et al 2020;Pawar et al 2020). Moreover, other researchers studied the braking actions in usual driving environments (Tu et al 2015;Li et al 2017;Xiao et al 2019;Zhu et al 2021). Most of the research investigated braking as a whole process but did not focus on pre-braking separately.…”

Section: Braking Motion Analysis and Pre-braking Behaviormentioning

confidence: 99%

Pre-braking behaviors analysis based on Hilbert–Huang transform

Zhu

Dong

et al. 2022

CCF Trans. Pervasive Comp. Interact.

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Previous studies have shown that about 90% of traffic accidents are due to human error, which means that human factors may affect a driver's braking behaviors and thus their driving safety, especially when the driver makes a braking motion. However, most studies have mounted sensors on the brake pad, ignoring to some extent an analysis of the driver's behavior before the brake pad is pressed (pre-braking). Therefore, to determine the effect of different human factors on drivers' pre-braking behaviors, this study focused on analyzing drivers' local joints (knee, ankle, and toe) by a motion capture device. A Hilbert–Huang Transform (HHT)-based local human body movement analysis method was used to decompose the realistic complex pre-braking actions into sub-actions such as intrinsic mode functions (IMF1, IMF2, etc.). Analysis of the results showed that IMF1 is a common and necessary action when pre-braking for all drivers, and IMF2 may be the safety assurance action that allows right-foot transverse movement at the beginning part of the pre-braking process. We also found that the experienced, male, and Phys.50 groups may have consistent characteristics in the HHT scheme, which could mean that such drivers would have better performance and efficiency during the pre-braking process. The results of this study will be useful in decomposing and discerning the specific actions that lead to accidents, providing insights into driver training for novice drivers, and guiding the construction of daily automated driver assistance or accident prevention systems (advanced driver assistance systems, ADASs).

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Rule obedience as a mediator between normlessness and risky driving in hazy conditions

Jiang

Rau

2018

Transportation Research Part F: Traffic Psychology and Behaviou

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Effects of Driving Simulator Fidelity on the Driving Behavior of Emergency Braking

Cited by 3 publications

References 3 publications

Effect of Motion Cues on Highway Driving Performance in Simulated Driving

Effect of Motion Cues on Highway Driving Performance in Simulated Driving

Pre-braking behaviors analysis based on Hilbert–Huang transform

Rule obedience as a mediator between normlessness and risky driving in hazy conditions

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