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Fidelity Assessment of Motion Platform Cueing: Comparison of Driving Behavior under Various Motion Levels
by
Kunclova, Tereza
, Toman, Přemysl
, Bouchner, Petr
, El hamdani, Sara
, Novotný, Stanislav
, Svoboda, Josef
in
Algorithms
/ Artificial intelligence
/ Autonomous vehicles
/ Comparative analysis
/ driving simulator
/ driving simulator experiment
/ Eye movements
/ Kinematics
/ Laboratories
/ motion cues fidelity
/ motion platform
/ Motion sickness
/ real car experiment
/ Roads & highways
/ Sensors
/ Software
/ Virtual reality
/ Xsens MTi-G sensor
2023
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Fidelity Assessment of Motion Platform Cueing: Comparison of Driving Behavior under Various Motion Levels
by
Kunclova, Tereza
, Toman, Přemysl
, Bouchner, Petr
, El hamdani, Sara
, Novotný, Stanislav
, Svoboda, Josef
in
Algorithms
/ Artificial intelligence
/ Autonomous vehicles
/ Comparative analysis
/ driving simulator
/ driving simulator experiment
/ Eye movements
/ Kinematics
/ Laboratories
/ motion cues fidelity
/ motion platform
/ Motion sickness
/ real car experiment
/ Roads & highways
/ Sensors
/ Software
/ Virtual reality
/ Xsens MTi-G sensor
2023
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Fidelity Assessment of Motion Platform Cueing: Comparison of Driving Behavior under Various Motion Levels
by
Kunclova, Tereza
, Toman, Přemysl
, Bouchner, Petr
, El hamdani, Sara
, Novotný, Stanislav
, Svoboda, Josef
in
Algorithms
/ Artificial intelligence
/ Autonomous vehicles
/ Comparative analysis
/ driving simulator
/ driving simulator experiment
/ Eye movements
/ Kinematics
/ Laboratories
/ motion cues fidelity
/ motion platform
/ Motion sickness
/ real car experiment
/ Roads & highways
/ Sensors
/ Software
/ Virtual reality
/ Xsens MTi-G sensor
2023
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Fidelity Assessment of Motion Platform Cueing: Comparison of Driving Behavior under Various Motion Levels
Journal Article
Fidelity Assessment of Motion Platform Cueing: Comparison of Driving Behavior under Various Motion Levels
2023
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Overview
The present paper focuses on vehicle simulator fidelity, particularly the effect of motion cues intensity on driver performance. The 6-DOF motion platform was used in the experiment; however, we mainly focused on one characteristic of driving behavior. The braking performance of 24 participants in a car simulator was recorded and analyzed. The experiment scenario was composed of acceleration to 120 km/h followed by smooth deceleration to a stop line with prior warning signs at distances of 240, 160, and 80 m to the finish line. To assess the effect of the motion cues, each driver performed the run three times with different motion platform settings–no motion, moderate motion, and maximal possible response and range. The results from the driving simulator were compared with data acquired in an equivalent driving scenario performed in real conditions on a polygon track and taken as reference data. The driving simulator and real car accelerations were recorded using the Xsens MTi-G sensor. The outcomes confirmed the hypothesis that driving with a higher level of motion cues in the driving simulator brought more natural braking behavior of the experimental drivers, better correlated with the real car driving test data, although exceptions were found.
Publisher
MDPI AG,MDPI
Subject
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