A
Andras Kemeny
Researcher at Renault
Publications - 114
Citations - 2460
Andras Kemeny is an academic researcher from Renault. The author has contributed to research in topics: Driving simulator & Virtual reality. The author has an hindex of 21, co-authored 114 publications receiving 2183 citations. Previous affiliations of Andras Kemeny include Centre national de la recherche scientifique & Arts et Métiers ParisTech.
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Journal ArticleDOI
Evaluating perception in driving simulation experiments.
Andras Kemeny,Francesco Panerai +1 more
TL;DR: Recent psychophysical studies have revealed an unexpectedly important contribution of vestibular cues in distance perception and steering, prompting a re-evaluation of the role of visuo-vestibular interaction in driving simulation studies.
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Role of Lateral Acceleration in Curve Driving: Driver Model and Experiments on a Real Vehicle and a Driving Simulator
TL;DR: A new driver model, assuming drivers control a variable safety margin of perceived lateral acceleration according to their anticipated steering deviations, predicts that extreme values of lateral acceleration in curves decrease quadratically with speed, in accordance with experimental data obtained in a vehicle driven on a test track and in a motion-based driving simulator.
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Motion cueing in the renault driving simulator
Gilles Reymond,Andras Kemeny +1 more
TL;DR: In this paper, a non-linear motion cueing algorithm was developed to anticipate and reduce these false motion cues in the Renault Dynamic Simulator, which is capable of directly rendering transient vehicle accelerations and sustained linear acceleration cues.
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Active, passive and snapshot exploration in a virtual environment: influence on scene memory, reorientation and path memory
TL;DR: The results suggest that (1) 2D image features from a visual scene are memorized and (2) pointing towards the origin of the path relies on motion duration integration or a frame of reference integrated during displacement.
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Model-based predictive motion cueing strategy for vehicle driving simulators
TL;DR: In this paper, a model-based predictive control theory is used for the design of motion rendering strategies in a high-performance automotive driving simulator, where actuator constraints are always respected, and the use of motion workspace is maximized during simulations.