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Cited 9 time in webofscience Cited 12 time in scopus
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Driving Skill Modeling Using Neural Networks for Performance-Based Haptic Assistance SCIE SCOPUS

Title
Driving Skill Modeling Using Neural Networks for Performance-Based Haptic Assistance
Authors
이호진Kim, HyoungkyunChoi, Seungmoon
Date Issued
2021-06
Publisher
IEEE Systems, Man, and Cybernetics Society
Abstract
This article addresses a data-driven framework, modeling expert driving skills for performance-based haptic assistance using neural networks (NNs). We have built a haptic driving training simulator to collect expert driving data and to provide proper haptic feedback. We establish an expert driving skill model by training NNs with the collected data. Then, the skill model is applied to the performance-based haptic assistance to provide optimized references of the steering/pedaling movements. We evaluate the skill model and its application to the performance-based haptic assistance in two user experiments. The results of the first experiment demonstrate that our skill model has appropriately captured experts' steering/pedaling skills. The results of the second experiment show that our performance-based haptic assistance can help novice drivers perform steering as expert drivers, but cannot assist their pedaling performance.
URI
https://oasis.postech.ac.kr/handle/2014.oak/109403
DOI
10.1109/THMS.2021.3061409
ISSN
2168-2291
Article Type
Article
Citation
IEEE Transactions on Human-Machine Systems, vol. 51, no. 3, page. 198 - 210, 2021-06
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최승문CHOI, SEUNGMOON
Dept of Computer Science & Enginrg
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