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pro vyhledávání: '"Han, Teawon"'
Autor:
Han, Teawon
Automated Vehicles (AVs) must choose optimal driving actions under various traffic situations. However, designing their decision-making systems is challenging because it's impossible to anticipate all possible traffic situations. Previous studies pro
In this paper, an online evolving framework is proposed to detect and revise a controller's imperfect decision-making in advance. The framework consists of three modules: the evolving Finite State Machine (e-FSM), action-reviser, and controller modul
Externí odkaz:
http://arxiv.org/abs/2006.08092
An online evolving framework is proposed to support modeling the safe Automated Vehicle (AV) control system by making the controller able to recognize unexpected situations and react appropriately by choosing a better action. Within the framework, th
Externí odkaz:
http://arxiv.org/abs/1908.10823
This paper proposes a framework to recognize driving intentions and to predict driving behaviors of lane changing on the highway by using externally sensable traffic data from the host-vehicle. The framework consists of a driving characteristic estim
Externí odkaz:
http://arxiv.org/abs/1908.10820
Autor:
Hejase, Bilal *, Yurtsever, Ekim *, Han, Teawon, Singh, Baljeet, Filev, Dimitar P., Tseng, H. Eric, Ozguner, Umit *
Publikováno v:
In IFAC PapersOnLine 2022 55(24):129-134
Autor:
Han, Teawon1 (AUTHOR) than10@ford.com, Nageshrao, Subramanya P.1 (AUTHOR) snageshr@ford.com, Filev, Dimitar2 (AUTHOR) dfilev@ford.com, Redmill, Keith3 (AUTHOR) redmill.1@osu.edu, Ozguners, Umit3 (AUTHOR) ozguner.1@osu.edu
Publikováno v:
IEEE Transactions on Systems, Man & Cybernetics. Systems. Sep2022, Vol. 52 Issue 9, p5723-5735. 13p.
Akademický článek
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Publikováno v:
IFAC-PapersOnLine; January 2020, Vol. 53 Issue: 2 p8118-8123, 6p
Publikováno v:
2012 IEEE International Conference on Robotics & Biomimetics (ROBIO); 2012, p1256-1261, 6p