Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Tong Duy Son"'
Autor:
Nicolas Ochoa Lleras, Tong Duy Son, Sebastian vom Dorff, Adam Molin, Hasan Esen, Maxime Denniel, Maximilian Kneissl, Sandra Hirche
Publikováno v:
IFAC-PapersOnLine. 53:17564-17571
The development of highly automated driving functions requires rigorous testing to demonstrate the safety and functionality of the automated vehicle. One open question is how to perform such tests to sufficiently prove the vehicle’s capabilities. D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b57e0f62aeca94ebbbc5185c2eb5e29
https://doi.org/10.1016/j.ifacol.2020.12.2669
https://doi.org/10.1016/j.ifacol.2020.12.2669
Publikováno v:
2021 21st International Conference on Control, Automation and Systems (ICCAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efb3f3b9bd6bd0757d6a1883d52eae96
https://doi.org/10.23919/iccas52745.2021.9649993
https://doi.org/10.23919/iccas52745.2021.9649993
In this paper, we present the development and deployment of an embedded optimal control strategy for autonomous driving applications on a Ford Focus road vehicle. Non-linear model predictive control (NMPC) is designed and deployed on a system with ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a77fb0c008687972a5b119b7c08e6ab
http://arxiv.org/abs/2110.03349
http://arxiv.org/abs/2110.03349
Publikováno v:
ITSC
This paper presents a safe imitation learning approach for autonomous vehicle driving, with attention on real-life human driving data and experimental validation. In order to increase occupant's acceptance and gain drivers' trust, the autonomous driv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06bd5438682a4eba1e77c789dd1a9537
https://doi.org/10.1109/itsc48978.2021.9564785
https://doi.org/10.1109/itsc48978.2021.9564785
Publikováno v:
2021 IEEE Intelligent Vehicles Symposium (IV).
This paper presents a Model in the Loop (MiL) framework to validate embedded autonomous driving (AD) and advanced driver assistant systems (ADAS) algorithms development. Recently, it has been recognized in the autonomous driving industry that simulat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f18ad84891f3158c6b5dde4fd06e9d5
https://doi.org/10.1109/iv48863.2021.9575530
https://doi.org/10.1109/iv48863.2021.9575530
Publikováno v:
CCTA
This paper presents an investigation of Gaussian Processes (GPs) in combination with model predictive control (MPC) for autonomous driving control on slippery snowy road conditions. A double lane change scenario with two different road friction coeff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94b764dea6411e80354a764a11d28d3d
https://doi.org/10.1109/ccta41146.2020.9206260
https://doi.org/10.1109/ccta41146.2020.9206260
Publikováno v:
ACC
Autonomous vehicle driving systems face the challenge of providing safe, feasible and human-like driving policy quickly and efficiently. The traditional approach usually involves a search or optimization-based planning followed by a model-based contr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9d8f414ca3806e58aee101871f91ba1
https://lirias.kuleuven.be/handle/20.500.12942/688375
https://lirias.kuleuven.be/handle/20.500.12942/688375
Autor:
Quan Nguyen, Tong Duy Son
Publikováno v:
CDC
This paper presents a novel control framework to handle safety-critical control for non-affine nonlinear systems. The proposed control development is considered to deal with safety-critical aspects in autonomous vehicle driving. The safety constraint
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2b45a8e69dd1399a4b3a953d197aac9
https://doi.org/10.1109/cdc40024.2019.9029446
https://doi.org/10.1109/cdc40024.2019.9029446
Publikováno v:
European Journal of Control. 33:35-42
This paper presents a multi-objective iterative learning control (ILC) design approach that realizes an optimal trade-off between robust convergence, converged tracking performance, convergence speed, and input constraints. Linear time-invariant sing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1418ff38afe37690b74ee6eb0936c0af
https://doi.org/10.1016/j.ejcon.2016.10.001
https://doi.org/10.1016/j.ejcon.2016.10.001
Publikováno v:
IEEE Transactions on Automatic Control. 61:1063-1068
This paper presents an approach to deal with model uncertainty in iterative learning control (ILC). Model uncertainty generally degrades the performance of conventional learning algorithms. To deal with this problem, a robust worst-case norm-optimal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17e33e37ceb14f7bee525341eabfa052
https://doi.org/10.1109/tac.2015.2457785
https://doi.org/10.1109/tac.2015.2457785