Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Moritz Werling"'
Publikováno v:
Frontiers in Future Transportation, Vol 4 (2023)
Externí odkaz:
https://doaj.org/article/d370d6cae30b41839d638d3fdae51ee5
Publikováno v:
Frontiers in Future Transportation, Vol 4 (2023)
Achieving feasible, smooth and efficient trajectories for autonomous vehicles which appropriately take into account the long-term future while planning, has been a long-standing challenge. Several approaches have been considered, roughly falling unde
Externí odkaz:
https://doaj.org/article/6621013391f345dd85d55b79a5c3a31b
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72c22277cad794c7a5578d2059d968fa
https://doi.org/10.1109/iros51168.2021.9636672
https://doi.org/10.1109/iros51168.2021.9636672
Q-learning with Long-term Action-space Shaping to Model Complex Behavior for Autonomous Lane Changes
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1880537c6e02768b9ba9c7a7706506c
https://doi.org/10.1109/iros51168.2021.9636668
https://doi.org/10.1109/iros51168.2021.9636668
Publikováno v:
ICRA
Well-established optimization-based methods can guarantee an optimal trajectory for a short optimization horizon, typically no longer than a few seconds. As a result, choosing the optimal trajectory for this short horizon may still result in a sub-op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d710d650a5f3fb791d68c847098ae08e
https://doi.org/10.1109/icra48506.2021.9560777
https://doi.org/10.1109/icra48506.2021.9560777
Challenging problems of deep reinforcement learning systems with regard to the application on real systems are their adaptivity to changing environments and their efficiency w.r.t. computational resources and data. In the application of learning lane
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a928ba168d356ed6cc6fe11204cd33e3
Publikováno v:
ICRA
The common pipeline in autonomous driving systems is highly modular and includes a perception component which extracts lists of surrounding objects and passes these lists to a high-level decision component. In this case, leveraging the benefits of de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2523ec863ad02f62acced730556141db
Publikováno v:
IROS
In many real-world decision making problems, reaching an optimal decision requires taking into account a variable number of objects around the agent. Autonomous driving is a domain in which this is especially relevant, since the number of cars surrou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f427d63d5378086ad26af40ccb8f1a20
Publikováno v:
at - Automatisierungstechnik. 64:786-794
Zusammenfassung Die aus der Literatur bekannten Verfahren zur Optimierung von Fahrtrajektorien überfordern kurz und mittelfristig die Fahrzeugsteuergeräte hinsichtlich ihrer Rechenleistung. Um auch neu aufkommenden Qualitätsanforderungen zu entspr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5ae1145addb7a44451d28f816ad2b01
https://doi.org/10.1515/auto-2016-0074
https://doi.org/10.1515/auto-2016-0074
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. :1-10
In this paper, a trajectory optimization algorithm is proposed, which formulates the lateral vehicle guidance task along a reference curve as a constrained optimal control problem. The optimization problem is solved by means of a linear time-varying
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db9013fc4c5f90eb562418d239b5f877
https://doi.org/10.1109/tits.2016.2614705
https://doi.org/10.1109/tits.2016.2614705