Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Probst, Malte"'
Driver support systems that include human states in the support process is an active research field. Many recent approaches allow, for example, to sense the driver's drowsiness or awareness of the driving situation. However, so far, this rich informa
Externí odkaz:
http://arxiv.org/abs/2306.03849
Publikováno v:
Transactions on Intelligent Vehicles (TIV 2022)
The survival analysis of driving trajectories allows for holistic evaluations of car-related risks caused by collisions or curvy roads. This analysis has advantages over common Time-To-X indicators, such as its predictive and probabilistic nature. Ho
Externí odkaz:
http://arxiv.org/abs/2303.08458
Publikováno v:
Intelligent Transportation Systems Conference (ITSC 2019)
We address the problem of motion planning for four-way intersection crossings with right-of-ways. Road safety typically assigns liability to the follower in rear-end collisions and to the approaching vehicle required to yield in side crashes. As an a
Externí odkaz:
http://arxiv.org/abs/2303.07936
Publikováno v:
Transactions on Intelligent Vehicles 2019
Risk assessment is a central element for the development and validation of Autonomous Vehicles (AV). It comprises a combination of occurrence probability and severity of future critical events. Time Headway (TH) as well as Time-To-Contact (TTC) are c
Externí odkaz:
http://arxiv.org/abs/2303.07181
We consider the problem of correct motion planning for T-intersection merge-ins of arbitrary geometry and vehicle density. A merge-in support system has to estimate the chances that a gap between two consecutive vehicles can be taken successfully. In
Externí odkaz:
http://arxiv.org/abs/2303.07047
Publikováno v:
International Conference on Robotics and Automation Engineering (ICRAE 2022)
Self-driving cars face complex driving situations with a large amount of agents when moving in crowded cities. However, some of the agents are actually not influencing the behavior of the self-driving car. Filtering out unimportant agents would inher
Externí odkaz:
http://arxiv.org/abs/2303.06935
Autor:
Kollatschny, Wolfram, Grupe, Dirk, Parker, Michael L., Ochmann, Martin W., Schartel, Norbert, Romero-Colmenero, Encarni, Winkler, Hartmut, Komossa, Stefanie, Famula, Philipp, Probst, Malte A., Santos-Lleo, Maria
Publikováno v:
A&A 670, A103 (2023)
IRAS23226-3843 has previously been classified as a changing-look AGN based on X-ray and optical spectral variations. In 2019, Swift observations revealed a strong rebrightening in X-ray and UV fluxes in comparison to observations in 2017. We took fol
Externí odkaz:
http://arxiv.org/abs/2212.07270
Reinforcement Learning (RL) can enable agents to learn complex tasks. However, it is difficult to interpret the knowledge and reuse it across tasks. Inductive biases can address such issues by explicitly providing generic yet useful decomposition tha
Externí odkaz:
http://arxiv.org/abs/2212.05298
Publikováno v:
JHEP 11 (2022) 163
We study the possible BPS Wilson loops in three-dimensional ${\cal N}=4$ Chern-Simons-matter theory which involve only the gauge field and bilinears of the scalars. Previously known examples are the analogues of the Gaiotto-Yin loops preserving four
Externí odkaz:
http://arxiv.org/abs/2210.03758
Publikováno v:
JHEP 08 (2022) 165
We construct new large classes of BPS Wilson hyperloops in three-dimensional ${\cal N}=4$ quiver Chern-Simons-matter theory on $S^3$. The main strategy is to start with the 1/2 BPS Wilson loop of this theory, choose any linear combination of the supe
Externí odkaz:
http://arxiv.org/abs/2206.07390