Zobrazeno 1 - 10
of 39 787
pro vyhledávání: '"Mårtensson, A."'
Autor:
Wright, Brian1 (AUTHOR) brian.wright@mbzuh.ac.ae
Publikováno v:
Journal of Islamic Studies. Sep2024, Vol. 35 Issue 3, p397-400. 4p.
Autor:
ÇOLAK, Yaşar1 yasar.colak@ihu.edu.tr
Publikováno v:
Amasya Theology Journal / Amasya Ilahiyat Dergisi. Jun2021, Issue 16, p125-159. 35p.
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This paper proposes an observer-based formation tracking control approach for multi-vehicle systems with second-order motion dynamics, assuming that vehicles' relative or global position and velocity measurements are unavailable. It is assumed that a
Externí odkaz:
http://arxiv.org/abs/2409.08675
In this paper, we introduce a temporal logic-based safety filter for Autonomous Intersection Management (AIM), an emerging infrastructure technology for connected vehicles to coordinate traffic flow through intersections. Despite substantial work on
Externí odkaz:
http://arxiv.org/abs/2408.14870
In this work, we present a transformer-based framework for predicting future pedestrian states based on clustered historical trajectory data. In previous studies, researchers propose enhancing pedestrian trajectory predictions by using manually craft
Externí odkaz:
http://arxiv.org/abs/2408.15250
In this work, we address the problem of charging coordination between electric trucks and charging stations. The problem arises from the tension between the trucks' nontrivial charging times and the stations' limited charging facilities. Our goal is
Externí odkaz:
http://arxiv.org/abs/2407.10307
In this work, we propose an approach for ensuring the safety of vehicles passing through an intelligent intersection. There are many proposals for the design of intelligent intersections that introduce central decision-makers to intersections for enh
Externí odkaz:
http://arxiv.org/abs/2405.11300
Autor:
Arfvidsson, Kaj Munhoz, Fragkedaki, Kleio, Jiang, Frank J., Narri, Vandana, Lindh, Hans-Cristian, Johansson, Karl H., Mårtensson, Jonas
In this work, we present a small-scale testbed for evaluating the real-life performance of cellular V2X (C-V2X) applications on 5G cellular networks. Despite the growing interest and rapid technology development for V2X applications, researchers stil
Externí odkaz:
http://arxiv.org/abs/2405.05911
Publikováno v:
2023 IEEE/CVF CVPRW, pp. 4454-4463
This paper is about effectively utilizing synthetic data for training deep neural networks for industrial parts classification, in particular, by taking into account the domain gap against real-world images. To this end, we introduce a synthetic data
Externí odkaz:
http://arxiv.org/abs/2404.08778