Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Kruber, P"'
Metadata exchange is crucial for efficient geo-distributed fog computing. Existing solutions for metadata exchange overlook geo-awareness or lack adequate failure tolerance. We propose HFCS, a novel hybrid communication system that combines hierarchi
Externí odkaz:
http://arxiv.org/abs/2305.13385
An understanding and classification of driving scenarios are important for testing and development of autonomous driving functionalities. Machine learning models are useful for scenario classification but most of them assume that data received during
Externí odkaz:
http://arxiv.org/abs/2105.07635
Autor:
Morales, Eduardo Sánchez, Kruber, Friedrich, Botsch, Michael, Huber, Bertold, Higuera, Andrés García
Due to their capability of acquiring aerial imagery, camera-equipped Unmanned Aerial Vehicles (UAVs) are very cost-effective tools for acquiring traffic information. However, not enough attention has been given to the validation of the accuracy of th
Externí odkaz:
http://arxiv.org/abs/2005.06314
Publikováno v:
2020 IEEE Intelligent Vehicles Symposium (IV)
The availability of real-world data is a key element for novel developments in the fields of automotive and traffic research. Aerial imagery has the major advantage of recording multiple objects simultaneously and overcomes limitations such as occlus
Externí odkaz:
http://arxiv.org/abs/2004.08206
Publikováno v:
2018 21st International Conference on Intelligent Transportation Systems (ITSC)
A modification of the Random Forest algorithm for the categorization of traffic situations is introduced in this paper. The procedure yields an unsupervised machine learning method. The algorithm generates a proximity matrix which contains a similari
Externí odkaz:
http://arxiv.org/abs/2004.02121
Autor:
Kruber, Friedrich, Wurst, Jonas, Morales, Eduardo Sánchez, Chakraborty, Samarjit, Botsch, Michael
Publikováno v:
2019 IEEE Intelligent Vehicles Symposium (IV)
The goal of this paper is to provide a method, which is able to find categories of traffic scenarios automatically. The architecture consists of three main components: A microscopic traffic simulation, a clustering technique and a classification tech
Externí odkaz:
http://arxiv.org/abs/2004.02126
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
This work provides a comprehensive analysis on naturalistic driving behavior for highways based on the highD data set. Two thematic fields are considered. First, some macroscopic and microscopic traffic statistics are provided. These include the traf
Externí odkaz:
http://arxiv.org/abs/1903.04249
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Unit commitment problem on an electricity network consists in choosing the production plan of the plants (units) of a company in order to meet demand constraints. It is generally solved using a decomposition approach where demand constraints are rela
Externí odkaz:
http://arxiv.org/abs/1809.00548