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pro vyhledávání: '"Jonas Wurst"'
Autor:
Alberto Flores Fernández, Jonas Wurst, Eduardo Sánchez Morales, Michael Botsch, Christian Facchi, Andrés García Higuera
Publikováno v:
Sensors, Vol 22, Iss 12, p 4498 (2022)
The prediction of the motion of traffic participants is a crucial aspect for the research and development of Automated Driving Systems (ADSs). Recent approaches are based on multi-modal motion prediction, which requires the assignment of a probabilit
Externí odkaz:
https://doaj.org/article/ba3c3e2cf3f046a4909dab0370763159
Publikováno v:
IEEE Transactions on Intelligent Vehicles. 8:3506-3521
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e78481d13e4c0da411f8056f9acf99d4
https://doi.org/10.1109/tiv.2023.3260270
https://doi.org/10.1109/tiv.2023.3260270
Traffic scenario categorisation is an essential component of automated driving, for e.\,g., in motion planning algorithms and their validation. Finding new relevant scenarios without handcrafted steps reduce the required resources for the development
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::566267b9ca39759b64f1a9081e180e35
http://arxiv.org/abs/2105.07639
http://arxiv.org/abs/2105.07639
Detecting unknown and untested scenarios is crucial for scenario-based testing. Scenario-based testing is considered to be a possible approach to validate autonomous vehicles. A traffic scenario consists of multiple components, with infrastructure be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7403a47b1dbc23400ef6aeb6536757a
Publikováno v:
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::487de29a6b32c443fa6e1f19340d10c9
A novel unsupervised outlier score, which can be embedded into graph based dimensionality reduction techniques, is presented in this work. The score uses the directed nearest neighbor graphs of those techniques. Hence, the same measure of similarity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d57f0fa1c37dc55a6bad83593b9ced65
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:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb476542a8d3a34cb67a30e7ee496579
https://doi.org/10.1109/ivs.2019.8813994
https://doi.org/10.1109/ivs.2019.8813994