Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hannes Reichert"'
Publikováno v:
ISC2
Complex inner-city junctions are among the most critical traffic areas for injury and fatal accidents. The development of highly automated driving (HAD) systems struggles with the complex and hectic everyday life within those areas. Sensor-equipped s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a700f278eb78b74414049f430a10f9d1
http://arxiv.org/abs/2307.06177
http://arxiv.org/abs/2307.06177
Publikováno v:
2022 IEEE Intelligent Vehicles Symposium (IV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d3584979dc8b999d892a7ea0119e45a
https://doi.org/10.1109/iv51971.2022.9827220
https://doi.org/10.1109/iv51971.2022.9827220
Autor:
Hannes Reichert, J. Marius Zollner, Konrad Doll, Kevin Rosch, Daniel Bogdoll, Lukas Lang, Bernhard Sick, Christoph Stiller, Hans-Christian Rellss
Publikováno v:
ISC2
Full-stack autonomous driving perception modules usually consist of data-driven models based on multiple sensor modalities. However, these models might be biased to the sensor setup used for data acquisition. This bias can seriously impair the percep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df649351d898d78458221ad3c8835196
http://arxiv.org/abs/2105.06896
http://arxiv.org/abs/2105.06896
Publikováno v:
2019 IEEE Intelligent Vehicles Symposium (IV).
In this article, we present an approach to forecast trajectories of vulnerable road users (VRUs) including a numerical quantification of the uncertainty of the forecast. The uncertainty estimates are modeled as normal distributions by means of neural
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd24077aec1c3978c7f8c2f16c594b75
https://doi.org/10.1109/ivs.2019.8814258
https://doi.org/10.1109/ivs.2019.8814258