Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Marc Holzapfel"'
Publikováno v:
2020 IEEE Intelligent Vehicles Symposium (IV).
Automated driving is one of the main drivers in the automotive industry. On the way to full automation current Advanced Driver Assistant Systems (ADAS) and Automated Driving Systems (ADS) backed by new and enhanced sensor systems take over more and m
Autor:
Marc Holzapfel, Marc Albrecht
Publikováno v:
ATZextra. 23:34-37
Publikováno v:
VEHITS
Publikováno v:
Proceedings ISBN: 9783658309947
In the context of the release of automated driving functions on SAE level 3 and higher, research is currently focusing on the safety proof. However, even on level 1 and 2, the driver can potentially hand over the driving tasks to the vehicle in many
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e32596c8c98e3c80a9263b0c403bc6f7
https://doi.org/10.1007/978-3-658-30995-4_22
https://doi.org/10.1007/978-3-658-30995-4_22
Publikováno v:
VEHITS
Publikováno v:
VEHITS
For the development of Advanced Driver Assistant Systems (ADAS) and Automated Driving Systems (ADS) a change from test case-based testing towards scenario-based testing can be observed. Based on current approaches to define scenarios and their inhere
Publikováno v:
Intelligent Vehicles Symposium
Advanced Driver Assistant Systems (ADAS) use a multitude of input signals for tasks like trajectory planning and control of vehicle dynamics provided by a large variety of information sources such as sensors and digital maps. To assure the feature’
Publikováno v:
2017 IEEE International Systems Engineering Symposium (ISSE).
Established methods and processes in the field of Automotive Systems Engineering (ASE) are challenged by the rising complexity of current features. Expanding system boundaries, tighter interconnections of functional elements, increasingly complex a
Publikováno v:
SAE Technical Paper Series.
Publikováno v:
Intelligent Vehicles Symposium
In this paper we present an online learning approach to predict driver behavior and resulting vehicle states. The driver is represented by driver states x→ and a control function ƒ c . Kernel Density Estimation is used for online estimation of cur