- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
In: Journal of Low Power Electronics and Applications 8.4 (2018).
- Klassifikation
-
Ingenieurwissenschaften und Maschinenbau
- Ereignis
-
Veröffentlichung
- (wo)
-
Erlangen
- (wer)
-
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
- (wann)
-
2018
- Urheber
- URN
-
urn:nbn:de:bvb:29-opus4-114849
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:52 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Fickenscher, Jörg
- Schmidt, Sandra
- Hannig, Frank
- Bouzouraa, Mohamed Essayed
- Teich, Jürgen
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Entstanden
- 2018
Ähnliche Objekte (12)
Trust in highly automated driving
HAVEit: DLR makes highly automated driving sustainable
Macroscopic Safety Requirements for Highly Automated Driving
Context Aware Data Reduction for Highly Automated Driving
Highly precise MEMS gyroscopes for fully automated driving
Optimization based Analysis of Highly Automated Driving Simulation
Supporting take-over situations in highly automated driving
Redundant Steering System for Highly Automated Driving of Trucks
Variant Management for Technical Architecture of Highly-Automated Driving Systems
Dynamic Maps for Highly Automated Driving - Generation, Distribution and Provision
Interactive Maneuver Prediction and Planning for Highly Automated Driving Functions
Validating Machine Learning-based Highly Automated Driving Functions by Diversity
Trust in highly automated driving
HAVEit: DLR makes highly automated driving sustainable
Macroscopic Safety Requirements for Highly Automated Driving
Context Aware Data Reduction for Highly Automated Driving
Highly precise MEMS gyroscopes for fully automated driving
Optimization based Analysis of Highly Automated Driving Simulation
Supporting take-over situations in highly automated driving
Redundant Steering System for Highly Automated Driving of Trucks
Variant Management for Technical Architecture of Highly-Automated Driving Systems
Dynamic Maps for Highly Automated Driving - Generation, Distribution and Provision
Interactive Maneuver Prediction and Planning for Highly Automated Driving Functions
Validating Machine Learning-based Highly Automated Driving Functions by Diversity
Trust in highly automated driving
HAVEit: DLR makes highly automated driving sustainable
Macroscopic Safety Requirements for Highly Automated Driving
Context Aware Data Reduction for Highly Automated Driving
Highly precise MEMS gyroscopes for fully automated driving
Optimization based Analysis of Highly Automated Driving Simulation
Supporting take-over situations in highly automated driving
Redundant Steering System for Highly Automated Driving of Trucks
Variant Management for Technical Architecture of Highly-Automated Driving Systems
Dynamic Maps for Highly Automated Driving - Generation, Distribution and Provision
Interactive Maneuver Prediction and Planning for Highly Automated Driving Functions