Sensor Fusion as an Enabling Technology for Safety-critical Driver Assistance Systems

Author(s):  
Richard Altendorfer ◽  
Sebastian Wirkert ◽  
Sascha Heinrichs-Bartscher
2019 ◽  
Vol 109 (04) ◽  
pp. 211-215
Author(s):  
R. Müller ◽  
L. Schirmer ◽  
M. Scholer

Mit der Übernahme sicherheitskritischer Funktionen durch technische Systeme, wie zum Beispiel Fahrerassistenzsysteme, werden Methoden zur Funktionsabsicherung immer wichtiger. Eine diese Methoden ist der Key Characteristics Flowdown, der eine Visualisierung und Analyse der Schlüsselmerkmale sowie deren Zusammenhänge ermöglicht. Um die Nutzung der Methode systematischer zu gestalten sowie den Zeitaufwand zu reduzieren, wird in dem Beitrag eine Modularisierung der Merkmale für Betriebsmittel in der Montage vorgestellt.   With the execution of safety-critical functions by technical systems, e.g. driver assistance systems, methods for safeguarding are becoming increasingly important. One of these methods is the Key Characteristics Flowdown, which enables a visualization and analysis of key characteristics and their interrelations. In order to enable a more systematic use of the method and to reduce the required time, the article presents a modularization of the features for assembly equipment.


2017 ◽  
Author(s):  
Mario Amoruso ◽  
Stefano Caiola ◽  
Giuseppe Doronzo ◽  
Marino Difino

As vehicles move toward autonomous capability, there is a rising need for hardware-in-the loop (HIL) testing to validate and verify the functionality of advanced driver assistance systems (ADAS), which are anticipated to play a central role in autonomous driving. This white paper gives an overview of the ADAS HIL with sensor fusion concept, shares main takeaways from initial research efforts, and highlights key system-level elements used to implement the application.


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