Emulation of Autonomous Driving Functionsof an L7e Vehicle using Real Sensor Data and a Real-time Target Machine

Konferenz: AmE 2023 – Automotive meets Electronics - 14. GMM Symposium
15.06.2023-16.06.2023 in Dortmund, Germany

Tagungsband: GMM-Fb. 106: AmE 2023

Seiten: 3Sprache: EnglischTyp: PDF

Autoren:
Kamau, Edwin N. (University of Applied Sciences Cologne, Köln, Germany)
Becciu, Alessandro (Nuraxys GmbH, Overath, Germany)
Stockem Novo, Anne (Ruhr West University of Applied Sciences, Mülheim an der Ruhr, Germany)

Inhalt:
Advance of Autonomous driving functions pose new challenges for their application on different variety of vehicles, the increasing complexity of the vehicle architecture, higher expectation of safety, lower environmental impact and higher comfort. In order to perform a system test, alternative solutions to vehicle test are investigated with the goal to improve the cost efficiency and lower the environmental impact. In this work the development of a hardware in the loop (HiL) solution for emulating longitudinal and lateral control algorithms using real data acquired with cameras installed in a L7e vehicle is investigated. Such a vehicle is expected to play a major role in the future of the automotive industry for its comparatively low carbon emissions, however it presents challenges for sensor application as compared to passenger cars, due to the low availability of publicly available data that can be used to test and develop automated driving functions. First results presented in this work show the feasibility of emulating longitudinal vehicle dynamics using vision sensor data collected with a lightweight L7e vehicle.