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AI-For-Mobility—A New Research Platform for AI-Based Control Methods

Ruggaber, Julian and Ahmic, Kenan and Brembeck, Jonathan and Baumgartner, Daniel and Tobolar, Jakub (2023) AI-For-Mobility—A New Research Platform for AI-Based Control Methods. Applied Sciences, 23. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/app13052879. ISSN 2076-3417.

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Official URL: https://www.mdpi.com/2076-3417/13/5/2879

Abstract

AI-For-Mobility (AFM) is the new research platform to investigate and implement novel control methods based on Artificial Intelligence (AI) within the Department of Vehicle System Dynamics at the German Aerospace Center (DLR). A production hybrid vehicle serves as a base platform. Since AI-based methods are data-driven, the vehicle is equipped with manifold sensors to provide the required data. They measure the vehicle’s state holistically and perceive the surrounding environment, while high performance on-board CPUs and GPUs handle the sensor data. A full by-wire control system enables the vehicle to be used for applications in the field of automated driving. Despite all modifications, it is approved for public road use and meets the driving dynamics properties of a standard road vehicle. This makes it an attractive research and test platform, both for automotive applications and technology demonstrations in other scientific fields (e.g., robotics, aviation, etc.). This paper presents the vehicle’s design and architecture in a detailed manner and shows a promising application potential of AFM in the context of AI-based control methods.

Item URL in elib:https://elib.dlr.de/194049/
Document Type:Article
Title:AI-For-Mobility—A New Research Platform for AI-Based Control Methods
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Ruggaber, JulianUNSPECIFIEDhttps://orcid.org/0000-0003-4300-9104UNSPECIFIED
Ahmic, KenanUNSPECIFIEDhttps://orcid.org/0000-0002-2266-1067UNSPECIFIED
Brembeck, JonathanUNSPECIFIEDhttps://orcid.org/0000-0002-7671-5251UNSPECIFIED
Baumgartner, DanielUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Tobolar, JakubUNSPECIFIEDhttps://orcid.org/0000-0002-4888-4664UNSPECIFIED
Date:23 February 2023
Journal or Publication Title:Applied Sciences
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:23
DOI:10.3390/app13052879
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2076-3417
Status:Published
Keywords:automated test vehicle; AI-based control methods; test vehicle design; vehicle dynamics; holistic vehicle instrumentation
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - V&V4NGC - Methoden, Prozesse und Werkzeugketten für die Validierung & Verifikation von NGC
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of System Dynamics and Control > Vehicle System Dynamics
Deposited By: Ruggaber, Julian
Deposited On:03 Apr 2023 11:08
Last Modified:24 Apr 2023 14:56

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