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Micro AI-For-Mobility - Research Platform for AI-Based Control Methods

Diegel, Daniel and Pölzleitner, Daniel and Baumgartner, Daniel and Brembeck, Jonathan (2024) Micro AI-For-Mobility - Research Platform for AI-Based Control Methods. In: 100th IEEE Vehicular Technology Conference, VTC 2024-Fall. IEEE. VTC 2024 Fall, 2024-10-07 - 2024-10-10, Washington, D.C.. doi: 10.1109/VTC2024-Fall63153.2024.10757935. ISBN 979-833151778-6. ISSN 1550-2252.

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Official URL: https://ieeexplore.ieee.org/abstract/document/10757935

Abstract

The AI for Micro Mobility (µAFM) is the new research platform for investigation of novel active and passive electronic bicycle assistance control methods within the Department of Vehicle System Dynamics at the German Aerospace Center (DLR). Autonomous driving and artificial intelligence offer completely new possibilities for control systems. However, no studies have yet investigated the holistic approach, from the perception sensors to the control algorithms, with the aim of protecting vulnerable road users, particularly in the context of bicycles. The objective of our research is to contribute to this field of study. To this end, we equipped a production electric serial hybrid power train bicycle with a set of state-of-the-art sensors and computational hardware. The hardware and software integration of the various sensors as well as the network architecture is presented. Paving the path for further research in this field. Concluding, two real-word experiments are conducted to validate and investigate the performance of the setup for further control algorithms studies.

Item URL in elib:https://elib.dlr.de/207725/
Document Type:Conference or Workshop Item (Speech)
Title:Micro AI-For-Mobility - Research Platform for AI-Based Control Methods
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Diegel, DanielUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Pölzleitner, DanielUNSPECIFIEDhttps://orcid.org/0009-0004-1873-3162178236799
Baumgartner, DanielUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Brembeck, JonathanUNSPECIFIEDhttps://orcid.org/0000-0002-7671-5251UNSPECIFIED
Date:28 November 2024
Journal or Publication Title:100th IEEE Vehicular Technology Conference, VTC 2024-Fall
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI:10.1109/VTC2024-Fall63153.2024.10757935
Publisher:IEEE
Series Name:Conference on Vehicular Technology (VTC)
ISSN:1550-2252
ISBN:979-833151778-6
Status:Published
Keywords:ai-based control methods, e-bike research platform, bicycle assistant systems, robotic bicycle, electro-mobility, micro mobility platform
Event Title:VTC 2024 Fall
Event Location:Washington, D.C.
Event Type:international Conference
Event Start Date:7 October 2024
Event End Date:10 October 2024
Organizer:IEEE
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
Institute of System Dynamics and Control > Vehicle System Dynamics
Deposited By: Diegel, Daniel
Deposited On:13 Jan 2025 09:44
Last Modified:19 Feb 2025 09:04

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