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Titel:

Vehicle Rollover Detection Using Recurrent Neural Networks

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Dengler, C.; Treetipsounthorn, K.; Chantranuwathana, S.; Phanomchoeng, G.; Lohmann, B.; Panngum, S.
Seitenangaben Beitrag:
pp. 59-64
Kapitel Beitrag:
Article number 9095843
Abstract:
Rollover accidents have a higher fatality rate than other types of accidents. Therefore, rollover prevention systems are of great importance for driver safety. The implementation of rollover prevention systems requires an estimation of the rollover risk. To assess that risk, different rollover indices have been introduced. A difficulty is the dependence of these indices on unknown parameters, e.g., center of gravity and current load of the vehicle. One solution is to implement an algorith...     »
Stichworte:
Rollover Detection, Rollover Prevention, Neural Network, Recurrent Neural Network
Dewey-Dezimalklassifikation:
620 Ingenieurwissenschaften
Herausgeber:
Institute of Electrical and Electronics Engineers Inc.
Kongress- / Buchtitel:
IEEE International Conference on Cybernetics and Intelligent Systems (CIS)[9th, 2019] and IEEE Conference on Robotics, Automation and Mechatronics (RAM)
Datum der Konferenz:
18.-20.11.2019
Publikationsdatum:
19.05.2020
Jahr:
2020
Quartal:
2. Quartal
Jahr / Monat:
2020-05
Monat:
May
Nachgewiesen in:
Scopus
Print-ISBN:
978-1-7281-3459-8
E-ISBN:
978-1-7281-3458-1
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1109/CIS-RAM47153.2019.9095843
WWW:
https://ieeexplore.ieee.org/document/9095843
TUM Einrichtung:
Lehrstuhl für Regelungstechnik
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