Cheng, Shiqing (2023) Exploring Knowledge Transfer Opportunities between the Railway and Automotive Industries: A Systematic Literature Review. Masterarbeit, Hochschule Harz.
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Kurzfassung
As two significant transportation sectors, the railway and automotive industries face similar challenges, including increased traffic demands, surging energy costs, and the pressing need to address sustainability and environmental concerns. It is urgent for these industries to seek proactive knowledge transfer opportunities to boost their competitiveness and effectively tackle these multifaceted challenges. However, there is a lack of articles that directly investigate knowledge transfer opportunities between these two sectors. This study employs a Systematic Literature Review (SLR) in four comprehensive databases (IEEExplore, Scopus, ScienceDirect, Web of Science) and delves into online resources provided by relevant stakeholders to explore knowledge transfer opportunities between the two sectors with a focus on infrastructure maintenance and data-sharing. Through the SLR, this research summarizes the current state of digitalization within the railway and automotive industries, presents practices related to data-sharing and infrastructure maintenance in both sectors, and points out potential opportunities for knowledge transfer, including preparing the infrastructure for smart mobility, implementing predictive maintenance for autonomous driving infrastructure, popularizing V2X communication in the railway industry, and empowering the data-sharing with Blockchain in the railway industry, which serve as a springboard for further exploration of smart and sustainable mobility solutions.
elib-URL des Eintrags: | https://elib.dlr.de/200797/ | ||||||||
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Dokumentart: | Hochschulschrift (Masterarbeit) | ||||||||
Titel: | Exploring Knowledge Transfer Opportunities between the Railway and Automotive Industries: A Systematic Literature Review | ||||||||
Autoren: |
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Datum: | 2023 | ||||||||
Referierte Publikation: | Nein | ||||||||
Open Access: | Nein | ||||||||
Gold Open Access: | Nein | ||||||||
In SCOPUS: | Nein | ||||||||
In ISI Web of Science: | Nein | ||||||||
Seitenanzahl: | 98 | ||||||||
Status: | veröffentlicht | ||||||||
Stichwörter: | Railway Automotive Digitalization Automation Innovation Transfer | ||||||||
Institution: | Hochschule Harz | ||||||||
Abteilung: | Fachbereich Automatisierung und Informatik | ||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||
HGF - Programm: | Verkehr | ||||||||
HGF - Programmthema: | Schienenverkehr | ||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||
DLR - Forschungsgebiet: | V SC Schienenverkehr | ||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - TraCo - Train Control and Management, V - KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz | ||||||||
Standort: | Braunschweig | ||||||||
Institute & Einrichtungen: | Institut für Verkehrssystemtechnik Institut für Verkehrssystemtechnik > Informationsgewinnung und Modellierung, BS | ||||||||
Hinterlegt von: | Groos, Jörn Christoffer | ||||||||
Hinterlegt am: | 11 Dez 2023 12:52 | ||||||||
Letzte Änderung: | 11 Dez 2023 12:52 |
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