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Strategic Analysis of an Accelerated Introduction of Cooperative, Connected and Automated Mobility (CCAM)

  • For over 80 years the idea of self-driving cars has influenced our perception of the future transport mode. While in 1939 people were excited, they did not believe it would ever become reality. In 2021 we are now closer than ever to bringing these cars on the road. But the vast number of stakeholders and the various aspects that must be considered for the execution of self-driving cars makes it even more complex than at first glance. The creation of a proper artificial intelligence infrastructure, the integration of AI within the automotive industry and lastly, getting society to accept self-driving cars, are the focus of this dissertation. Through a literature review, a qualitative and a quantitative study these key aspects have been considered. At the centre is the over one century old German, and European, automotive industry. The European automotive manufacturers and suppliers need to act together, take risks, educate future self-driving car users and overall see the European automotive industries as allies. Europeans would benefit from pooling financial capabilities and data gathering to execute technological improvements faster and better. To bring autonomous vehicles on the road, and to create a transport mode capable of competing with Chinese, American and other competitors’ products, and to simply not be outsmarted by them, Europeans have to work together and become strategically bold. As the COVID-19 pandemic hit in 2020, integrating AI within our automotive industry may not be on companies’ minds, but we need it now more than ever. Through AI, processes, such as information gathering and handling, can be improved and machinery supporting workers can be introduced. In addition, the fundamental assumptions on which our future mobility world is based have changed and, as a result, strategies must be reassessed. While the introduction reflects on pre-COVID-19 times, the papers included in this dissertation highlight the changes and the opportunities the virus brought upon the industry and tries to encourage it to expand AI integration and self-driving vehicle execution. The pandemic may have resulted in lower financial capabilities for the research and creation of self-driving cars, but it has also allowed for an increased acceptance rate of this future transport mode. Overall, it is time for the automotive industry to reconsider its self-driving vehicle deployment approach drastically in order to reinvent itself and usher in a new era where AI within automobiles is not feared but preferred.

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Author:Christina Frances Edye
Referee:Wolfgang H. Schulz, Silja Hoffmann, Lutz Göcke
Document Type:Doctoral Thesis
Year of Publication:2023
Date of first Publication:2023/02/10
Publishing Institution:Zeppelin Universität
Granting Institution:Zeppelin Universität
Date of final exam:2022/03/01
Release Date:2023/02/10
Tag:autonomous driving, artificial intelligence, automotive industry, mobility, COVID-19, supplier risks, process optimisation
Page Number:X, 117, x Seiten
Licence (German):License LogoUrheberrechtlich geschützt