Internet of Things & Blockchain Application in Highly Automated Driving
The increasing interconnectedness of road users and the sharp rise in data exchange between various technical systems have raised questions of security. Therefore, cybersecurity is crucial and appropriate measures must be taken to ensure it. In the present research, such measures were vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. A further challenge is that in the future, renewal cycles for hardware (e.g., sensors and computer hardware) and especially software will be substantially shorter than the current service life of vehicles. This study combined distributed ledger technology with the Internet of Things (IoT) to develop, apply, and critically assess a possible solution for maintaining security in real-time applications of vehicle-to-everything communication. The basis for the developed framework was elaborated blockchain approaches found in the literature, which had not yet been applied in a Swiss or European project. With the help of experts from existing Swiss automated driving projects or those from fields related to automated driving, Mobility 4.0, distributed ledger technology, and the IoT, the applicability of the adapted AUTOPILOT framework was evaluated. While some researchers hope for a real-time application of the blockchain, this could not be proven in the analysis of the results. One reason is the divergent understanding of real time, as the delay in sending and receiving messages remains the largest bottleneck of blockchain technology. However, this study also demonstrated that it is precisely in non-time-critical applications that blockchain experts have the greatest interest and that they are where the largest opportunities lie. Therefore, the researcher aims to focus on non-time-critical applications next. Although this research primarily focused on Swiss mobility service providers and Swiss authorities, it may also be of interest to automotive OEMs and mobility providers outside of Switzerland.
Raemy, Nicola, 2021
Art der Arbeit Master Thesis
Betreuende Dozierende Kondova, Galia
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Studiengang: Business Information Systems (Master)