Abstract
Efficient Vehicle-to-Everything enabling cooperation and enhanced decision-making for autonomous vehicles is essential for optimized and safe traffic. Real-time decision-making based on vehicle sensor data, other traffic data, and environmental and contextual data becomes imperative. As a part of such Intelligent Traffic Systems, cooperation between different stakeholders needs to be facilitated rapidly, reliably, and securely. The Internet of Things provides the fabric to connect these stakeholders who share their data, refined information, and provided services with each other. However, these cloud-based systems struggle to meet the real-time requirements for smart traffic due to long distances across networks. Here, edge computing systems bring the data and services into the close proximity of fast-moving vehicles, reducing information delivery latencies and improving privacy as sensitive data is processed locally. To solve the issues of trust and latency in data sharing between these stakeholders, we propose a decentralized framework that enables smart contracts between traffic data producers and consumers based on blockchain. Autonomous vehicles connect to a local edge server, share their data, or use services based on agreements, for which the cooperating edge servers across the system provide a platform. We set up proof-of-concept experiments with Hyperledger Fabric and virtual cars to analyze the system throughput with secure unicast and multicast data transmissions. Our results show that multicast transmissions in such a scenario boost the throughput up to 2.5 times where the data packets of different sizes can be transmitted in less than one second.
H. Nguyen and T. Nguyen—These authors contribute equally.
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Notes
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The terms “participant”, “station”, “node”, and “peer” interchangeably use with the same meaning, while the term “network” and “system” are also interchangeable.
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Acknowledgment
This research is done in a strategic research project TrustedMaaS under focus institute Infotech Oulu, University of Oulu, and ECSEL JU FRACTAL (grant 877056). A personal grant by the Nokia foundation for Mr. Tri Nguyen. The researchers operate under Academy of Finland, 6G Flagship (grant 318927).
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Nguyen, H., Nguyen, T., Leppänen, T., Partala, J., Pirttikangas, S. (2022). Situation Awareness for Autonomous Vehicles Using Blockchain-Based Service Cooperation. In: Franch, X., Poels, G., Gailly, F., Snoeck, M. (eds) Advanced Information Systems Engineering. CAiSE 2022. Lecture Notes in Computer Science, vol 13295. Springer, Cham. https://doi.org/10.1007/978-3-031-07472-1_29
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