AI-Driven Cloud-Native Microservices for Secure and Scalable Coordination of Autonomous Vehicle Fleets
DOI:
https://doi.org/10.15662/IJARCST.2023.0606005Keywords:
Autonomous Vehicle Fleets, Cloud-Native Microservices, AI-Powered Framework, Cybersecurity, Recommender Systems, Fleet Coordination, Predictive Maintenance, Scalable Architecture, Intelligent Transportation SystemsAbstract
Autonomous vehicle fleets are rapidly transforming transportation systems, demanding secure, scalable, and intelligent frameworks for coordination, data processing, and decision-making. This paper proposes a secure and scalable AI-powered cloud-native microservices framework designed for coordinated autonomous vehicle fleets, integrating advanced cybersecurity measures and AI-based recommender systems. The framework leverages cloud-native microservices to enable modularity, interoperability, and dynamic scaling, while AI models optimize fleet coordination, predictive maintenance, and route planning. Cybersecurity mechanisms, including anomaly detection and secure communication protocols, ensure data integrity and privacy across the fleet. The AI-based recommender system provides real-time decision support for routing, energy management, and service allocation, enhancing operational efficiency and safety. Experimental evaluations demonstrate improvements in task latency, resource utilization, security assurance, and overall fleet performance. This study highlights the potential of combining cloud-native architectures, AI, and cybersecurity to advance next-generation autonomous vehicle fleet management.
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