Q-Edge: Leveraging Quantum Computing for Enhanced Software Engineering in Vehicular Networks
Adriano Maia, Marcus Freire, Thiago Luigi Mello, Roberto Rodrigues Filho, Eduardo Santana de Almeida, Cassio Vinicius Serafim Prazeres, Gustavo B. Figueiredo, Maycon Leone Maciel Peixoto · 2025
Connected autonomous vehicles (CAVs) require extensive data processing to make real-time decisions such as obstacle detection, collision avoidance, and route optimization. To enable fast and accurate decision-making in CAVs, services traditionally executed in cloud data centers are being moved to the edge to minimize data transfer from vehicles to the cloud. We present a framework called Q-Edge that utilizes quantum computing at the network edge to improve the speed and effectiveness of data analysis for CAVs. By integrating quantum computing principles such as superposition, entanglement, and teleportation with edge computing, we propose a solution to address the latency and bandwidth issues inherent in traditional cloud computing methods. This approach, leveraging quantum software engineering practices, enables realtime decision-making, optimizing CAV performance and enhancing traffic management, urban mobility, and road safety.