Quantum Artificial Intelligence for Secure Autonomous Vehicle Navigation: An Architectural Proposal

TL;DR

This paper proposes a quantum AI-based architecture for autonomous vehicle navigation that enhances sensor fusion, optimizes navigation policies with quantum reinforcement learning, and secures communications against quantum threats.

Contribution

It introduces a novel quantum AI framework integrating quantum neural networks, quantum reinforcement learning, and post-quantum cryptography for autonomous vehicle navigation.

Findings

Quantum neural networks enable multimodal sensor fusion.

Quantum reinforcement learning optimizes navigation policies.

Post-quantum cryptography secures vehicle communications.

Abstract

Navigation is a very crucial aspect of autonomous vehicle ecosystem which heavily relies on collecting and processing large amounts of data in various states and taking a confident and safe decision to define the next vehicle maneuver. In this paper, we propose a novel architecture based on Quantum Artificial Intelligence by enabling quantum and AI at various levels of navigation decision making and communication process in Autonomous vehicles : Quantum Neural Networks for multimodal sensor fusion, Nav-Q for Quantum reinforcement learning for navigation policy optimization and finally post-quantum cryptographic protocols for secure communication. Quantum neural networks uses quantum amplitude encoding to fuse data from various sensors like LiDAR, radar, camera, GPS and weather etc., This approach gives a unified quantum state representation between heterogeneous sensor modalities. Nav-Q module processes the fused quantum states through variational quantum circuits to learn optimal navigation policies under swift dynamic and complex conditions. Finally, post quantum cryptographic protocols are used to secure communication channels for both within vehicle communication and V2X (Vehicle to Everything) communications and thus secures the autonomous vehicle communication from both classical and quantum security threats. Thus, the proposed framework addresses fundamental challenges in autonomous vehicles navigation by providing quantum performance and future proof security. Index Terms Quantum Computing, Autonomous Vehicles, Sensor Fusion