Challenges and Future Prospects of Integrating Quantum Computing Into Intelligent Transportation Systems

Abstract

Quantum computing holds transformative potential for Intelligent Transportation Systems (ITS), offering solutions to complex and computationally intensive challenges in modern transportation networks. By leveraging quantum mechanics principles like superposition and entanglement, quantum algorithms can optimize traffic management, route planning, and logistics with unprecedented speed and accuracy. This can significantly enhance real-time traffic flow predictions, dynamic route optimization, and efficient resource allocation, particularly for electric vehicle networks, promoting sustainable and energy-efficient transportation solutions. However, integrating quantum computing into ITS faces challenges. Current quantum hardware is limited by issues like qubit instability, short coherence times, and high error rates, impeding large-scale applications. Additionally, developing hybrid systems that combine classical and quantum computing capabilities, and ensuring robust data privacy and security, are significant hurdles.