Real-Time Path Planning Design for Autonomous Driving Vehicles

Dear Colleagues,

Real-time path planning is key to making intelligent vehicles safe, efficient, and autonomous. Advancement in autonomous driving technology can enable vehicles to quickly sense their surroundings, anticipate changes, and make safe, reliable navigation choices in busy, unpredictable traffic. Reliable path planning helps vehicles drive smoothly without collisions, save energy, shorten travel time, and improve passenger comfort. It also allows vehicles to work together, perform coordinated movements, and coexist well with humans in smart transportation systems. This Special Issue aims to share the latest research and practical progress in real-time path planning for autonomous vehicles, focusing on both theory and engineering. It emphasizes advances in algorithms, computing speed, environmental sensing, and adaptable control that help autonomous systems work well in changing conditions. Hence, for this Issue, we welcome contributions that bridge the gap between simulation and real-world deployment, explore methods combining optimization techniques and control strategies, and demonstrate scalable solutions applicable to diverse traffic and environmental scenarios.

Topics of interest include, but are not limited to, the following:

• Real-time trajectory and motion planning algorithms for autonomous vehicles;
• AI and machine learning methods for decision-making and control;
• Multi-sensor fusion and environmental perception for navigation;
• Cooperative and distributed path planning for connected vehicles;
• Safety assurance and human–machine interaction in path planning.

Dr. Feng Huang
Dr. Xiwei Bai
Dr. Penghui Xu
Guest Editors

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