Review on Autonomous and Sustainable Urban Mobility Systems: Challenges and Future Directions

Abstract

This review examines strategies that enable safety and energy efficiency in collaborative intelligent agent ecosystems, including mobile robots, assistive systems, and autonomous vehicles. Safety is framed as a hierarchical architecture: city-wide route planning through multi-agent information and decision sharing, regional collision-free motion coordination, and precise local path execution. Energy efficiency is analyzed in parallel, spanning artificial intelligence (AI)-driven eco-routing and task allocation, eco-driving and eco-locomotion for adaptive and cooperative motion control, and eco-power through actuator design, kinematic optimization, and bio-inspired mechanisms. These layers are deeply interconnected, showing that safety assurance and energy sustainability must be co-optimized rather than treated independently. Reinforcement learning, distributed intelligence, and cross-modal human-robot interaction emerge as pivotal enablers for robust, real-time adaptation in uncertain environments. Looking ahead, future intelligent ecosystems will depend on hyper-integrated co-optimization across planning, control, and hardware, guided by explainable and ethically aligned AI, paving the way toward safe, efficient, and trustworthy autonomous systems.