Autonomous Shuttle

Autonomous shuttles are self-driving vehicles designed to provide on-demand transportation services, primarily focusing on improving first/last-mile connectivity and accessibility, particularly for vulnerable populations. Current research emphasizes optimizing route planning and traffic integration using models like dynamic traffic assignment and greedy insertion heuristics, alongside enhancing localization and perception capabilities through sensor fusion (e.g., GPS, IMU, LiDAR) and advanced algorithms such as graph neural networks. This research is significant for its potential to improve urban mobility, reduce reliance on private vehicles, and enhance public transportation efficiency, particularly in suburban and campus settings.