Pedestrian Environment

Research on pedestrian environments focuses on improving safety, accessibility, and overall experience for pedestrians, particularly in increasingly dense urban areas. Current efforts utilize computer vision and machine learning, including deep learning models like GANs and LSTMs, to analyze sidewalk infrastructure from satellite imagery, predict pedestrian movement for collision avoidance systems (e.g., for e-scooters), and enable more efficient and socially aware robot navigation in crowded spaces. These advancements offer the potential for improved urban planning, enhanced accessibility for vulnerable populations, and safer integration of autonomous systems into pedestrian environments.