Autonomous Vehicles(AVs);deep learning;pedestrian detection;pedestrian anomaly behaviors;synthetic dataset;Metaverse

The dataset is generated specifically to simulate the essential components for driving environments in a virtual campus of Chulalongkorn University, including street blocks, various pavements, lane markings, traffic signs, lamp poles, and pedestrians, among other features. We selected this campus for our simulation due to its distinctive road and pavement environments, which are unique to Thailand and other Asian countries. This choice contrasts with many widely cited datasets that predominantly feature environments from European or other regions.