Safety

Exploring Top-Down Visual Attention for Transportation Behavior Analysis

This project stands at the intersection of cognitive psychology, AI and computer vision, and transportation safety and efficiency. By focusing on the nuanced ways in which humans allocate their visual attention, and how this can inform the development of artificial intelligence (AI) and machine learning (ML) to aid in self-driving cars, transportation safety automation, and […]

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Investigation of Emerging Sensing and AI/ML Technologies to Enhance the Safety of Vulnerable Roadway Users at Signalized Intersection

Accurately identifying and analyzing vulnerable roadway users (VRUs) such as pedestrians, bicyclists, and other non-vehicle occupants, are a crucial yet difficult undertaking. VRUs’ behavior is influenced by localized factors such as land use, and their movements are not confined to predefined paths. This study will investigate the use of emerging technologies such as LiDAR, network

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