William Angell
Papers
2
Total Citations
304
H-Index
2
About
William Angell is a leading researcher in autonomous vehicle technology and human-machine interaction, with a focus on understanding driver behavior in real-world automated driving contexts. As a key contributor to the MIT Advanced Vehicle Technology Study (AVT), Angell has spearheaded large-scale naturalistic driving studies that capture how human drivers interact with automation systems over extended periods. His 2019 paper, with 227 citations, provides critical insights into the limitations of current autonomous systems, arguing that the full driving task remains too complex for purely model- or learning-based approaches. His earlier 2017 work, cited 77 times, further establishes his role in applying deep learning to analyze driver behavior and automation interaction. Angell’s research has profoundly influenced the design of safer, more human-centered autonomous vehicles, emphasizing the need for robust localization and sensing-acting systems. His contributions are essential for students and researchers seeking to bridge the gap between human cognition and machine autonomy, making him a pivotal figure in the evolution of transportation safety and intelligent vehicle systems.
Research Focus
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Top Papers
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