Carlo Savorgnan
Papers
1
Total Citations
2
H-Index
1
About
Carlo Savorgnan is a researcher specializing in the intersection of autonomous vehicle technology, human factors, and driving simulation. His work focuses on the critical evaluation of assisted and autonomous driving systems compared to human driving, using advanced driving simulators to capture both objective performance metrics and subjective user experiences. His most-cited study, "Assisted / autonomous vs. human driving assessment on the DiM driving simulator using objective / subjective characterization" (2019), provides a foundational framework for assessing how drivers perceive and interact with automated features—a key challenge in the development of safe, user-centered autonomous vehicles. By combining quantitative data from simulator sensors with qualitative feedback from participants, Savorgnan’s research bridges the gap between engineering performance and human trust, offering insights that inform the design of more intuitive and reliable driving assistance systems. His work contributes to the growing body of literature on human-automation interaction, with implications for both automotive industry standards and regulatory guidelines.
Research Focus
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Top Papers
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