Public Road AV Assessment Techniques | 2026 Mcity Member Meeting

Carol Flannagan, Research Professor at UMTRI, and Efe Yarbasi, Assistant Research Scientist at UMTRI, discuss public road autonomous vehicle assessment techniques at the 2026 Mcity Member Meeting. Mcity is part of the U-M Transportation Research Institute within the U-M College of Engineering.
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About the speakers: Dr. Flannagan has over 30 years of experience conducting data analysis and research on injury risk related to motor vehicle crashes. Her recent work on crash-avoidance technologies includes the application of statistical methods to estimate the effectiveness and potential benefits of crash-avoidance technologies as well as the safety assessment of automated driving systems (ADS). Dr. Flannagan’s work often involves the fusion and analysis of large state- and national-level databases, including crash, EMS, and hospital data. These fused databases are useful in analyzing the effect of a wide variety of countermeasures on crash involvement and injury risk. Finally, Dr. Flannagan has worked to develop and apply a wide variety of new and old statistical approaches, such as natural language processing, Bayesian methods, and causal inference methods to address transportation data issues and answer transportation research questions.

Dr. Yarbasi’s expertise encompasses uncertainty quantification in complex systems, verification and validation (V&V) activities, robotics, energy systems modeling in smart building infrastructure, and systems engineering. Before joining UMTRI, he extensively collaborated with government and industry on various projects, spanning from development of a surgical endoscopy robot to energy optimization of a net-zero-energy building. At Georgia Tech, he worked with international experts on a NATO STO project to create a validation database for simulation environments in air and sea vehicle design. His dissertation furthered this work by developing a comprehensive methodology for identifying critical uncertainties in complex multidisciplinary design, and guiding experimentation to mitigate these uncertainties.

Dr. Yarbasi’s research interests focus on developing safe and reliable autonomous vehicles, leveraging smart city infrastructure to enhance transportation safety and efficiency, and integrating Advanced Air Mobility (AAM) systems with other transportation modes. His overarching goal is to contribute to the creation of a transportation ecosystem that is safe, efficient, and equitable, paving the way for a sustainable future in mobility.

He is a member of the American Institute of Aeronautics and Astronautics (AIAA).

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