CAREER: Data-driven Multiscale Modeling of Complex Traffic Systems Utilizing Networked Driving Simulators

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This Faculty Early Career Development (CAREER) award supports research that will investigate human driving behavior and interactions among traffic participants, with the aim of empowering technological advances in autonomous and connected vehicles. Understanding human driving behavior is vital for engineering connected and autonomous vehicles that safely share roads with humans. This award supports fundamental research about human driving behavior, including their physiological and cognitive engagement with other drivers and the environment. To ensure a safe and cost-effective approach, the project will utilize an immersive virtual reality driving simulator. Controlled and repeatable experiments will be conducted in this environment by systematically exposing drivers to a variety of traffic scenarios. The project will integrate educational activities that introduce students, including students from underrepresented groups, to STEM topics, as well as outreach activities to raise awareness of the general public to traffic safety, secondary crashes, and impaired driving. This CAREER project will study multiscale traffic interactions, at the vehicle, driver, and cognitive levels. Using brain scans for multiple interacting participants, this project will investigate whether brain coupling characteristics emerge among drivers at the group level, and how cognitive level engagement relates to other driving behaviors. The research findings have potentially transformative implications for cognitive and behavioral neuroscience and technological advancement in driver assistance systems. The project will generate rich multiscale datasets, identify experimentally-informed modeling parameters, and discover experimentally-validated traffic models.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.