Asmussen Receives funding for transportation project


University of Tennessee-Oak Ridge Innovation Institute - Katie Asmussen - Research Assistant Professor - Transportation CRI

Congratulations to Katherine Asmussen, research assistant professor with UT-ORII’s Transportation Convergent Research Initiative and UTK’s Center for Transportation Research, on receiving an award for her project – Consumer Acceptance of Automated Vehicles: Evidence from a Newly Deployed U.S. Survey and Stated-Preference Experiment.

With this award, her research project aims to provide evidence-based insights to help cities and agencies prepare for the integration of automated mobility services in ways that improve access, safety, and system performance.

This research focuses on understanding how robotaxi services will actually be used as they move from pilot programs to real-world deployment. With companies like Waymo now operating fully driverless services in several U.S. cities, automated ride-hailing is no longer hypothetical. However, we still know very little about how people will integrate these services into their daily travel routines, whether robotaxis will replace private vehicle trips, complement public transit, or generate new travel demand altogether.

To address this gap, Asmussen, alongside Hongyu Zheng from UTK’s Department of Industrial & Systems Engineering – University of Tennessee, Knoxville are deploying a custom-designed survey that collects detailed information on individuals’ current travel behavior, attitudes toward automation, safety perceptions, trust, and willingness to use robotaxi services for different types of trips. The survey also includes scenario-based choice experiments in which respondents choose between driving, public transit, and robotaxi options under varying conditions such as cost, wait time, reliability, and service characteristics.

The analysis will use advanced behavioral modeling techniques to estimate who is most likely to adopt robotaxis, for which trips, and under what conditions. The goal is to move beyond general opinions about autonomous vehicles and instead generate realistic behavioral forecasts that can inform transportation planning, congestion management, equity considerations, and infrastructure investment decisions.


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