Congratulations to Honor Student Jordan Strand’s Graduation!

We are thrilled to congratulate honors student Jordan Strand on his recent graduation and the successful completion of his undergraduate thesis, “A Trust-Based Decision Framework for Autonomous Vehicle Control in Mixed-Autonomy Traffic.”

In his thesis, Jordan tackled the complex challenge of enabling autonomous systems to safely and effectively interact with human-driven vehicles (HDVs). To better understand real-world driving behavior, his research leveraged large-scale naturalistic driving datasets—specifically the Highway Drone Dataset (highD)—to model the intricate decision-making processes of human drivers. His work analyzed key driving dynamics, including speed regulation, car-following behavior, and lane-changing patterns across diverse traffic conditions.

A major highlight of Jordan’s research is the development of a novel trust estimation framework. Building on prior studies regarding pedestrian–vehicle interactions, Jordan extended the concept of behavioral trust to vehicle–vehicle interactions. His proposed model quantifies the reliability of nearby vehicles based on observable actions—such as headway maintenance, adherence to traffic norms, and collision risk indicators—to successfully identify patterns associated with safe versus risky driving.

Ultimately, Jordan’s work represents an exciting step forward in developing human-aware autonomous driving models that can navigate the complexity and variability of real-world human behavior.

Congratulations, Jordan, on this outstanding achievement! We are incredibly proud of your hard work and wish you the absolute best in your future endeavors.