  In this letter, we present an approach for learning human driving behavior,
without relying on specific model structures or prior distributions, in a
mixed-traffic environment where connected and automated vehicles (CAVs) coexist
with human-driven vehicles (HDVs). We employ conformal prediction to obtain
theoretical safety guarantees and use real-world traffic data to validate our
approach. Then, we design a controller that ensures effective merging of CAVs
with HDVs with safety guarantees. We provide numerical simulations to
illustrate the efficacy of the control approach.
