Safe Merging in Mixed Traffic with Confidence
CoRR(2024)
摘要
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.
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