Uncertainty modeling and runtime verification for autonomous vehicles driving control: A machine learning-based approach.

•A unified framework is proposed for uncertainty modeling and runtime verification of autonomous vehicles driving control.•A formal modeling language is presented to model the stochastic behaviors in the uncertain environment.•Runtime verification is provided based on parameter update from machine learning classifier.