Symbolic Perception Risk in Autonomous Driving
Autonomous Car
Cautious Planning with Incremental Symbolic Perception: Designing Verified Reactive Driving Maneuvers
Time-Incremental Learning of Temporal Logic Classifiers Using Decision Trees
Classification of Time-Series Data Using Boosted Decision Trees
When to Terminate: Path-non Existence Verification Improves Sampling-based Motion Planning
Learning A Risk-Aware Trajectory Planner From Demonstrations Using Logic Monitor
Differentiable Logic Layer for Rule Guided Trajectory Prediction
A Control Architecture for Provably-Correct Autonomous Driving
Learning An Explainable Trajectory Generator Using The Automaton Generative Network (AGN)
Vehicle Trajectory Prediction Using Generative Adversarial Network With Temporal Logic Syntax Tree Features
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