A distilled physics-informed neural surrogate in a hierarchical optimal control architecture raises simulated PIT success from 63.8% to 76.7% and succeeds in three of four low-speed scaled-vehicle tests.
Physics-informed neural network modeling of vehicle collision dynamics in precision immobilization technique maneuvers
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Physics-Informed Neural Optimal Control for Precision Immobilization Technique in Emergency Scenarios
A distilled physics-informed neural surrogate in a hierarchical optimal control architecture raises simulated PIT success from 63.8% to 76.7% and succeeds in three of four low-speed scaled-vehicle tests.