A two-stage multi-fidelity Bayesian optimization method uses pre-computed simulation data to tune a vehicle's controller with only 17 real-world experiments.
Effects of Model Complexity on the Performance of Automated Vehicle Steering Controllers: Model Development, Validation and Comparison,
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Efficient Learning of Vehicle Controller Parameters via Multi-Fidelity Bayesian Optimization: From Simulation to Experiment
A two-stage multi-fidelity Bayesian optimization method uses pre-computed simulation data to tune a vehicle's controller with only 17 real-world experiments.