Techniques for improving the performance of an autonomous vehicle (AV) are described herein. A system can determine a plan for the AV in a driving scenario that optimizes an initial cost function of a control algorithm of the AV. The system can obtain data describing an observed human driving path in the driving scenario. Additionally, the system can determine for each cost dimension in the plurality of cost dimensions, a quantity that compares the estimated cost to the observed cost of the observed human driving path. Moreover, the system can determine a function of a sum of the quantities determined for each cost dimension in the plurality of cost dimensions. Subsequently, the system can use an optimization algorithm to adjust one or more weights of the plurality of weights applied to the plurality of cost dimensions to optimize the function of the sum of the quantities.
Systems and Methods for Pareto Domination-Based Learning
2023-07-20
Patent
Elektronische Ressource
Englisch
L-Dominance: An Approximate-Domination Mechanism for Adaptive Resolution of Pareto Frontiers
British Library Conference Proceedings | 2014
|Trade Space Exploration Enabled by a Non-Domination Level Coordinate System on the Pareto Frontier
British Library Conference Proceedings | 2013
|