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Combining Belief Function Theory and Stochastic Model Predictive Control for Multi-Modal Uncertainty in Autonomous Driving
Therefore, the measure of reliability of the estimation provided by Belief Function Theory is used in the design of collision-avoidance safety constraints, in particular to increase safety when the intention of traffic participants is not clear.
Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing
In the exploration, a MPC collects diverse data by balancing the racing objectives and the exploration criterion; then the GP is re-trained.
Multistage Stochastic Model Predictive Control for Urban Automated Driving
For motion optimization, we propose to use a two-stage hierarchical structure that plans the trajectory and the maneuver separately.
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