Search Results for author:
Found 5 papers, 0 papers with code
Model Predictive Control with Infeasible Reference Trajectories
Model Predictive Control (MPC) formulations are typically built on the requirement that a feasible reference trajectory is available.
ParkPredict: Motion and Intent Prediction of Vehicles in Parking Lots
We investigate the problem of predicting driver behavior in parking lots, an environment which is less structured than typical road networks and features complex, interactive maneuvers in a compact space.
Safe Trajectory Tracking in Uncertain Environments
In Model Predictive Control (MPC) formulations of trajectory tracking problems, infeasible reference trajectories and a-priori unknown constraints can lead to cumbersome designs, aggressive tracking, and loss of recursive feasibility.
Learning When to Drive in Intersections by Combining Reinforcement Learning and Model Predictive Control
In this paper, we propose a decision making algorithm intended for automated vehicles that negotiate with other possibly non-automated vehicles in intersections.
A Computationally Efficient Model for Pedestrian Motion Prediction
We present a mathematical model to predict pedestrian motion over a finite horizon, intended for use in collision avoidance algorithms for autonomous driving.
Systems and Control
