Search papers, labs, and topics across Lattice.
This paper introduces a unified framework for Decision-Making (DM) and Trajectory Planning (TP) in automated vehicles navigating unsignalized intersections, utilizing a Finite Horizon Optimal Control Problem (FHOCP) combined with Time-Varying Artificial Potential Fields (TV-APF). The method incorporates short-horizon motion prediction and a conflict-zone occupancy coefficient to proactively address potential collisions, resulting in the generation of safe and feasible reference trajectories. Simulation results in complex multi-vehicle scenarios validate the framework's effectiveness in enhancing intersection navigation safety and efficiency.
Automated vehicles can now navigate unsignalized intersections safely by integrating decision-making and trajectory planning into a single framework.
This paper presents a novel framework for integrated Decision-Making (DM) and Trajectory Planning (TP) for automated vehicles at unsignalized intersections. The approach leverages a Finite Horizon Optimal Control Problem (FHOCP) that employs Time-Varying Artificial Potential Fields (TV-APF). By utilizing short-horizon motion prediction and a dedicated conflict-zone occupancy coefficient, the framework suitably accounts for potential collisions within the FHOCP. The proposed method effectively unifies DM and TP, ensuring the generation of a feasible and safe reference trajectory. Simulation results in multi-vehicle traffic scenarios demonstrate the effectiveness of the approach.
