Unifying Decision-Making and Trajectory-Planning in Unsignalized Intersections Using Time-Varying Potential Fields
It addresses the challenge of integrating decision-making and trajectory planning for autonomous vehicles in complex intersection scenarios, but results are only simulation-based and lack quantitative comparison.
The paper introduces a unified framework for decision-making and trajectory planning at unsignalized intersections using time-varying potential fields, achieving safe and feasible trajectories in multi-vehicle simulations.
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.