SM-NR is a geometric planner that identifies meeting gaps on narrow roads and selects from cut-in, back-up, and meet maneuvers, claiming higher success rates than TEB and P2EG.
Robust decision making for autonomous vehicles at highway on-ramps: A constrained adversarial reinforcement learning approach,
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Scene Modeling of Autonomous Vehicles Avoiding Stationary and Moving Vehicles on Narrow Roads
SM-NR is a geometric planner that identifies meeting gaps on narrow roads and selects from cut-in, back-up, and meet maneuvers, claiming higher success rates than TEB and P2EG.