DriveAnchor: Progressive Anchor-based Flow Learning for Autonomous Driving Planning

• URL: http://arxiv.org/abs/2606.00519v1
• Date: Sat, 30 May 2026 04:17:59 GMT
• Title: DriveAnchor: Progressive Anchor-based Flow Learning for Autonomous Driving Planning
• Abstract summary: DriveAnchor is a framework for autonomous driving planning.<n>It achieves behavioral diversity, controllability, and safety in a composable pipeline.<n>It reduces near-range collision rates by 89% and improves mean reward by 32% without degradation in imitation accuracy.
• Score: 6.848508447210393
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present DriveAnchor, a three-stage framework for autonomous driving planning that achieves behavioral diversity, controllability, and safety in a composable pipeline. Demonstration Flow Pretraining replaces the unstructured Gaussian prior with a vocabulary of 2,398 trajectory shapes constructed by farthest-point sampling, structurally grounding behavioral diversity in vocabulary coverage. Guided Flow Post-training jointly post-trains an Energy Field module with flow matching (FM), conditioning the Energy Field on static road geometry alone, to relocate anchors toward user-specified corridor polygons before flow generation, adding controllability without differentiable guidance; after Stage 2, new corridor presets require only Energy Field updates, not FM retraining. Reward-Refined Flow Fine-tuning applies zeroth-order reinforcement learning to align each anchor's output with collision-avoidance objectives: because the flow-matching model is a deterministic feedforward network in single-step mode, each anchor uniquely determines the output trajectory, reducing reward optimization to a direction search in anchor space without log-likelihood computation or ODE-to-SDE conversion. Evaluated on approximately 2 million held-out driving scenarios, DriveAnchor reduces near-range collision rates by 89% and improves mean reward by 32% without degradation in imitation accuracy, with 2.06 ms inference on NVIDIA Drive Orin. DriveAnchor has been validated through real-world vehicle testing, confirming its practicality for production deployment.

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