SafeDriveVLA: Navigation-Conditioned World Model Dreaming for Conflict-Aware End-to-End Autonomous Driving
cs.RO
Submitted: 2026-10-14
Updated: 2026-10-14
Comments: Accepted at CoRL 2026. Project page: https://safedrive-vla.github.io/SafeDriveVLA/
Code: https://github.com/ASGuard-UCI/safedrive-vla
Project page: https://safedrive-vla.github.io/SafeDriveVLA
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles
- Planning-oriented Autonomous Driving
- VAD: Vectorized Scene Representation for Efficient Autonomous Driving
- SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment
- Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail
- Vega: Learning to Drive with Natural Language Instructions
- AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning
- Baidu Apollo EM Motion Planner
- Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
- A Survey on Vision-Language-Action Models for Autonomous Driving
- Vision-Language-Action Models for Autonomous Driving: Past, Present, and Future
- Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving
- DriveLM: Driving with Graph Visual Question Answering
- OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving
- EMMA: End-to-End Multimodal Model for Autonomous Driving
- FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving
- Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models
- ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation
- OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model
- NoRD: A Data-Efficient Vision-Language-Action Model that Drives without Reasoning
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- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies