VERDI: VLM-Embedded Reasoning for Autonomous Driving

1. 1Leverage fine-tuned Vision-Language Models (VLMs) for trajectory planning
2. 2Apply commonsense reasoning to make near-optimal decisions with limited information
3. 3Integrate VLM-Embedded Reasoning into autonomous driving stacks to improve performance
4. 4Evaluate VERDI's effectiveness in benchmark evaluations and real-world tests

Autonomous driving engineers and AI researchers can benefit from VERDI as it enhances trajectory planning and decision making in complex real-world scenarios

💡 VERDI improves autonomous driving performance by emulating human behavior with fine-tuned VLMs and commonsense reasoning

🚗💡 VERDI enhances autonomous driving decision making with VLM-Embedded Reasoning