Can LVLMs Obtain a Driver's License? A Benchmark Towards Reliable AGI for Autonomous Driving

TL;DR

This paper introduces IDKB, a large-scale dataset designed to evaluate and improve Large Vision-Language Models' reliability for autonomous driving by encompassing comprehensive driving knowledge and testing 15 LVLMs.

Contribution

The paper presents IDKB, a new extensive dataset covering driving knowledge from theory to practice, and evaluates LVLMs' reliability in autonomous driving tasks.

Findings

Fine-tuning improves LVLM performance significantly.

IDKB enables comprehensive assessment of LVLMs in driving scenarios.

LVLMs show potential but still need enhancements for safety-critical tasks.

Abstract

Large Vision-Language Models (LVLMs) have recently garnered significant attention, with many efforts aimed at harnessing their general knowledge to enhance the interpretability and robustness of autonomous driving models. However, LVLMs typically rely on large, general-purpose datasets and lack the specialized expertise required for professional and safe driving. Existing vision-language driving datasets focus primarily on scene understanding and decision-making, without providing explicit guidance on traffic rules and driving skills, which are critical aspects directly related to driving safety. To bridge this gap, we propose IDKB, a large-scale dataset containing over one million data items collected from various countries, including driving handbooks, theory test data, and simulated road test data. Much like the process of obtaining a driver's license, IDKB encompasses nearly all the explicit knowledge needed for driving from theory to practice. In particular, we conducted comprehensive tests on 15 LVLMs using IDKB to assess their reliability in the context of autonomous driving and provided extensive analysis. We also fine-tuned popular models, achieving notable performance improvements, which further validate the significance of our dataset. The project page can be found at: \url{https://4dvlab.github.io/project_page/idkb.html}