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[T-IV] This repository collects research papers of large Vision Language Models in Autonomous driving and Intelligent Transportation System. The repository will be continuously updated to track the latest update.
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| 2026-08-06 | 467 |
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# Vision Language Models in Autonomous Driving: A Survey and Outlook :oncoming_automobile:
<div align="center">
<a href="https://ieeexplore.ieee.org/document/10531702"><img src="https://img.shields.io/badge/arXiv-2310.14414-b31b1b.svg" alt="arXiv Badge"/></a>
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This repository collects research papers on __Vision Language Models in Autonomous Driving: A Survey and Outlook__. The repo maintained by [TUM-AIR](https://www.ce.cit.tum.de/air/home/) will be continuously updated to track the latest work in the community.
**Keywords: Vision Language Model, Large Language Model, Autonomous Driving, Intelligent Vehicle,
Conditional Data Generation, Decision Making, Language-guided Navigation, End-to-End Autonomous Driving**
<p align="center">
<img src="Assets/figure1.png" width="330" height="330"/>
</p>
## :fire: Update
- [17.May.2024] Our paper has been accepted by [IEEE Transactions on Intelligent Vehicles](https://ieeexplore.ieee.org/document/10531702/keywords#keywords).
- [22.Oct.2023] ArXiv Version: Vision Language Models in Autonomous Driving and Intelligent Transportation Systems
## 🤝 Citation
Please visit [Vision Language Models in Autonomous Driving: A Survey and Outlook](https://ieeexplore.ieee.org/document/10531702) for more details and comprehensive information. If you find our paper and repo helpful, please consider citing it as follows:
```BibTeX
@ARTICLE{10531702,
author={Zhou, Xingcheng and Liu, Mingyu and Yurtsever, Ekim and Zagar, Bare Luka and Zimmer, Walter and Cao, Hu and Knoll, Alois C.},
journal={IEEE Transactions on Intelligent Vehicles},
title={Vision Language Models in Autonomous Driving: A Survey and Outlook},
year={2024},
pages={1-20},
keywords={Autonomous vehicles;Task analysis;Planning;SData models;Surveys;Computational modeling;Visualization;Vision Language Model;Large Language Model;Autonomous Driving;Intelligent Vehicle;Conditional Data Generation;Decision Making;Language-guided Navigation;End-to-End Autonomous Driving},
doi={10.1109/TIV.2024.3402136}}
```
## :page_with_curl: Introduction
The applications of **Vision-Language Models (VLMs)** in the fields of **Autonomous Driving (AD)** and **Intelligent Transportation Systems (ITS)** have attracted widespread attention due to their outstanding performance and the ability to leverage **Large Language Models (LLMs)**. By integrating
language data, the vehicles, and transportation systems are able to deeply understand real-world environments, improving driving safety and efficiency
<p align="center">
<img src="Assets/figure2.jpg"/>
</p>
## 🌟 Large VLMs in Autonomous Driving
### Perception and Understanding
| Method Excerpt of 49,147 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:5bde30f0c09d63ee, desc:vision-language