Create README.md

README.md

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+---
+license: apache-2.0
+size_categories:
+- 100B<n<1T
+---
+# **PDM-Lite**: A Rule-Based Planner for CARLA Leaderboard 2.0
+
+## Description
+PDM-Lite is a state-of-the-art rule-based expert system for autonomous urban driving in CARLA Leaderboard 2.0, and the first to successfully navigate all scenarios. This dataset was used to create the QA dataset for DriveLM-Carla, a benchmark for evaluating end-to-end autonomous driving algorithms with Graph Visual Question Answering (GVQA). DriveLM introduces GVQA as a novel approach, modeling perception, prediction, and planning through interconnected question-answer pairs, mimicking human reasoning processes. Additionally, this dataset was used for training Transfuser++ with imitation learning, which achieved 1st place (map track) and 2nd place (sensor track) in the CARLA Autonomous Driving Challenge 2024.
+
+##Dataset Features
+
+- **High-Quality Data:** 1759 routes with 100 % route completion and zero infractions
+- **Diverse Scenarios:** Covers 38 complex scenarios, including urban traffic, other traffic participants violating traffic rules and high-speed highway driving
+- **Focused Evaluation:** Short routes averaging 160 m in length
+
+## Data Modalities
+
+- **BEV Semantics Map:** 512x512 pixels, centered on ego vehicle, 2 pixels per meter resolution
+- **Image Data:** RGB images, semantic segmentation, and depth information
+- **Lidar Data:** Detailed lidar point clouds
+- **Augmented Data:** Augmented versions of RGB, semantic, depth, and lidar data
+- **Simulator Data:** Comprehensive information on nearby objects
+
+For more information: https://github.com/OpenDriveLab/DriveLM/tree/DriveLM-CARLA
+## License and Citation
+Apache 2.0 license unless specified otherwise.
+
+```bibtex
+@article{sima2023drivelm,
+  title={DriveLM: Driving with Graph Visual Question Answering},
+  author={Sima, Chonghao and Renz, Katrin and Chitta, Kashyap and Chen, Li and Zhang, Hanxue and Xie, Chengen and Luo, Ping and Geiger, Andreas and Li, Hongyang},
+  journal={arXiv preprint arXiv:2312.14150},
+  year={2023}
+}
+@misc{contributors2023drivelmrepo,
+  title={DriveLM: Driving with Graph Visual Question Answering},
+  author={DriveLM contributors},
+  howpublished={\url{https://github.com/OpenDriveLab/DriveLM}},
+  year={2023}
+}
+@misc{Beißwenger2024PdmLite,
+  title        = {{PDM-Lite}: A Rule-Based Planner for CARLA Leaderboard 2.0},
+  author       = {Bei{\ss}wenger, Jens},
+  howpublished = {\url{https://github.com/OpenDriveLab/DriveLM/blob/DriveLM-CARLA/docs/report.pdf}},
+  year         = {2024},
+  school       = {University of Tübingen},
+}
+```