---
license: mit
tags:
  - autonomous-driving
  - carla
  - yolo
  - lane-detection
  - ufld
  - pytorch
  - computer-vision
  - self-driving-car
datasets:
  - custom
language:
  - en
---

# Autonomous Driving CARLA Models

Pre-trained models for autonomous driving in the CARLA 0.9.15 simulator.

## Models

| Model | File | Size | Description |
|-------|------|------|-------------|
| YOLO11n | `yolo_carla_best.pt` | ~6MB | Object detection (vehicles, pedestrians, traffic lights, speed signs) |
| UFLD | `ufld_carla_best.pth` | ~735MB | Lane detection fine-tuned on CARLA |
| TuSimple | `tusimple_18.pth` | ~245MB | Pre-trained lane detection backbone |

## YOLO11n Object Detection

Custom-trained on CARLA simulator data.

**Classes:**
- 0: Vehicle
- 1: Pedestrian  
- 2: Traffic Light
- 3: Speed Limit Sign

**Training:**
- Epochs: 250
- Batch Size: 128
- Optimizer: AdamW
- Learning Rate: 0.005
- Image Size: 640×640

![YOLO Results](yolo_training_results.png)
![Confusion Matrix](yolo_confusion_matrix.png)

## UFLD Lane Detection

Fine-tuned Ultra Fast Lane Detection model.

**Architecture:**
- Backbone: ResNet-18
- Grid: 100×56
- Input: 800×288

**Training:**
- Epochs: 50
- Batch Size: 32
- Optimizer: Adam
- Learning Rate: 1e-4
- Loss: SoftmaxFocalLoss + ParsingRelationLoss

![UFLD Loss Curve](ufld_loss_curve.png)

## Usage

```python
from huggingface_hub import hf_hub_download

# Download YOLO model
yolo_path = hf_hub_download(
    repo_id="jkdxbns/autonomous-driving-carla",
    filename="yolo_carla_best.pt"
)

# Download UFLD model
ufld_path = hf_hub_download(
    repo_id="jkdxbns/autonomous-driving-carla",
    filename="ufld_carla_best.pth"
)
```

## GitHub Repository

Full source code: [github.com/jkdxbns/autonomous-driving-carla](https://github.com/jkdxbns/autonomous-driving-carla)

## Author

**Justin Mascarenhas**  
CMPE 789 - Robot Perception  
Rochester Institute of Technology

## License

MIT License