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

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

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

Author

Justin Mascarenhas
CMPE 789 - Robot Perception
Rochester Institute of Technology

License

MIT License