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Autonomous Driving Simulator

Framework
Instructions
Developers

Framework

Instructions

1. Workflow

Step 1: Collect data from the Simulator
Step 2: Design neural network class (torch.nn.Module)
        Write data processing class (torch.utils.data.Dataset)
Step 3: Train the model and save weights (torch.utils.data.DataLoader, optimizer, loss function, …)
Step 4: Drive a car in the Simulator using the trained model

2. Train

Please open the "Simulator_train" application on your operating system.

Once opened, the Scene will initiate the recording of training data, which will be saved in the "Data/DatasetX/IMG" path and the "Data/DatasetX/VehicleData.txt" file.

In this VehicleData.txt the data is: the path of IMG, throttle(range: 0 to 1), brakes(range: 0 to 1), sterring(range: -1 to 1).

Please note that you should not remove the "Index.txt" file from the "Data/" directory.

3. Drive

Please open the "Simulator_test" application on your operating system.

and then run your:

python drive.py

In this scene, 3 images are output to your net, and 3 elements of control are acepted.(throttle, brakes and steering)

4. Simulator Functions

Function	Keyboard Defaults	Gamepad Defaults
Sterring	A/D	Left Stick - Left/Right
Throttle	W	Left Stick - Up, Right Trigger
Brakes	S	Left Stick - Down, Left Trigger
Reset the Position	F1	-
Switch mouse control	Mouse right button	-
Quit	ESC	-

5. Simulator Scenes Download Link:

Source code:

https://gitlab.lrz.de/tum-autonomousdriving/autonomous-driving

Build:

https://syncandshare.lrz.de/getlink/fiEQ6uWeJQFmosTX7HsxwG/

Useful Vision Algorithms

Pretrained Weights:

https://syncandshare.lrz.de/getlink/fi6mGLJoqSu3GEBxW7aWNT/weights

1. Object Detection

1.1 YOLOv5

1.2 YOLOv8

2. Semantic Segmentation

2.1 YOLOv5_sg

Developers

4. Programmers

Tang Yuhang	Guo Yujie	Chen Zehao	Feng Tinghan	Tang Shaolong
Ning Junbing	Jasmina Stratorska	Maram Bayadsi

5. Former Programmers

Gao Yichao	Yu Zhou	Michael Sodamin	Song Yinglei	Liu Hongshen
Liu Lian	Liu Hao	Xie Tongtong	Liu Zhuo	Yang Xiaohan

tum-autonomousdriving/autonomous-driving-simulator