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Autonomous Driving Simulator

Contents

• 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:

LRZ Sync+Share https://syncandshare.lrz.de/getlink/fiEQ6uWeJQFmosTX7HsxwG/

Google Drive https://drive.google.com/drive/folders/1YPlSq4V3ArtOUVH11h-doQ2UqCsvQKtQ?usp=sharing

Developers

1. Affiliation

Chair of Robotics, Artificial Intelligence and Real-time Systems · Technical University of Munich

2. Supervisor

Prof. Dr.-Ing. habil. Alois Christian Knoll

3. Programmers

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

4. Corresponding Programmer

周立国 Zhou Liguo