Solution 1 V2.0

Introduction

This is a solution for the competition. The control system adopts an event driven architecture and features two asynchronous processes for control and monitoring, respectively.

Recommended Hardware Requirements

• CPU: Intel Xeno W-1290P
• RAM: 16GB
• GPU: Quadro RTX4000

Usage

1. To run the solution, first clone this repository: git clone https://github.com/York-SDCNLab/Solution1_v2.git.

2. Navigate to /path/to/Solution1 and run pip install -e . to setup the local dependencies. Once done, you can install the project dependencies by runnig pip install -r requirements.txt (Sometimes, there may have some conflicts when installing the dependencies, you can ignore and proceed to the next step).

3. Now the project is set up! You can run python main.py to run this solution with default pwm or command like python main.py 0.15 to run this solution with specified pwm value.

Note

1. Generally, the performance of this solution is dependent on the frame rate of the csi camera. The recommended throttle (PWM) setting are as follows:

• frame rate below 30Hz, throttle: up to 0.1
• frame_rate 30 - 40Hz, throttle: up to 0.16
• frame_rate 40 - 50Hz, throttle: up to 0.17
• frame_rate above 50Hz, throttle: up to 0.18

2. The qlab's fps will also influence the performance of this solution, the recommended fps for this solution is 30. If the fps is much lower than 30, the recommended throttle is 0.1
3. Sometimes not all processes are properly activated due to some communication issues with the qlab, you can rerun the solution after entering the map again.
4. We are using our own functions to generate map and control the traffic light. If you want to run Setup_Competition.py and Traffic_Lights_Competition.py, comment out spawn_on_node(node_id=node_id) # spawn the car on the specific node in the main.py and run Setup_Competition.py and Traffic_Lights_Competition.py to setup the map before starting the solution.