Wi-Fi 6 Collision Avoidance Simulator

This project implements a simulation environment designed to integrate with Microsoft AirSim, enabling the testing of an edge service that leverages Wi-Fi 6 connectivity and computer vision for collision avoidance. The core objective is to evaluate the effectiveness of a low-latency, high-bandwidth communication service in ensuring the safety of semi-autonomous vehicles.

Key Features

• Wi-Fi 6 Connectivity: Utilizes the high-speed, low-latency capabilities of Wi-Fi 6 to simulate real-time communication between the edge service and the semi-autonomous vehicle.
• Computer Vision: Integrates a robust computer vision system that processes real-time frames to detect obstacles, ensuring timely intervention.
• Edge Computing: The service runs on edge servers, minimizing latency and enabling rapid decision-making in critical scenarios.
• Seamless Integration with AirSim: The simulator is built on top of AirSim, allowing for realistic simulation of vehicle dynamics and environmental conditions.
• Adaptive Control: The vehicle's control system is designed to respond dynamically to the edge service's commands, stopping or maneuvering the vehicle when an obstacle is detected.

Use Cases

• Safety Testing: Evaluate the system’s effectiveness in various collision scenarios, including pedestrians, vehicles, and static obstacles.
• Performance Benchmarking: Measure the impact of Wi-Fi 6 on communication latency and the overall responsiveness of the collision avoidance system.
• Scenario Simulation: Test in a variety of environments and under different conditions to ensure robustness and reliability.

Instructions

1. Download and unzip the AirSimNH scenario
2. Clone this repository
3. Create a VENV environment (Conda is not suggested and could cause bugs in the GUI) and activate it
4. Install the needed dependencies with pip

customtkinter==5.2.2
ftfy==6.2.0
numpy==2.0.0
pillow==10.3.0
regex==2024.5.15
requests==2.32.3
scipy==1.13.1
matplotlib==3.9.0
msgpack−rpc−python
airsim

5. Install Pytorch following the official guide
6. Install MMCV and MMSegmentation following the official guide

At this point everything should be ready.
To run the simulator, first start AirSim. Next, ensure that your VENV environment is active, and then execute the following command:

python ./app/GuiApp.py

Once started, if needed, go into settings and insert the ip address of the machine on which AirSim is running.

Docker

An image is also available on Dockerhub to easily run the project skipping the installation part.

You need an X server installed on the host machine. If you are on Windows you can use WSL2 as a workaround.