• 💡 Fields of interest: Machine Learning 🦾, Computer Science 🖥️, Control Systems and Autonomous Systems 🏎️ ✈️
• 📚 Education: Machine Learning (Msc) and Automation and Control Systems (BEng) at Gdańsk University of Technology

e-mail: durawa.p.soft@gmail.com

This project implements OS/US detection system for iRacing simulator. The detection model is based on Adaptive Neuro Fuzzy Inference System (ANFIS) [2], [3]. The idea to use ANFIS is based on work of Hirche and Ayalew [1].

Project repository: US/OS detection system for iRacing

• Data was collected on Centripetal Circuit.
• Each test consisted of Sine with Dwell maneuver.
• Tests are were performed under different vehicle velocities, sine frequencies, dwell times, maximum steering angles.
• Dataset is balanced for left and right turns.
• Data collection procedure was derived from [1].

• Model was trained using the ANFIS-PyTorch framework implemented by J. Power [3].
• Model for Mazda MX-5 is available.
• Mazda MX-5 model struggles when vehicle runs on kerbs.

• [1] Hirche, B. and Ayalew, B., "A Fuzzy Inference System for Understeer/Oversteer Detection Towards Model-Free Stability Control" SAE Int. J. Passeng. Cars - Mech. Syst. 9(2):2016, doi:10.4271/2016-01-1630.
• [2] Jang, Jyh-Shing., (1993). ANFIS Adaptive-Network-based Fuzzy Inference System. Systems, Man and Cybernetics, IEEE Transactions on. 23. 665 - 685. 10.1109/21.256541.
• [3] Power, J. Implementation of ANFIS using the pyTorch framework Source: https://github.com/jfpower/anfis-pytorch [Access: 29.04.2024]