This paper presents an open-source Software-in-the-Loop (SIL) simulation platform designed for autonomous Ackerman vehicle research and education. The proposed framework focuses on simplicity, while making it easy to work with small-scale experimental setups, such as the XTENTH-CAR platform. The system was designed using open source tools, creating an environment with a monocular camera vision system to capture stimuli from it with minimal computational overhead through a sliding window based lane detection method. The platform supports a flexible algorithm testing and validation environment, allowing researchers to implement and compare various control strategies within an easy-to-use virtual environment. To validate the working of the platform, Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) algorithms were implemented within the SIL framework. The results confirm that the platform provides a reliable environment for algorithm verification, making it an ideal tool for future multi-agent system research, educational purposes, and low-cost AGV development. Our code is available at https://github.com/shantanu404/monosim.git.
@article{arxiv.2603.23965,
title = {MonoSIM: An open source SIL framework for Ackermann Vehicular Systems with Monocular Vision},
author = {Shantanu Rahman and Nayeb Hasin and Mainul Islam and Md. Zubair Alom Rony and Golam Sarowar},
journal= {arXiv preprint arXiv:2603.23965},
year = {2026}
}
Comments
6 pages, 16 figures, Published in "IEEE 12th International Conference on Automation, Robotics and Application 2026"