Year: 2025
Type: article
Abstract: All-terrain and armored vehicles (ATVs) are designed to operate in environments where the terrain changes significantly and affects their performance. Traditional control systems don’t adapt to changing environmental conditions, resulting in reduced performance and safety issues. TAC systems solve this by real-time terrain data-driven adaptation of control techniques to improve the performance, mobility, and stability of the vehicle. This project aims to develop and test a new TAC system that adapts to different terrain types, including swampy soil, rugged surfaces, and natural barriers, while maintaining vehicle operational excellence. The proposed TAC system does continuous terrain assessment through sensor data processing and machine learning algorithms that modify the fundamental control elements, which are wheel speeds, torque distribution, and suspension setpoints. Multiple scenario simulations were done through extensive modeling. Experimental data show that TAC improves vehicle stability during off-roading in sandy terrain and rocky surfaces and minimizes mechanical damage from unnecessary slippage and rollover. Military personnel, rescue teams, and exploration teams must use TAC for their missions because TAC helps teams make flexible and instant decisions during unpredictable scenarios.
DOI: 10.14419/5ce13315
Authors: Dr. Nidhi Mishra, Adil Raja, Dr. Parul Malik
Institution: Kalinga University
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4415764213
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