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2026 conference-paper

Backward Fuzzy Driving Control for 6×4 Off-Road Vehicles

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4Institutions déclarées
1Pays d’affiliation déclarés

Résumé fourni par la source

Off-road autonomous vehicle systems must be able to operate across unstructured and variable terrain while avoiding obstacles. This presents significant challenges in vehicle and control system design, especially for less conventional platforms such as 6×4 vehicles. While forward driving autonomy has developed and matured in recent years, effective reverse navigation remains an under-explored area of vehicle co-design. Reversing 6×4 vehicles have limited rear steering authority, an extended wheelbase, and asymmetric traction, which introduce complex dynamics into any control system that is used. To address this need, a robust and experimentally validated fuzzy logic control architecture for 6×4 reverse navigation was developed during the course of this project. This architecture incorporates both near-field and long-range path data with adaptive outputs controlling steering and velocity based on a rule base that covers the whole vehicle state space. This method has low computational cost and is robust to terrain changes, wheel slip, and actuator lag. To accomplish this, the controller coevolves with the vehicle design parameters, making this an effective co-design strategy. The vehicle design constraints are embedded into the controller through constraint-aware membership functions and rule tuning, reducing the need for terrain-specific calibration. The architecture is modular and scalable across numerous similar platforms, supporting rapid reconfiguration and vehicle design exploration for future autonomous off-road vehicles such as those used in expeditionary environments.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Backward Fuzzy Driving Control for 6×4 Off-Road Vehicles
Date Crossref
07/04/2026
Éditeur
SAE International
Type
proceedings-article

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Institutions déclarées

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Sujets associés

Vehicle Dynamics and Control SystemsControl and Dynamics of Mobile RobotsRobotic Locomotion and Control

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