Intelligent Vehicle Path Tracking Control Method Based on Curvature Optimisation.

Area of Science:

• Automotive Engineering
• Control Systems
• Robotics

Background:

• Intelligent vehicles (IVs) face a conflict between path tracking accuracy and body stability.
• This conflict arises from the mutual restriction of these two performance metrics during vehicle movement.

Purpose of the Study:

• To propose an intelligent vehicle path tracking control method based on curvature optimization.
• To reduce the comprehensive performance conflict between path tracking accuracy and body stability in IVs.

Main Methods:

• Developed a three-degrees-of-freedom vehicle dynamics model.
• Incorporated a preview error model considering vehicle roll.
• Designed a path tracking control method utilizing curvature optimization.

Main Results:

• Achieved up to 84.10% optimization in lateral deviation with a 2% stability improvement at 10 m/s and 0.15 m⁻¹ curvature.
• Demonstrated up to 66.80% lateral deviation optimization with a 4% stability improvement at 10 m/s and 0.2 m⁻¹ curvature.
• Showcased 20-30% body stability improvement at 15 m/s and 0.15 m⁻¹ curvature, even triggering boundary conditions.

Conclusions:

• The curvature optimization controller effectively enhances the tracking accuracy of fuzzy sliding mode controllers.
• The proposed method ensures smooth vehicle operation by incorporating body stability constraints during optimization.