Multidirectional motion coupling based extreme motion control of distributed drive autonomous vehicle.

Area of Science:

• Autonomous Vehicle Control
• Vehicle Dynamics and Stability
• Robotics and Intelligent Systems

Background:

• Distributed Drive Autonomous Vehicles (DDAVs) face challenges in maintaining control accuracy and stability during extreme maneuvers.
• Existing control methods may not adequately address multidirectional motion coupling under varied road conditions.

Purpose of the Study:

• To enhance the multidirectional motion control accuracy and driving stability of DDAVs under extreme conditions.
• To develop an effective extreme speed estimation method and a robust multidirectional motion coupling control law.

Main Methods:

• Proposed an extreme speed estimation method utilizing a dynamic boundary defined by yaw rate, sideslip angle, and roll angle.
• Designed a multidirectional motion coupling control law using an eight-degrees-of-freedom (8-DOF) vehicle dynamic model.
• Integrated these methods into a Multidirectional Motion Coupling Control System (MMCCS) for DDAVs.

Main Results:

• Simulations demonstrated the effectiveness of the proposed MMCCS in double-line-shifting and serpentine driving scenarios.
• The system showed robust performance across different road adhesion conditions.
• The proposed method proved superior to existing integrated control strategies.

Conclusions:

• The developed extreme speed estimation and multidirectional motion coupling control methods significantly improve DDAV performance.
• The MMCCS offers enhanced stability and control accuracy for autonomous vehicles in extreme driving situations.
• This research contributes to the advancement of safer and more reliable autonomous driving systems.