  Full drive-by-wire electric vehicles (FDWEV) with X-by-wire technology can
achieve independent driving, braking, and steering of each wheel, providing a
good application platform for autonomous driving technology. Path planning and
tracking control, in particular, are critical components of autonomous driving.
However, It is challenging to comprehensively design an robust control
algorithm by integrating vehicle path planning in a complicated unstructured
scenario for FDWEV. To address the above issue, this paper first proposes the
artificial potential field (APF) method for path planning in the prescribed
park with different static obstacles to generate the reference path
information, where speed planning is incorporated considering kinematics and
dynamic constraints. Second, two tracking control methods, curvature
calculation (CC-based) and model predictive control (MPC-based) methods with
the lateral dynamics model, are proposed to track the desired path under
different driving conditions, in which a forward-looking behavior model of the
driver with variable preview distance is designed based on fuzzy control
theory. CarSim-AMESim-Simulink co-simulation is conducted with the existence of
obstacles. The simulation results show that the proposed two control approaches
are effective for many driving scenarios and the MPC-based path-tracking
controller enhances dynamic tracking performance and ensures good
maneuverability under high-dynamic driving conditions.
