Modelling and control strategies in path tracking control for autonomous tracked vehicles: A review of state of the art and challenges.

• Dynamic model of the tracked vehicle considered this type of forces which is traction, hydrodynamic, centrifugal, lateral friction, longitudinal resistive, bulldozing, and compaction force. • Path tracking is vital in autonomous vehicles since it is designed to deliver appropriate steering, throttle, and brake input to control the vehicle's direction and speed along a predefined path. • Model Predictive Control (MPC) may handle system limits and future predictions. • The objective of a path tracking controller is to eliminate any variation in vehicle direction from the specified path. This paper provides a review of path tracking strategies used in autonomous vehicle control design. Several elements of modelling process and path tracking control are examined, including the vehicle model implemented, the path tracking control algorithms used, and the criteria for evaluating the controller's performance. Path tracking control is classified into several forms based on its methodology and linearity. Vehicle models are grouped into numerous types based on the linearity and the intended behaviour to be observed. This study explores each of these strategy in terms of the applicability and disadvantages/advantages. The main challenges in the field of path tracking control are defined and future research directions are offered based on the critical reviews. Based on the entire review, a model-based controller based on a linear vehicle model and assessed with hardware-in-the-loop (HIL) is suggested. This review is aimed to serve as a starting point for determining which controllers to use in path tracking control development for an autonomous tracked vehicle. [ABSTRACT FROM AUTHOR]