## 1 Introduction
\begin{table}
\begin{tabular}{c c c} \hline
**Sensors** & **Advantages** & **Disadvantages** \\ \hline \multirow{2}{*}{GNSS} & Providing absolute position and heading & \multirow{2}{*}{Affected by occlusion} \\  & information all-day & \\ \hline \multirow{2}{*}{INS} & Providing high-precision and high-frequency & \multirow{2}{*}{
\begin{tabular}{c} Inevitable drift by time and \\ temperature \\ \end{tabular} } \\  & attitude data & \\ \hline \multirow{2}{*}{MV} & Low cost, rich information, suitable for irregular & \multirow{2}{*}{Affected by light and shadow} \\  & land plots or signal-blocking environments & \\ \hline \multirow{2}{*}{LiDAR} & \multirow{2}{*}{High precision, strong anti-interference ability} & \multirow{2}{*}{High cost, affected by dust} \\  & & \\ \end{tabular}
\end{table} 
Table 1: Comparison of advantages and disadvantages of three types of sensors. The purpose of this paper is to summarize the application and development of path-tracking control methods in various agricultural vehicles in different working scenarios, including the construction of vehicle models and the application and improvement of control algorithms. This work can help researchers timely understand the current application status of path-tracking control methods in autonomous agricultural vehicles, and provide valuable guidance for the further development of intelligent agriculture and precision agriculture. The main work of this article is as follows. The first section summarizes the composition of the agricultural machinery automatic navigation system and the importance of path-tracking control technology and introduces and compares the path-tracking control methods that are frequently used in agricultural vehicles. Section 2 introduces different models of path-tracking control methods for automatic agricultural machinery navigation, including kinematic models and dynamic models. The next section focuses on the review and discussion of the application and improvement of agricultural vehicle path-tracking control methods in dry fields, paddy fields, orchards, agricultural robots, and facility agriculture, as well as articulated agricultural vehicles. Challenges and prospects of research on path-tracking control technology for agricultural vehicles' automatic navigation are discussed in Section 4. Finally, some conclusions of this paper are presented. \begin{table}
\begin{tabular}{c c c} \hline
**Control Method** & **Advantage** & **Disadvantage** \\ \hline PID control & Simple structure, easy implementation, good robustness, and high accuracy & Parameter tuning is difficult, and there is a contradiction between overshoot and response time \\ \hline Fuzzy control & It does not dependent on precise mathematical models and can be applied to nonlinear systems with good robustness and adaptability & The selection of rules is not systematic, the tracking error is large, and it is difficult to correct quickly \\ \hline Pure pursuit control & Few control parameters and predictable & Poor robustness in selecting preview points and difficulty in adjusting the look-ahead distance \\ \hline Optimum control & Performance indicators can be optimized & Poor adaptability to nonlinear systems and high requirements for model accuracy \\ \hline Sliding mode control & Insensitivity to external disturbances, few adjustment parameters, and fast response speed & There is a chattering phenomenon \\ \hline Model predictive control & It can compensate for the uncertainty of the system timely and enhance the stability of the system & High computational complexity and poor real-time performance \\ \hline Neural network control & It has good adaptability to the nonlinear characteristics of agricultural machinery movement & The algorithm is complex, requires a large number of high-quality training samples, and has a weak generalization ability \\ \hline Linear quadratic optimal control & It can obtain the optimal control strategy under a certain performance indicator & Poor performance on nonlinear models \\ \hline \end{tabular}
\end{table}