Abstract: Abstract: Aiming at the harsh transportation conditions faced by unmanned dump trucks in open-pit mines, such as low road grade, multiple slopes and bends, large vehicle load, and wide range of variation, a lateral vertical collaborative control method for open-pit dump trucks is proposed, and the control strategy is modeled, simulated, and experimentally verified. Firstly, the lateral and longitudinal dynamic models of dump trucks were established based on the transportation conditions of open-pit mines, providing a theo-retical basis for the design of vehicle motion control strategies. Secondly, based on the coupling concept, an adaptive preview horizontal vertical layered control system for open-pit dump trucks was designed. The lateral control is based on a linear quadratic regulator (LQR), and a feedforward controller is used to reduce steady-state errors. A fuzzy controller is used to adaptively adjust the preview distance to improve the ac-curacy of path tracking control; Establish a layered feedback longitudinal speed controller for longitudinal control, using model predictive control and fuzzy PID feedback control respectively, and establish a reverse model for vehicle driving and braking to reduce the impact of dump truck load and road slope changes on longitudinal speed tracking. Once again, typical transportation conditions of open-pit mines were simulated in Simulink and Trucksim environments, and simulation comparative experiments were conducted. The results showed that compared to a single lateral controller, the lateral longitudinal collaborative controller can significantly improve the accuracy of vehicle path tracking while also ensuring the safety and stability of vehicle operation. Finally, an unmanned dump truck model test vehicle was built in the laboratory, and a simulated road model was designed and built based on the open-pit mine return road. Horizontal control simulation experiments were conducted under different working conditions; The results show that the lateral controller designed in this article can accurately track the desired path, verifying the feasibility and effec-tiveness of the lateral control strategy applied in autonomous vehicles.