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Intelligent autonomous articulated vehicles (IAAVs), the most important transportations of intelligent mining system, are the future direction of mining industry. Though it could realize the unmanned drive, without supports of hydraulic steering process analyses and vehicle dynamic researches, there are no references for the IAAVs to adjust the steering angle in certain driving error. It still has to check the signal from the angle sensor repeatedly to track the planned path in the working process, which lead to the low control accuracy. In this paper, the theories of hydraulic steering process and vehicle model will be developed for the vehicle intelligent control with the analyses of road and tire characteristics based on the principle of least resistance.

Autonomous truck with modular chassis has the characteristics of high driving flexibility and strong load capacity. It can be equipped with different numbers of modular chassis according to the task requirements. The application of autonomous truck can solve the problems of traffic accidents and shortage of drivers effectively, which is the development trend of trucks in the future. For the collision-free trajectory planning problem of dual-modular chassis autonomous truck, this paper designs a hierarchical local trajectory planner that combines the artificial potential field method with polynomial curve fitting method. This planner plans the center of mass trajectory firstly, and then generates the modular chassis trajectories according to the position relationship between the center of mass and the chassis.

With high maneuverability and heavy-duty load capacity, articulated steer vehicles (ASV) are widely used in construction, forestry and mining sectors. However, the steering process of ASV is much different from wheeled steer vehicles and tractor-trailer vehicles. Unsuitable steering control in path following could easily give rise to the “snaking” behaviour, which greatly reduces the safety and stability of ASV. In order to achieve precise control for ASV, a novel path tracking control method is proposed by virtual terrain field (VTF) method. A virtual U-shaped terrain field is assumed to exist along the reference path. The virtual terrain altitude depends on the lateral error, heading error, preview distance and road curvature. If the vehicle deviates from the reference line, it will be pulled back to the lowest position under the influence of additional lateral tire forces which are caused by the virtual banked road.