Unmanned Driving Technology in Coal Mine Based on Semantic Information Method

Abstract

Aiming at the transportation scheduling problem of unmanned trucks in open-pit mines, an optimization model for transportation scheduling of unmanned trucks in open-pit mines is established, taking the minimum sum of fuel cost, fixed start-up cost, fault maintenance cost and network base station construction and maintenance cost as the objective function, and taking mining amount, crushing amount in crushing field, truck number and truck transportation work as the bundle reduction conditions. By adjusting the position of the encapsulated individual and the optimal encapsulated individual through the parameter position adaptive updating mechanism, the search range of the solution space can be enlarged, so that the algorithm can jump out of the local optimum. This paper analyzes the influence of vehicle clearance on coordinated traffic at intersections under clearance theory, and puts forward the minimum vehicle clearance to meet coordinated traffic. Generate trajectories with behavioral semantics through hierarchical online selection of primitives; Based on the model predictive control algorithm, the motion control module fully considers the execution ability, tracking deviation and control stability of the platform drive motor, and updates the weight coefficient of the control objective function in real time with the help of the semantic attributes of the behavioral motion primitives given by the motion planning, so as to reduce the lateral error, heading error and speed error of the trajectory tracking. Finally, a real vehicle is verified by a medium-sized hybrid unmanned crawler platform, which proves that the proposed intersection coordinated traffic model is feasible in theory, reflecting that the traffic density is a factor that affects the transportation efficiency. Under the condition of meeting the production requirements, reduce the intersection conflict and improve the traffic capacity of the intersection by adopting large-load unmanned mine trucks as much as possible, reducing the number of unmanned mine trucks and the interference between equipment.