Research On The Intelligent Truck Dispatching Method For Open-pit Mines

In recent years,the rapid development of intelligent networking and autonomous driving technology has marked that unmanned driving has become a major development trend in the automotive industry.Limited areas such as open-pit mines and closed parks have become ideal scenarios for the commercialization of unmanned driving technology and have been preliminarily commercialized.Application,relying on intelligent connected vehicle technology,various types of operation vehicles can transmit and share real-time information with other vehicles,roadside equipment and the cloud,thereby realizing multi-vehicle coordinated scheduling,which can greatly improve the efficiency and performance of vehicle operation.It is helpful to improve the efficiency of system transportation.However,domestic open-pit mines are still manually scheduled by experience,and the real-time data brought by informatization,digitization and intelligence of open-pit mines cannot be effectively applied,which resulting in low transportation efficiency and high operating costs.Based on the existing trucks scheduling methods,this paper establishes a multi-objective traffic flow planning model for unmanned truck scheduling in open-pit mines,designs a real-time matching algorithm for truck-shovel tasks.They are simulated and verified by MATLAB software,and the method in this paper provides a new solution to the optimization problem of truck scheduling in open-pit mines.The specific work of this paper mainly includes the following three aspects:(1)Research on multi-objective traffic flow planning methods for driverless fleet.Firstly,the content of the traffic flow planning model and its significance to the trucks dispatching in open-pit mines are explained in detail,and the construction of the traffic flow planning model for the unmanned fleet is analyzed.The objective function of traffic flow planning model is designed with considering transportation cost,equipment utilization rate,ore grade deviation and other factors.Restrictions are designed according to mine production needs and mine trucks transportation process,and a multi-objective traffic flow planning model suitable for unmanned fleet is constructed.(2)Research the real-time scheduling methods of trucks for multi-unloading crushing stations.The operation scenarios and classification of real-time scheduling are introduced in detail,and the limitations of existing real-time scheduling methods are analyzed according to the development of intelligent network technology and the status quo of real-time scheduling in mining areas.Considering the influence of equipment in operation on mine trucks scheduling,the iterative prediction models of waiting time for heavy and empty trucks scheduling are designed respectively,and the coupling between real-time scheduling and traffic flow planning is established based on the path arrears time and the production completion.The trucks real-time dispatching model for the multi-unloading crushing stations is constructed.(3)Simulation and verification of the methods proposed in this paper.Based on MATLAB software,the multi-objective traffic flow planning model of unmanned fleet in open-pit mines and the trucks real-time scheduling model for multi-unloading crushing stations are simulated to prove the feasibility of the methods in this paper.The traffic flow planning and the real-time scheduling results are compared with the existing methods to prove the superiority of the methods proposed in this paper.Finally,this paper summarizes the research,analyzes the advantages and disadvantages of this research,and determines the future research content.