Study on Route Optimization Strategy of Unmanned Truck in Mining Area under Fuel Constraint Condition
In recent years,with the wide application of intelligent technology,driverless trucks,as a new type of mining transportation equipment,have been widely used in mining logistics because of their advantages of safety,reliability,accuracy and efficiency.However,in actual mining applications,the fuel supply of trucks is very limited,which limits the operating dis-tance and driving time of driverless trucks to some extent.Therefore,it is particularly important to find a path planning strategy to optimize fuel consumption and improve transportation efficiency.An unmanned truck routing strategy for optimized fuel con-sumption is proposed to optimize fuel consumption and enable more efficient transportation.An optimization model of vehicle route fuel consumption in mining area is established,which links fuel consumption with vehicle speed,truck power and other factors,and considers the limiting factors such as terrain,road conditions,location of gas stations and fuel storage capacity.On this basis,an improved genetic algorithm is used to search for the optimal solution,and its optimization accuracy is tested by cross-validation and sensitivity analysis.In order to verify the effectiveness and feasibility of this strategy,a practical test was carried out in a typical mining path.The test results show that,under the same fuel supply,compared with other intelligent algo-rithms,the proposed route planning strategy for optimized fuel consumption of unmanned trucks can effectively reduce fuel con-sumption and complete transportation tasks more efficiently.In addition,under different fuel supply conditions,the strategy can be quickly optimized according to real-time conditions,and the optimal solution can be obtained,which has certain practical value and application prospect.
driverless trucks in mining areasfuel constraintpath optimization strategyintelligent mine
万方数据
维普
