Abstract
This article sorts out and analyzes the operation scenarios and typical applications of intelligent networked automatic driving in the open-pit mine scene, and analyzes the corresponding relationship between them. Based on this, the overall technical architecture of the open-pit mine intelligent networked autonomous driving is analyzed, and the technical attributes of the vehicle end, network and cloud platform are studied under this architecture. Finally, the trend of future technology and industry development is forecasted.
Highlights
This article sorts out and analyzes the operation scenarios and typical applications of intelligent networked automatic driving in the open-pit mine scene, and analyzes the corresponding relationship between them
From the perspective of the application of intelligent networked automatic driving, the realization of applications such as remote driving of mining trucks, operations between mining trucks and other construction machinery, and mining truck driving path planning are required to support the safe operation of automatic driving. 2.1 Operation Scenario 2.1.1 Loading The loading operation scenario means that the unloaded mining trucks are driven to the loading operation point in sequence, the loading equipment loads the materials into the mining truck bucket, and the mining trucks leave the operation point in turn
The mining truck automatically drives to the loading area according to the path and task planned by the cloud platform, combined with the perception of the surrounding environment, and sends real-time status information and task information of its own vehicle to the loading equipment in real time
Summary
The mining truck can automatically drive to the unloading area according to path planning and operation tasks, combined with the perception of the surrounding environment, and send the real-time status and task information of its own vehicle to the loading equipment. The decision-making planning system first needs to receive vehicle sensing unit (lidar, millimeter wave radar, vision, etc.) information, V2X (V2I, V2V, etc.) information, vehicle current positioning information and other multi-sensor fusion After the information, predictions are made based on the external environment output by the perception and communication equipment and the road plan of oneself to ensure the safety of the driving process After receiving data such as obstacles or other vehicles on the driving path, the information is provided to the path planning module for local path planning. Supported by LTE-V2X direct communication technology: 1) Car-to-vehicle direct communication: support forward collision warning, inter-vehicle operation coordination, etc.; 2) vehicle and intelligent roadside equipment communication: support road condition reminders, perception fusion, etc., to improve the safety of autonomous driving and the efficiency of collaborative operations
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