Unmanned Path Control Using Scenario-Based Subpath Strategies
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Solution Overview
Problem
Existing unmanned driving systems face inefficiencies due to the need to process and analyze large amounts of environment information, which occupies significant memory resources and reduces system efficiency.
Innovation Solution
The system pre-obtains target paths and scenario types, allowing direct determination of the current scenario type based on environment information, thereby reducing the need for extensive processing and analysis, and improving efficiency by minimizing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the unmanned driving system processes and analyzes large amounts of environment information in real-time, then the control accuracy and adaptability are improved, but the memory resource consumption increases and system efficiency decreases
Solution Approach 1:
The patent applies preliminary action by pre-dividing the path into multiple subpaths with different scenario types before the unmanned device actually travels. This allows the system to have control strategies ready in advance for each scenario type, eliminating the need for real-time analysis of large amounts of environment information while maintaining accurate and adaptive control.
2Speed
If the system pre-processes and stores environment information for all possible scenarios, then the control response speed is improved, but the memory resource occupation increases
Solution Approach 1:
The patent applies segmentation by dividing the entire path into multiple subpaths, where each subpath corresponds to a specific scenario type. This segmentation allows the system to store only the necessary environment information and control strategies for each specific scenario type rather than pre-processing all possible scenarios, thereby reducing memory resource occupation while maintaining fast control response speed.
3Adaptability or versatility
If the unmanned device performs real-time path planning and environment analysis, then the adaptability to unknown scenarios is improved, but the computing resource consumption and time delay increase
Solution Approach 1:
The patent applies preliminary action by pre-dividing the path into subpaths with different scenario types before execution. This allows the system to have control strategies ready in advance for each scenario type, eliminating the need for real-time analysis of large amounts of environment information while maintaining accurate and adaptive control.
Data Source
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AI summary
An unmanned device control method and apparatus, a storage medium, and an electronic device. An unmanned device is controlled to move according to a preplanned target path (S 102); current environment information of the unmanned device is obtained (S104); according to the current environment information of the unmanned device, a target subpath on which the unmanned device is located is determined, from target subpaths included in the target path, as a designated subpath (S 106); and a control strategy is then determined according to a scenario type corresponding to the designated subpath, and a determined control strategy is used to control the unmanned device (S108).