Autonomous Vehicle Path Planning in Historical Takeover Areas
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Solution Overview
Problem
Autonomous vehicles face challenges in passing certain driving areas due to safety restrictions, requiring manual intervention, which limits their autonomous capabilities.
Innovation Solution
The method involves obtaining historical control information from a previous manual passage through a restricted area and using it to determine a planned path for the vehicle to autonomously navigate these areas, adjusting path planning parameters based on decision-making, trajectory, and traffic constraints to ensure safety and feasibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles apply strict safety restrictions for autonomous driving, then the safety is improved, but the ability to pass certain driving areas autonomously deteriorates
Solution Approach 1:
The system performs preliminary actions by manually controlling the vehicle to pass through restricted areas beforehand, recording the actual control operations and environmental data. This historical manual control information is stored and later used to generate autonomous control strategies, allowing the vehicle to autonomously pass areas that initially would require manual intervention while maintaining safety standards.
Solution Approach 2:
Historical manual control information serves as an intermediary between manual and autonomous control modes. The system records actual driver operations, environmental conditions, and vehicle states during manual passage, then uses this intermediate data to train and validate autonomous control algorithms, enabling safe autonomous navigation through previously restricted areas.
2Ease of operation
If manual control is used to pass restricted areas, then the vehicle can pass through these areas, but the autonomous driving capability is limited
Solution Approach 1:
The system enables self-service by automatically learning from historical manual control data and generating autonomous control strategies without continuous human intervention. The vehicle records its own manual operation history, processes this data to create autonomous navigation plans, and executes these plans autonomously, progressively reducing the need for manual control while improving autonomous capability.
Solution Approach 2:
The system implements feedback by continuously recording actual vehicle states, environmental conditions, and control operations during manual passage through restricted areas. This historical feedback data is used to refine autonomous control algorithms, validate safety constraints, and improve future autonomous navigation performance in similar situations.
3Extent of automation
If historical control information is collected and processed, then the autonomous navigation capability is improved, but the system complexity increases
Solution Approach 1:
The system extracts only the essential and useful information from historical manual control data, such as key decision points, critical environmental features, and important control parameters. By filtering and selecting only the most relevant historical information, the system reduces data processing complexity while maintaining effective autonomous navigation capability.
Solution Approach 2:
The historical control information is segmented into distinct components including environmental conditions, vehicle states, control operations, and outcome results. This segmentation allows the system to process and analyze specific aspects independently, reducing overall system complexity while enabling comprehensive autonomous navigation through structured data utilization.
Data Source
Figure 2
Figure 3A~3B
Figure 3C~4
AI summary
Embodiments of the present disclosure provide a method and an apparatus for controlling a vehicle, a device and a storage medium. The method includes: in response to determining that a target vehicle is located in a historical takeover area, obtaining historical control information associated with passing through a historical path in the historical takeover area, the historical takeover area indicating an area through which a vehicle in a manual control state passed in a previous period; determining a planned path for the target vehicle to pass through the historical takeover area based on the historical control information; and controlling the target vehicle to pass through the historical takeover area in an automatic control state based on the planned path.