Autonomous Steering Override Thresholds for Scene-Based Handover
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Solution Overview
Problem
Existing vehicle travel control systems cannot accurately respond to requests for transitioning from autonomous steering control to manual operation based on the vehicle's travel scene, as they rely solely on the magnitude of the driver's steering holding force without considering the specific travel scenario.
Innovation Solution
The system sets multiple cancellation thresholds corresponding to different travel scenes, allowing for responsive transitions from autonomous steering control to manual operation by adjusting the steering torque requirements based on the current travel scenario, such as exiting a main road or navigating a curved route.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single cancellation threshold is used for autonomous steering control, then the system structure is simple, but the system cannot respond appropriately to different travel scenes
Solution Approach 1:
The single cancellation threshold is segmented into multiple scene-specific thresholds (first cancellation threshold for exit scenes, second cancellation threshold for curved routes, third cancellation threshold for other scenes). This segmentation allows the system to adapt to different travel scenes while maintaining a structured and manageable threshold configuration.
Solution Approach 2:
The cancellation threshold is made dynamic by automatically selecting different threshold values based on the detected travel scene. The system transitions from a static single threshold to a dynamic multi-threshold system that adapts in real-time to the current driving conditions, improving versatility without requiring manual intervention.
2Reliability
If the cancellation threshold is set to a large value, then the system working factor is improved, but the ease of override is reduced
Solution Approach 1:
Different cancellation thresholds are applied to different travel scenes based on their specific characteristics. The first cancellation threshold (larger value) is applied to exit scenes where system stability is crucial, while the second cancellation threshold (smaller value) is applied to curved routes where driver intervention may be more frequently needed. This local quality approach optimizes both reliability and ease of override for each scene.
Solution Approach 2:
The cancellation threshold parameter is changed based on the travel scene detection. The system automatically adjusts the threshold value (from first to second to third cancellation threshold) according to the current scene, allowing the parameter to vary dynamically to balance system working factor and ease of override across different driving conditions.
3Ease of operation
If the cancellation threshold is set to a small value, then the ease of override is improved, but false cancellation due to steering torque fluctuations increases
Solution Approach 1:
The system applies different threshold values to different travel scenes to address false cancellation issues. The first cancellation threshold (larger value) for exit scenes and the third cancellation threshold for general scenes provide higher stability and reduce false cancellations, while the second cancellation threshold (smaller value) is selectively applied to curved routes where it is more appropriate. This local quality approach minimizes false cancellation rates while maintaining ease of override where needed.
Data Source
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AI summary
A travel control method for a vehicle is provided, which includes autonomous steering control for autonomously controlling the steering of the vehicle. The travel control method includes: setting a plurality of cancellation thresholds corresponding to respective travel scenes, the cancellation thresholds being used for canceling the autonomous steering control and transitioning to the driver's manual operation; detecting a travel scene of the vehicle during execution of the autonomous steering control; extracting a cancellation threshold corresponding to the detected travel scene from among the plurality of set cancellation thresholds; and determining, based on the extracted cancellation threshold, whether or not to cancel the autonomous steering control and transition to the driver's manual operation.