Adaptive Lane Keeping Control for Curved Roads
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Solution Overview
Problem
Existing vehicle vision systems lack an effective method to dynamically adjust lane boundary detection based on vehicle speed, leading to inadequate response times in preventing lane departures, especially when vehicles approach lane boundaries rapidly.
Innovation Solution
A vehicle vision system utilizing CMOS cameras and advanced algorithms, including Kalman Filters and Linear-Quadratic Regulators, to detect lane boundaries and adjust intervention intensity based on vehicle speed, providing initial hard corrections followed by softer adjustments to maintain lane position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the system uses a fixed threshold for lane boundary detection, then the system is simple to implement, but the response time is insufficient when vehicles approach lane boundaries rapidly
Solution Approach 1:
The patent applies dynamics by making the lane boundary detection threshold variable rather than fixed. The threshold dynamically adjusts based on vehicle speed - at higher speeds, the threshold increases to allow greater lateral deviation before triggering a warning, while at lower speeds, the threshold decreases for more sensitive detection. This speed-adaptive threshold mechanism resolves the contradiction by improving response appropriateness across different driving conditions without requiring an overly complex system architecture.
Solution Approach 2:
The system changes the detection parameter (lateral distance threshold) based on another parameter (vehicle speed). By establishing a relationship where the threshold parameter varies with speed parameter, the system achieves better response characteristics for rapid lane approaches at high speeds while maintaining sensitivity at lower speeds. This parameter coupling approach improves overall system performance without adding significant complexity.
2Reliability
If the system generates warnings earlier for rapid lane approaches, then lane departure prevention is improved, but false alarms may increase
Solution Approach 1:
The patent changes the detection threshold parameter based on vehicle speed to balance early detection with false alarm reduction. At high speeds, the system allows larger lateral deviations before triggering warnings, recognizing that minor deviations are less concerning at higher velocities. At lower speeds, the system becomes more sensitive. This adaptive parameter adjustment improves reliability by preventing actual lane departures while reducing false alarms that would occur with a fixed low threshold.
Solution Approach 2:
The system dynamically adjusts its sensitivity based on operating conditions (vehicle speed). Rather than using a static threshold that causes false alarms across all conditions, the dynamic threshold adapts to the current speed context, improving the signal-to-noise ratio for actual lane departure events and filtering out spurious detections that are more common at certain speeds.
3Measurement precision
If the system uses multiple cameras and complex algorithms, then detection accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing speed-threshold relationship data. Rather than performing complex real-time calculations for each frame, the system uses pre-established lookup tables or formulas that map vehicle speed to appropriate detection thresholds. This preliminary preparation reduces real-time processing requirements while maintaining high detection accuracy through the use of multiple cameras and sophisticated algorithms.
Solution Approach 2:
The system dynamically selects processing intensity based on operational needs. By using multiple cameras with different fields of view, the system can selectively process images from relevant cameras based on current driving conditions and speed, adjusting computational effort dynamically to balance accuracy with processing time constraints.
Data Source
AI summary
A vehicular lane keeping assist system includes a camera and a control having an image processor that processes image data captured by the camera to determine lane boundaries defining a traffic lane of a road traveled by the vehicle. The control adjusts control of steering of the vehicle responsive to determination that the vehicle is traveling along a curved section of the road traveled by the vehicle. The control controls steering of the vehicle at a first degree responsive to determination that the vehicle is at or near a determined first lane boundary of the traffic lane at an inboard region of the curved section of the road, and the control controls steering of the vehicle at a second degree responsive to a determination that the vehicle is at or near a determined second lane boundary of the traffic lane at an outboard region of the curved section of the road.