Lane Tracking With Adaptive Coordinates for Perpendicular Lanes
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Solution Overview
Problem
Existing lane tracking systems in vehicles are less effective when the lane orientation is perpendicular to the vehicle orientation, as they rely on the vehicle's coordinate system, which limits their ability to accurately detect and track lane lines in various orientations.
Innovation Solution
The system generates and updates a lane model using observation points from sensors, expressed in a lane-specific coordinate system that is transformed to maintain correspondence with the vehicle coordinate system, allowing for orientation-agnostic lane tracking. This involves processing sensor detections, determining if points pertain to an existing model, and updating or initializing a recursive least squares adaptive filter to adjust the lane model based on vehicle orientation changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a vehicle coordinate system is used for lane tracking, then the system is simple to implement, but it fails to accurately track lane lines when the lane orientation is perpendicular to the vehicle orientation
Solution Approach 1:
The system dynamically adapts the coordinate system based on lane orientation. Instead of using a fixed vehicle coordinate system, the system determines the orientation of lane lines and rotates the coordinate system to align with the lane direction, enabling accurate tracking in all orientations while maintaining computational efficiency through adaptive transformation.
Solution Approach 2:
The system changes the coordinate system parameters (rotation angle, orientation) based on the detected lane line orientation. By adjusting the coordinate system parameters to match the lane orientation, the system achieves accurate measurement in perpendicular and other orientations without requiring a completely different tracking approach.
2Measurement precision
If the lane model is updated frequently to maintain accuracy, then the tracking precision improves, but the computational load and processing time increase
Solution Approach 1:
The system performs periodic updates of the lane model at optimized intervals rather than continuously. By updating the lane model periodically based on accumulated observation points and significant changes in lane orientation, the system maintains accuracy while reducing unnecessary computational operations and processing overhead.
Solution Approach 2:
The system performs preliminary processing of observation points by accumulating and pre-processing detections before final lane model updates. This preliminary action prepares data in advance, allowing for more efficient batch processing and reducing the computational burden during critical tracking updates.
Data Source
AI summary
Systems and methods include obtaining observation points of a lane line using a sensor of a vehicle. Each observation point indicates a location of a point on the lane line. A method includes generating or updating a lane model with the observation points. The lane model indicates a path of the lane line and the lane model is expressed in a lane-specific coordinate system that differs from a vehicle coordinate system that is defined by an orientation of the vehicle. The method also includes transforming the lane-specific coordinate system to maintain a correspondence between the lane-specific coordinate system and the vehicle coordinate system based on a change in orientation of the vehicle resulting in a change in the vehicle coordinate system.