Curvature Value Detection Using Vehicle Trajectory Splines
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Solution Overview
Problem
Existing methods for determining curvature values in navigable paths rely on manual processes that are prone to errors and are not scalable, leading to inconsistent accuracy in ground truth data, which affects driver assistance systems and navigation services.
Innovation Solution
A method using high-quality real driving trajectory data collected by vehicles performing maneuvers, which associates position data with map data to generate smooth splines and calculate maximum curvature values, providing a more accurate and scalable solution for determining curvature values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to determine curvature values, then the process can be performed with simple equipment, but the accuracy and consistency of curvature data deteriorates
Solution Approach 1:
The patent replaces manual mechanical measurement methods with automated sensor-based data collection systems. Vehicles equipped with GPS receivers and sensors automatically collect position data during driving maneuvers, eliminating the need for manual measurement while significantly improving curvature data accuracy and consistency.
Solution Approach 2:
The system enables vehicles to automatically collect and contribute their own position data during normal driving operations. The vehicles self-service the data collection process by recording their trajectories and maneuvers, which are then aggregated to determine curvature values without requiring external manual intervention.
2Productivity
If manual measurement methods are used, then the equipment requirements remain simple, but the scalability of the process deteriorates
Solution Approach 1:
The patent creates a universal data collection system where vehicles perform multiple functions: they collect position data for curvature determination, contribute to mapping services, and provide traffic pattern information. This multi-functional approach increases productivity while the standardized system design manages complexity through reuse of common components.
Solution Approach 2:
The system merges data collection from multiple vehicles into a unified curvature determination process. By combining position data from many vehicles performing the same maneuver, the system achieves high productivity in curvature data collection while the centralized processing architecture manages complexity through aggregation and averaging of measurements.
3Reliability
If different sources and techniques are used to generate path curves, then data availability increases, but the consistency and reliability of curvature data deteriorates
Solution Approach 1:
The patent applies local quality by determining curvature values specific to each geographic location and maneuver type rather than using universal approximations. By collecting actual vehicle trajectory data for specific locations, the system achieves high reliability for ground truth curvature data while maintaining adaptability to different local conditions through location-specific measurements.
Solution Approach 2:
The system changes the fundamental parameter from approximate path curves to actual vehicle trajectory data. By measuring the true path followed by vehicles during maneuvers rather than relying on map approximations, the system improves reliability of curvature data while adapting to various data sources through standardized processing of position data from different vehicles and conditions.
Data Source
AI summary
Systems and methods for the detection and analysis of curvature data are described. A method includes: receiving position data of a vehicle turning maneuver along a portion of a roadway, where the position data includes measured position data collected by sensors of a vehicle while traversing the vehicle turning maneuver; associating the received position data with map data of the portion of the roadway; generating a spline based on the position data, the spline being a smooth curve representing the vehicle turning maneuver from a first road segment to a second road segment; identifying a segment of the spline containing a turning point of the vehicle turning maneuver, the turning point representing a change of a vehicle path from along the first road segment to along the second road segment; and determining a maximum curvature value for the identified segment of the spline.