3D Road Geometry Estimation Using Fresnel Segment Modeling
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Solution Overview
Problem
Current road geometry estimation methods for autonomous vehicles rely on mathematical approximations that incur significant errors, which are not suitable for the high precision and safety-critical operations required in autonomous driving.
Innovation Solution
A system and method that utilize Fresnel integrals to accurately model road geometry, allowing for precise estimation of road curvature and heading, and extend this to 3D road geometry modeling by dividing roads into segments with uniform length, ensuring G2-continuity and minimal approximation errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mathematical approximations are used for road geometry estimation, then computation speed is improved, but measurement precision deteriorates due to significant approximation errors
Solution Approach 1:
The patent changes the mathematical parameters from standard polynomial approximations to Fresnel integrals with specific parameter transformations. This allows the system to maintain computational efficiency while achieving high precision in road geometry estimation by transforming the problem into a different mathematical domain where both speed and accuracy can be preserved.
Solution Approach 2:
The patent segments the road geometry into multiple road segments, each modeled independently using Fresnel integrals. This segmentation allows for localized high-precision modeling while maintaining overall computational efficiency through divide-and-conquer strategy, resolving the contradiction between detailed accuracy and computation speed.
2Measurement precision
If high precision road geometry modeling is implemented, then measurement precision is improved, but device complexity increases due to computational requirements
Solution Approach 1:
The patent uses Fresnel integrals as a mathematical copy or representation of the road geometry that can be computed efficiently. Instead of directly modeling complex real-world road variations, the system creates a simplified mathematical copy using Fresnel functions that preserves essential geometric features while reducing computational complexity.
3Ease of manufacture
If standard polynomial approximations are used, then ease of manufacture is improved, but manufacturing precision deteriorates due to approximation errors affecting autonomous vehicle safety
Solution Approach 1:
The patent substitutes traditional mechanical/mathematical approximation methods (polynomial fitting) with a different mathematical system based on Fresnel integrals. This substitution maintains the ease of implementation through standardized mathematical functions while dramatically improving the precision of road geometry modeling to meet safety-critical requirements.
Data Source
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AI summary
A system and method including identifying lane line data associated with a road within the sensor data; modelling a geometry of the road as a sequence of road segments, each road segment being defined by parameters including a curvature rate and a road grade rate; generating, based on a mathematical representation of the modelled road geometry, an approximation of each road segment; and generating, based on the generated approximation of each road segment, a three-dimensional representation of the road including the sequence of segments.