Road Segment Difficulty Scoring for Curved Route Navigation
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Solution Overview
Problem
Current map representations of roadways, which use lines to approximate road geometries, fail to convey information about the severity of turns and curves, leading to inadequate information for drivers and automated driving systems, resulting in increased stress and complexity in navigation.
Innovation Solution
A point-based approach is used to dynamically assess roadway curvature by representing routes as minimal sets of points, analyzing segment characteristics such as expected vehicle speeds and road types, and determining point densities to identify curves and assign difficulty indicators, which are then provided to drivers and automated systems through alerts and trajectory adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex algorithms such as splines or other mathematical approximations are applied to estimate roadway geometries, then measurement precision of roadway curvature is improved, but device complexity and computational intensity increase
Solution Approach 1:
The patent uses simple point-based representations instead of complex continuous curve models. Each point contains minimal geometry information, and these lightweight point objects are processed efficiently by the curvature estimation module to derive roadway characteristics without requiring heavy computational resources for maintaining complex geometric models
Solution Approach 2:
The patent replaces traditional mechanical/mathematical approximation methods (splines, polynomial fitting) with a machine learning-based curvature estimation approach. The ML model is trained offline to learn the relationship between point patterns and curvature characteristics, enabling real-time curvature estimation during navigation without executing complex mathematical algorithms
2Loss of information
If detailed line-based map representations are used to represent roadways, then information completeness about road geometry is improved, but ease of operation for real-time navigation deteriorates
Solution Approach 1:
The patent extracts only the essential geometry information needed for curvature estimation from the full map data, representing roadways as sequences of points with minimal attributes (position, road type, speed limit). This extracted point-based representation retains sufficient information for the ML model to estimate curvature while being much more efficient for real-time processing during navigation
Solution Approach 2:
The patent segments the roadway representation into discrete point elements rather than continuous lines. Each point can be independently processed by the ML model, allowing for efficient batch processing and parallel computation of curvature estimates along the navigation route, improving real-time performance
3Device complexity
If minimal point-based representation of routes is used, then device complexity is reduced, but loss of information about roadway characteristics increases
Solution Approach 1:
The patent introduces a machine learning curvature estimation module as an intermediary between the simple point-based route representation and the navigation system. This ML intermediary learns to infer curvature characteristics from the minimal point data by analyzing patterns in point spacing and distribution, effectively bridging the information gap without requiring complex geometric computations
Solution Approach 2:
The patent performs preliminary training of the ML model offline using comprehensive roadway geometry data. During this preliminary phase, the model learns to map point-based representations to curvature characteristics. Once trained, the model can efficiently estimate curvature during real-time navigation using only the minimal point data, without needing access to detailed geometric information
Data Source
AI summary
Systems, methods, and other embodiments described herein relate to improving vehicle control in relation to curved roadways. In one embodiment, a method includes, in response to determining a route for a vehicle that is represented using points for navigating to a destination, identifying one or more curves along the route according to proximities of the points. The method includes generating difficulty indicators for respective ones of segments that include the one or more curves. The method includes providing the difficulty indicators as the vehicle encounters the respective ones of the segments that include the one or more curves.