Scaling Historical Probe Data for Road Geometry Changes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Historical probe data associated with previous map versions becomes outdated due to changes in road geometry, leading to errors in predicting current traffic conditions when applied to new map versions, as it is prohibitive to update all archived data with each new map release.
Innovation Solution
A scaled model is generated based on historical traffic data from previous map versions, using a scaling factor to adjust predictions for current map versions, allowing for accurate determination of current traffic conditions by comparing scaled historical measures with current traffic measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If historical probe data is used with previous map versions, then traffic condition analysis can be performed, but prediction accuracy deteriorates due to road geometry changes
Solution Approach 1:
The patent applies parameter changes by transforming historical probe data through scaling factors that adjust traffic measures based on geometry changes between map versions. The scaling factor is calculated as the ratio of current geometry parameters to historical geometry parameters, thereby adapting historical data to current road conditions without requiring complete data re-collection
Solution Approach 2:
The patent introduces a scaling factor as an intermediary element that mediates between historical probe data and current traffic analysis. This scaling factor serves as a transformation coefficient that bridges the gap between outdated map geometry and current road geometry, enabling accurate predictions without direct updates to all historical data
2Measurement precision
If all archived historical probe data is updated to current map version, then prediction accuracy is improved, but processing time and cost increase prohibitively
Solution Approach 1:
The patent extracts only the essential geometry parameters from the complete map data that are necessary for calculating scaling factors. Instead of updating all historical probe data with the entire current map version, it selectively extracts and applies only the relevant geometric transformation parameters, significantly reducing processing requirements
Solution Approach 2:
The patent applies partial action by updating only the necessary scaling factors derived from geometry changes rather than comprehensively updating all historical probe data. This partial update approach achieves sufficient prediction accuracy improvement without the prohibitive time and cost of complete data re-processing
3Productivity
If historical models from previous map versions are applied to current map version, then processing efficiency is maintained, but prediction errors increase due to geometry changes
Solution Approach 1:
The patent applies dynamics by making the historical model adaptive through scaling factors that dynamically adjust traffic measures based on geometry changes. The model transitions from a static application of historical data to a dynamic system that automatically compensates for geometric differences between map versions, maintaining both efficiency and reliability
Data Source
AI summary
An apparatus receives instances of probe data each comprising location data. The apparatus identifies instances of probe data corresponding to a first traversable map element (TME) of a current map version based on the location data and the current map version. The apparatus determines a current traffic measure for the first TME based on the probe data. The apparatus determines a historical traffic measure corresponding to a second TME of a previous map version that corresponds to the first TME of the current map version and a scaling factor for the first and second TMEs. The apparatus determines a scaled historical traffic measure by applying the scaling factor to the historical traffic measure and compares the current traffic measure and the scaled historical traffic measure. Responsive to determining that the comparison does not satisfy a similarity threshold requirement, the apparatus generates updated map/traffic data for the first TME.