Intersection Turn Path Averaging from Telematics Data
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Solution Overview
Problem
Current methods struggle to accurately determine vehicle paths through intersections using telematics data due to variations in intersection geometry and vehicle maneuvers, such as U-turns or turns into parking lots, without relying on pre-defined road data.
Innovation Solution
A method involving telematics data processing to isolate and simplify vehicle path data, calculate geometric median points, and generate an average spatial path by joining these points, excluding outliers based on spatial and angular thresholds, to define a refined vehicle turn path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed vehicle path data from multiple vehicles is collected and processed to determine accurate turn paths through intersections, then measurement precision of vehicle paths is improved, but loss of time for data processing increases
Solution Approach 1:
The patent segments the raw telematics data processing into distinct phases: data collection from multiple vehicles, spatial filtering to identify vehicles actually turning through the intersection, path simplification using geometric median calculations, and average path generation. This segmentation allows efficient processing by focusing computational resources on relevant data subsets rather than processing all raw data points uniformly.
Solution Approach 2:
The patent extracts only the spatial data points that are actually relevant to determining turn paths through the intersection, filtering out data from vehicles that do not make the turn (such as U-turns or turns into adjacent properties). This extraction process removes unnecessary data before processing, significantly reducing computational time while maintaining measurement precision for the actual turn paths.
2Reliability
If telematics data from multiple vehicles is processed to account for variations in intersection geometry and vehicle maneuvers, then reliability of path determination is improved, but device complexity increases
Solution Approach 1:
The patent uses feedback mechanisms where the system continuously refines the average turn path by comparing individual vehicle paths against the emerging average. Vehicles whose paths deviate significantly from the average (indicating U-turns or wrong maneuvers) are identified and excluded from further averaging. This feedback loop improves reliability by iteratively filtering out incorrect data while the computational complexity remains manageable through the use of straightforward geometric median calculations.
3Productivity
If spatial data points are simplified by reducing the number of points while maintaining path accuracy, then productivity of path determination is improved, but manufacturing precision of the path representation is worsened
Solution Approach 1:
The patent changes the parameter representation of vehicle paths by transforming detailed chronological spatial data points into a simplified geometric median representation. Instead of maintaining all original data points, the system calculates geometric medians at key positions along the path, creating a condensed representation that captures the essential turn geometry. This parameter transformation achieves both productivity improvement through reduced data volume and maintains manufacturing precision by preserving the core path characteristics.
Data Source
AI summary
Techniques for collapse of driving data to determine spatial averages of vehicle paths determining a spatial average vehicle path through a turn of within an intersection from a plurality of vehicles are provided. The telematics data may include plurality of spatial data points for each respective vehicle trip. Spatial data points associated with the turn of interest from each respective vehicle may be isolated and ordered chronologically, and converted into respective lines. A number of equally spaced points may be placed along each respective line, and a number of geometric median points may be determined by averaging each of the points along each of the respective lines. An average simplified line representing the spatial average vehicle path through the turn of the intersection may be generated based on the number of geometric median points.