Intersection-Based Telematics Compression for City-Scale Road Analysis
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Solution Overview
Problem
Conventional telematics data analysis methods are limited by the large volume of data generated, which restricts their ability to consider multiple roads and intersections simultaneously, and requires significant storage capacity, making them inefficient for comprehensive analysis.
Innovation Solution
The system compresses telematics data using GPS and sensor network information, representing geospatial data with fewer data points by identifying virtual lines and assigning ordinals to intersections, allowing for efficient retrieval and analysis of entire city networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional telematics data collection methods are used to record all GPS positions and sensor data, then complete driving behavior data is captured, but the data volume becomes excessively large requiring significant storage capacity
Solution Approach 1:
The patent extracts and stores only the essential features from complete telematics data - specifically intersection traversal events with ordinal pairs representing entry and exit roads. This selective extraction maintains the reliability of driving behavior analysis while dramatically reducing data volume by eliminating redundant GPS coordinates and sensor readings that do not contribute to intersection-level analysis
Solution Approach 2:
Instead of collecting all raw telematics data and then filtering for intersection events, the system inverts the approach by directly identifying and recording only intersection traversal events. The system processes GPS data to detect when vehicles enter and exit intersections, storing only these critical events with their ordinal representations, thereby achieving compression from the ground up
2Reliability
If all raw telematics data is stored for analysis, then comprehensive driving behavior information is available, but analysis of multiple roads and intersections simultaneously becomes computationally inefficient
Solution Approach 1:
The patent segments the continuous stream of telematics data into discrete intersection traversal events. By dividing the data into meaningful units (entries and exits at specific intersections with ordinal pairs), the system enables efficient processing and analysis of multiple roads and intersections simultaneously, as each segment can be independently analyzed and aggregated
Solution Approach 2:
The system transforms the parameter representation of telematics data from continuous GPS coordinates and sensor values to discrete ordinal pairs representing intersection sequences. This parameter transformation enables more efficient computational processing and storage while preserving the essential information needed for driving behavior analysis
3Measurement precision
If detailed GPS coordinates and sensor data are stored for each position, then precise driving behavior is recorded, but storage needs increase significantly
Solution Approach 1:
The patent creates a simplified copy or representation of the actual driving path by recording only intersection traversal events with ordinal pairs. Instead of storing every GPS coordinate along the entire route, the system captures the essential geometric information (which intersections were entered and exited in what sequence) in a compressed format that preserves measurement precision at the intersection level while reducing storage requirements
Data Source
AI summary
Example methods, apparatus, and articles of manufacture to capture and compress telematics data are disclosed herein. An example computer-implemented method, executed by a processor, to represent telematics data includes identifying, with the processor, a physical intersection of roads, identifying, with the processor, virtual lines crossing the roads, assigning, with the processor, ordinals to the virtual lines, representing, with the processor, a physical traversal through the physical intersection captured in first telematics data by a pair of the ordinals, and storing the pair of the ordinals in second compressed telematics data.