Telematics Intersection Compression Using Ordinal Crossing Pairs
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Solution Overview
Problem
Conventional telematics systems face challenges in efficiently processing and analyzing large amounts of geospatial driving data, particularly when vehicles cross intersections multiple times, due to the inability to natively handle temporal data, leading to limitations in processing capacity and storage requirements.
Innovation Solution
The system compresses telematics data by representing it using simplified straight-line segments, combining temporal and spatial data to identify intersection crossings and directions, and assigns ordinals to virtual lines around intersections, allowing for efficient retrieval and analysis of data across entire cities or regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional telematics systems process large amounts of geospatial driving data, then comprehensive analysis capability is improved, but processing time and power consumption increase significantly
Solution Approach 1:
The patent segments the continuous geospatial trajectory data into discrete straight-line segments connecting sequential points. This segmentation transforms the data structure from a continuous stream requiring sequential processing into discrete, independently processable units, enabling parallel processing and significantly reducing overall processing time while maintaining comprehensive analysis capability.
Solution Approach 2:
The patent extracts only the essential geometric features (straight-line segments between sequential points) from the complex geospatial data, discarding redundant intermediate coordinate information. This extraction reduces data volume while preserving the critical spatial relationships needed for intersection analysis, thereby improving processing efficiency without sacrificing analytical completeness.
2Loss of information
If conventional telematics systems store detailed geospatial data for multiple intersection crossings, then data completeness is improved, but storage requirements increase
Solution Approach 1:
The patent creates a simplified geometric copy of the vehicle's path by representing it as a sequence of straight-line segments between sequential GPS points. This copied representation preserves the essential spatial information needed to identify and analyze intersection crossings multiple times, while requiring significantly less storage space than storing all original detailed coordinate data.
3Productivity
If spatial software processes temporal driving data, then intersection traversal analysis is improved, but system complexity increases
Solution Approach 1:
The patent introduces a dynamic temporal component to spatial data by associating timestamps with each straight-line segment. This dynamic element allows the system to process temporal driving data efficiently by enabling time-based queries and analyses (such as identifying multiple crossings of the same intersection) without requiring complex temporal-spatial database structures, thus improving analysis efficiency while controlling system complexity.
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.