Verifying Road Traffic Designations Using Mobile Location Data
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Solution Overview
Problem
Existing computer-implemented geographic maps face difficulties in accurately determining whether a road is one-way or two-way, which affects the accuracy of driving routes and confuses users.
Innovation Solution
A method and system that utilize location data points with headings and speeds to associate and count data points in specific directions, determining the traffic direction of a road and comparing it to existing designations to identify conflicts, such as missing, unlikely, or incorrect one-way designations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing geographic map data is used to determine road traffic designation, then the system is simple to operate, but the measurement precision of traffic direction is insufficient
Solution Approach 1:
The patent introduces location data from mobile devices as an intermediary to verify road traffic designations. This intermediary data source provides independent evidence (headings and speeds of moving objects) that mediates between the existing map data and the actual traffic conditions, enabling more accurate verification without requiring direct intervention in the map data structure itself.
Solution Approach 2:
The system implements a feedback mechanism where location data from mobile devices is analyzed to determine actual traffic directions, which then feeds back to verify and potentially correct the stored traffic designations in the geographic map. This closed-loop feedback enables continuous improvement of data accuracy by comparing expected vs. observed traffic patterns.
2Reliability
If traffic designation verification is performed using location data, then the reliability of route information is improved, but the loss of time for data processing increases
Solution Approach 1:
The patent applies partial action by selectively verifying only those road segments where conflicts are detected between stored traffic designations and observed location data patterns. Rather than processing all road data universally, the system focuses computational resources on specific areas where verification is needed, reducing overall processing time while maintaining reliability where it matters most.
Solution Approach 2:
The system performs preliminary filtering and association of location data points with road segments before conducting the actual traffic direction analysis. By pre-organizing and validating the location data structure in advance, the system reduces the computational burden during the conflict detection phase, thereby reducing overall processing time while maintaining thorough verification.
3Manufacturing precision
If manual verification of road traffic designations is performed, then the manufacturing precision of map data is improved, but the productivity of map maintenance decreases
Solution Approach 1:
The system implements self-service by automatically analyzing location data from mobile devices to detect and flag potential traffic designation errors. Instead of requiring manual review of all road segments, the system autonomously identifies conflicts between stored designations and observed traffic patterns, enabling map data to essentially verify itself without continuous human intervention.
Solution Approach 2:
The automated verification system creates a feedback loop where location data continuously monitors traffic patterns and automatically reports discrepancies to map maintenance systems. This feedback mechanism enables rapid identification of errors without manual inspection, maintaining high map data accuracy while significantly improving maintenance productivity through automated error detection and reporting.
Data Source
AI summary
Provided are systems, methods, and computer-readable for verifying the traffic designations of roads of a geographic map. Location data for a geographic area is obtained and location data points are filtered based on speed. A road network for the geographic area is obtained, and location data points are associated with a road based on proximity and heading with respect to the orientation of the road. The associated location data points in each direction are counted and used to determine a traffic direction. The traffic direction is compared to the existing traffic designation for the road, and conflicts are identified, such as missing one-way designations, unlikely one-way designations, and incorrect one-way designations.