Road Segment Width Detection Using Probe Data
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Solution Overview
Problem
Traffic-aware routing and navigation systems rely on outdated and inaccurate data for road conditions, leading to delayed adjustments and errors in navigation due to dynamic changes in traffic and road characteristics.
Innovation Solution
A method using real-time or near real-time probe data to automatically detect changes in road segment width by comparing width-defining portions of current probe data with historical data, employing clustering algorithms like k-means to identify and quantify width changes, and providing alerts or updates based on configurable thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual observation and reporting of changed traffic conditions and road characteristics is used, then observation errors may occur and response time is delayed, but system complexity and cost are reduced
Solution Approach 1:
The system uses probe data from vehicles themselves to automatically detect road segment width changes without requiring manual observation. The probe data includes lateral position information that self-reports road conditions as vehicles traverse them, eliminating human observation errors and providing immediate automated detection of road changes.
Solution Approach 2:
The patent replaces manual observation mechanisms with automated data processing using probe data from vehicle sensors. The system processes lateral position data from multiple probes to automatically calculate width-defining portions and detect changes, substituting human observation with computational analysis.
2Reliability
If expensive infrastructure like LIDAR systems is deployed to monitor road conditions, then measurement precision and reliability are improved, but system cost and device complexity increase significantly
Solution Approach 1:
The system uses existing probe data infrastructure that serves multiple purposes - vehicle navigation, traffic flow analysis, and road condition monitoring. The same lateral position data used for navigation purposes is also utilized to detect road segment width changes, eliminating the need for dedicated monitoring infrastructure like LIDAR systems.
Solution Approach 2:
Instead of deploying physical sensing infrastructure, the system creates a virtual model of road conditions by processing and analyzing copies of existing probe data. The width-defining portions are calculated from lateral position data that already exists in the probe data stream, creating a digital representation of road geometry without physical sensors.
3Measurement precision
If comprehensive probe data processing is performed to detect width changes accurately, then measurement precision is improved, but processing resources and computational load increase
Solution Approach 1:
The system extracts only the essential lateral position information from probe data that is needed for width detection, rather than processing all available probe data. By focusing on width-defining portions - specifically the lateral positions that define the boundaries of the road segment - the system achieves accurate detection with reduced computational overhead.
Solution Approach 2:
The patent applies partial action by processing only the subset of probe data that is necessary for width detection. Instead of analyzing all probe data points, the system identifies and processes only those data points that contribute to defining the road width boundaries, achieving sufficient precision with minimal processing effort.
Data Source
AI summary
A method, apparatus and computer program product are provided to automatically detect changes in width of road segments in real-time or near real-time using probe data, such as probe data collected from vehicle and/or mobile devices traveling along a road segment. Probe data collected in real-time or near real-time is partitioned in order to identify width-defining portions of the probe data. The width-defining portions may be representative of the laterally-extreme lanes of the road segment, such as the left-most lane and the right-most lane. The width-defining portions are compared to corresponding width-defining portions of historical probe data to determine measures indicative of whether a road segment has expanded or narrowed. Indications of detected segment width changes may be provided to drivers and/or other systems or users. For example, map data for the road segment may be updated to reflect a detected width expansion or narrowing of the road segment.