Lane Status Confidence Indicators Using Probe Data Clustering
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Solution Overview
Problem
Traffic routing and navigation systems lack detailed lane-level information for road segments, often relying on outdated, inaccurate, or user-inputted data for lane closures or shifts, which may not be provided in a timely manner to drivers.
Innovation Solution
A method and apparatus using probe data to determine lane status confidence indicators by clustering probe data based on lateral positional indicators, calculating statistical measures, and assessing the confidence in lane status predictions, such as lane closures or shifts, to decide whether to transmit alerts to drivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user input or integrated reporting systems are used to provide lane-level information, then the system can obtain lane closure or shoulder closure details, but the information may be outdated, inaccurate, and not provided in a timely manner
Solution Approach 1:
The system enables drivers to automatically contribute lane status observations through their probe data (GPS location, lateral positioning) without requiring manual reporting. Each driver's vehicle location data serves as an automated report, eliminating the delay between observing a lane closure and reporting it, while maintaining high accuracy through objective sensor data rather than subjective user input
Solution Approach 2:
The patent replaces the mechanical system of manual user input and administrator processing with an automated electronic system that collects probe data from vehicle sensors, processes lateral positioning information through algorithms, and automatically generates lane status alerts. This substitution eliminates human response time delays and improves both timeliness and accuracy
2Loss of information
If general segment information is provided to drivers, then the system can alert drivers to slowdowns, but the information is not specific to individual lanes or sides of the road segment
Solution Approach 1:
The system segments the road into individual lane-level units by analyzing lateral positioning data. Instead of treating the entire road segment as a single unit, the patent divides it into discrete lanes based on the lateral distance of probe data points from the road centerline, enabling lane-specific alerts while using the same probe data infrastructure
Solution Approach 2:
The patent adds a lateral dimension to the traditional longitudinal traffic flow analysis. By incorporating lateral positioning information (distance from road centerline) alongside longitudinal position data, the system can determine which specific lane a vehicle occupies and provide lane-level granularity without requiring additional sensors or infrastructure
3Productivity
If lane status predictions are transmitted to all drivers, then comprehensive alert coverage is achieved, but unreliable predictions may cause false alarms and reduce system credibility
Solution Approach 1:
The system implements a confidence indicator mechanism that provides feedback on the reliability of each lane status prediction before dissemination. By calculating confidence levels based on the number and consistency of probe data observations, the system can filter out unreliable predictions and only transmit alerts that meet a confidence threshold, maintaining both coverage and trustworthiness
Data Source
AI summary
A method, apparatus and computer program product are provided to determine lane status confidence indicators of lane status predictions such as closures and/or shifting. Lane statuses and corresponding confidence indicators are determined based on probe data, such as probe data collected from vehicle and/or mobile devices traveling along a road segment. Probe data may be partitioned into clusters and compared to partitioned subsets of the probe data. Cluster stability for the segment and corresponding lane status confidence indicators can be determined based on the comparison. Accordingly, determinations of whether to transmit predicted lane statuses to another system, service, and/or user device may be made.