Traffic Incident Location Detection via Route Deviation Analysis
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Solution Overview
Problem
Current navigation systems lack the ability to accurately identify the location of incidents affecting traffic in real-time across multiple navigation devices, leading to inefficiencies in route deviation detection and traffic flow analysis.
Innovation Solution
A computer-based system that collects data from multiple navigation devices to determine portions of routes where deviations occur, identifying overlapping sub-portions to pinpoint the location of incidents affecting traffic by analyzing exit and return points and using thresholds to validate the significance of these deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If navigation systems collect and analyze data from multiple navigation devices to identify incident locations, then measurement precision of incident location is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The system segments the incident detection process into distinct functional modules: data collection from multiple navigation devices, route portion determination, sub-portion identification, and incident location identification. Each module handles a specific aspect of the analysis, reducing overall system complexity while maintaining high measurement precision through coordinated operation of these specialized components.
Solution Approach 2:
The system merges data from multiple independent navigation devices to collectively identify incident locations. By combining route deviation data, exit points, and return points from numerous devices, the system achieves high measurement precision for incident location identification that would be impossible with a single device, while the centralized processing architecture manages the complexity of integrating this multi-source data.
2Loss of information
If the system analyzes route deviations and determines overlapping sub-portions to identify incidents, then information completeness about traffic conditions is improved, but loss of time for data processing increases
Solution Approach 1:
The system performs preliminary actions by continuously collecting and storing route data, exit points, and return points from navigation devices before incidents occur. This pre-processing and organization of data allows for rapid incident location identification when deviations are detected, reducing the time required for analysis while maintaining complete traffic condition information through the accumulated data repository.
Solution Approach 2:
The system replaces manual or sequential analysis methods with automated computational processing. By using computer-based algorithms to automatically determine overlapping sub-portions and identify incident locations from the collected navigation data, the system minimizes data processing time while maintaining comprehensive traffic condition information that would be difficult to analyze through traditional methods.
3Reliability
If the system uses thresholds to validate deviation significance, then reliability of incident detection is improved, but measurement precision requirements increase
Solution Approach 1:
The system uses threshold parameters to validate the significance of route deviations and identify meaningful incidents. By establishing predetermined threshold values for deviation analysis, the system improves incident detection reliability by filtering out minor or insignificant deviations. The threshold mechanism works effectively with the accumulated precision from multiple navigation devices, where even moderate measurement precision across many devices achieves sufficient overall accuracy when combined with threshold-based validation.
Data Source
AI summary
In a method for identifying a location of an incident, a computer receives data from a plurality of navigation devices. The computer determines a portion of a determined route between a first point and a second point of at least one navigation device of the plurality of navigation devices, wherein the at least one navigation devices deviated from the determined route. The computer determines that two or more portions contain a sub-portion. The computer identifies a location of an incident, wherein the location is a location of the sub-portion.