Road Closure Detection Using Probe Data Time Intervals
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Solution Overview
Problem
Conventional systems for detecting road closures in navigation networks rely on third-party data, which may not be accurate or up-to-date, leading to inefficiencies in routing and route planning.
Innovation Solution
A method and system that utilize positional data from multiple devices to determine the elapsed time since a device last passed on a navigable element, comparing it to an expected time interval between device detections to identify potential closures, thereby reducing false positives and providing accurate, real-time closure information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If third-party data is used to detect road closures, then the system complexity is reduced, but the accuracy and timeliness of closure information deteriorates
Solution Approach 1:
The system uses probe data from devices themselves (GPS coordinates, timestamps, device identifiers) to detect road closures, rather than relying on external third-party data sources. Each device contributes its own positional information, enabling the system to self-generate closure detection data from the collective movements of devices in the network.
Solution Approach 2:
The server acts as an intermediary that collects, processes, and analyzes probe data from multiple devices to detect road closures. Instead of devices directly communicating closure information or relying on external sources, the server mediates the data collection and analysis process, comparing expected versus actual device presence to identify closures.
2Ease of manufacture
If third-party data is used for road closure detection, then data collection is simplified, but the timeliness and reliability of information deteriorates
Solution Approach 1:
The system continuously collects probe data from devices as they move through the network, enabling real-time detection of road closures. Rather than periodic updates from third-party sources, the continuous stream of positional data allows the system to immediately detect when devices stop passing through a navigable element, ensuring timely closure information.
3Device complexity
If simple absence of probe data is used to detect closures, then the detection process is simplified, but false positives increase
Solution Approach 1:
The system uses feedback from multiple device detections to validate closure status. By comparing the actual probe data received against expected device presence patterns, and by requiring consistent absence across multiple devices before declaring a closure, the system reduces false positives while maintaining detection capability.
Solution Approach 2:
Instead of declaring a closure based on a single device's absence (minimum action), the system requires excessive verification by checking multiple devices and comparing against expected traffic patterns. This partial or excessive action of verifying closure status through multiple data points significantly reduces false positives.
Data Source
AI summary
A method of detecting the closure of a navigable element forming part of a network of navigable elements within a geographic area. A server obtains positional data relating to the movement of a plurality of devices along the navigable element with respect to time. The positional data is used to determine an elapsed time since a device was last detected on the navigable element, and the determined elapsed time is compared to an expected time interval between consecutive devices being detected on the navigable element. The navigable element is identified as being potentially closed, subject to one or more optional validation steps, when the determined elapsed time exceeds the expected time interval, e.g. by a predetermined amount.