Dynamic Obstruction Map Layer Using Vehicle Behavior Signals
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Solution Overview
Problem
Existing systems for detecting temporary dynamic obstructions in road networks, such as snow mounds, are resource-intensive and prone to errors, leading to incorrect notifications and increased traffic risks due to the reliance on image analysis and constant use of image sensing devices.
Innovation Solution
An apparatus and method utilizing vehicle and driver behavior data, combined with contextual data like image and weather data, to determine the likelihood and validate the existence of temporary dynamic obstructions, updating a map layer with confidence values to accurately indicate obstruction presence without continuous image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image sensing devices and image analysis are used to detect obstructions, then detection capability is improved, but computational resource consumption increases
Solution Approach 1:
The patent introduces an intermediary indicator variable that mediates between image analysis results and obstruction notifications. Instead of directly notifying obstructions from image analysis, the system first updates the indicator variable with confidence values, which then triggers notifications only when thresholds are met. This intermediary layer reduces unnecessary notifications and computational overhead while maintaining detection accuracy.
Solution Approach 2:
The system changes the parameter representation from raw image data to processed indicator variables with confidence values. By transforming the detection output into a standardized parameter format that can be accumulated and thresholded, the system reduces computational resource requirements for continuous image analysis while maintaining effective obstruction detection.
2Measurement precision
If image analysis is performed continuously to detect obstructions, then detection accuracy is improved, but system reliability decreases due to errors
Solution Approach 1:
The system performs preliminary actions by continuously updating the indicator variable with confidence values from multiple image analyses before triggering a notification. This preliminary accumulation of evidence ensures that notifications are only generated when the obstruction detection confidence consistently exceeds thresholds, reducing false positives and improving notification reliability.
Solution Approach 2:
The system implements feedback mechanisms where image analysis results feed into the indicator variable, which then determines whether notifications are triggered. The feedback loop continuously monitors confidence values and adjusts notification decisions accordingly, improving reliability by filtering out erroneous detections that don't meet sustained confidence thresholds.
3Speed
If image sensing devices are used constantly to monitor obstructions, then real-time detection is improved, but resource consumption increases
Solution Approach 1:
The system employs periodic action by updating the indicator variable at regular intervals based on image analysis results, rather than continuously triggering notifications. The periodic updates to the indicator variable allow the system to maintain real-time awareness of obstructions while reducing computational energy consumption by only processing notifications when threshold conditions are met.
Data Source
AI summary
An apparatus, method and computer program product provide a map layer of one or more temporary dynamic obstructions. For example, the apparatus is configured to receive vehicle/driver behavior data associated with a vehicle at a portion of a road, determine a likelihood of a temporary dynamic obstruction existing proximate to the portion based on the vehicle behavior data, and update a datapoint of a map layer based on the likelihood. The datapoint indicates a state of existence of the temporary dynamic obstruction at the portion.