Lane Obstruction Inference via Multi-Vehicle Position Data
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Solution Overview
Problem
Existing methods for detecting lane obstructions rely on direct observations and manual reporting, which are insufficient and can lead to increased risks due to obstructed views and limitations, failing to provide adequate information about latent aspects of the environment.
Innovation Solution
A system that aggregates position data from reporting vehicles to infer the presence of lane obstructions by analyzing patterns in the movements of surrounding vehicles, communicating warnings to oncoming vehicles through a cloud-computing system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If direct observations and manual reporting are used to identify lane obstructions, then the system simplicity is maintained, but the detection reliability and completeness deteriorate due to obstructed views and limitations
Solution Approach 1:
The patent combines observations from multiple reporting vehicles with the target vehicle's own observations to infer lane obstructions. By merging data from surrounding vehicles' sensors and positions, the system achieves more reliable obstruction detection than any single vehicle could accomplish alone, resolving the contradiction between reliability and complexity.
Solution Approach 2:
The patent introduces a cloud-based server as an intermediary that aggregates position data from multiple vehicles, processes this data to identify obstruction patterns, and provides inferred obstruction information back to vehicles. This intermediary enables reliable multi-vehicle collaboration without requiring direct complex peer-to-peer communication between all vehicles.
2Loss of information
If only individual vehicle observations are collected, then the data collection process is simple, but the information completeness about latent environmental aspects deteriorates
Solution Approach 1:
The patent merges position data from multiple reporting vehicles to create a comprehensive view of traffic patterns and latent environmental aspects. By combining observations from multiple sources, the system recovers information that would be lost if only individual vehicle data were used, addressing the information completeness issue.
Solution Approach 2:
The patent adds a temporal and spatial dimension to data collection by gathering position information from multiple vehicles across different locations and times. This multi-dimensional approach allows the system to infer latent environmental aspects that cannot be detected from a single vehicle's perspective alone.
3Productivity
If manual reporting methods are used, then the implementation cost is low, but the productivity and responsiveness in providing obstruction warnings deteriorates
Solution Approach 1:
The patent enables vehicles to automatically report their position data and receive obstruction warnings without manual intervention. The system self-services by continuously collecting data from reporting vehicles, processing it through pattern recognition algorithms, and providing real-time warnings, thereby achieving high productivity and responsiveness.
Solution Approach 2:
The patent implements a feedback loop where position data from reporting vehicles is continuously processed to identify obstruction patterns, and warnings are provided back to oncoming vehicles in real-time. This closed-loop feedback system enables rapid detection and response to lane obstructions, significantly improving productivity compared to manual reporting.
Data Source
AI summary
System, methods, and other embodiments described herein relate to identifying lane obstructions. In one embodiment, a method includes collecting, in an electronic data store, position data of surrounding vehicles observed by reporting vehicles that travel over a roadway segment. The method includes analyzing the position data to identify whether observed positions correlate with an obstruction pattern that is indicative of a lane obstruction in at least one lane of the roadway segment. The method includes, in response to determining the position data indicates the lane obstruction, providing a signal identifying the lane obstruction to oncoming vehicles of the roadway segment.