Lane End Detection via Turn Signal Spatial Distribution Analysis
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Solution Overview
Problem
Current systems fail to accurately and efficiently update lane configuration information, such as the beginning or end of a lane, in real-time, especially in dynamic road conditions like construction sites or accidents, due to the lack of reliable lane-detection capabilities in typical vehicles.
Innovation Solution
A method utilizing statistical evaluations of turn signal activations from multiple vehicles to determine lane changes by analyzing spatial and temporal distributions of direction indicator data, transmitted to a central processing unit for updating digital road maps without the need for additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If typical automobiles are used for collecting lane configuration data, then the quantity of data sources increases, but the measurement precision deteriorates because few vehicles are equipped with sufficiently accurate and reliable cameras
Solution Approach 1:
The patent replaces optical sensing systems (cameras and image processing) with a behavioral signal-based system. Instead of mechanically/optically detecting lane markings, the system uses turn signal activations as indirect indicators of lane changes. This substitution allows typical vehicles without specialized sensors to contribute data, resolving the contradiction between quantity of sources and measurement precision.
Solution Approach 2:
The patent introduces turn signal activations as an intermediary signal that indirectly indicates lane configuration changes. Rather than directly detecting lanes, the system uses the driver's intentional signaling behavior as a mediator to infer lane ends and beginnings. This intermediary approach enables data collection from typical vehicles while maintaining reasonable accuracy through statistical analysis of activation patterns.
2Loss of information
If central databases are used to store lane configuration information, then the information can be distributed to vehicles, but the information becomes outdated quickly because temporary narrowing and lane closures are not stored in real-time
Solution Approach 1:
The patent implements a feedback mechanism where lane configuration data is continuously updated based on actual vehicle behavior observations. Turn signal activations from vehicles are fed back to the central server, which then updates the digital road map with observed lane ends and beginnings. This closed-loop feedback system ensures that the database remains current with real-time road conditions.
Solution Approach 2:
The system performs preliminary statistical analysis of turn signal patterns to identify potential lane configuration changes before they are formally recorded in the database. By analyzing spatial distributions and temporal patterns of activations, the system proactively detects lane ends and beginnings, updating the database in advance of when traditional methods would identify these changes.
3Device complexity
If statistical evaluations of turn signal activations are used to detect lane ends, then the device complexity is reduced by using existing vehicle technology, but the difficulty of detecting and measuring increases due to the need for sophisticated spatial and temporal analysis
Solution Approach 1:
The patent transforms the detection problem from spatial analysis (detecting lane markings in images) to temporal-spatial pattern recognition (analyzing turn signal activation distributions). By adding the temporal dimension of activation timing and the spatial dimension of location data, the system converts a visually complex problem into a statistically tractable one, reducing device complexity while managing detection difficulty through multidimensional analysis.
Data Source
Figure 1
AI summary
The invention relates to a method for detecting the end of a lane, comprising: receiving activation notices from vehicles; wherein the notices comprise data regarding the location of the vehicle at which the turn signal of the vehicle is activated; calculating spatial distributions for the location data; detecting the end of a lane on the basis of the distributions.