Traffic Lane Boundary Identification Using Frequency Span Analysis
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Solution Overview
Problem
Existing radar microwave technologies face challenges in accurately and flexibly identifying traffic lane boundaries due to interference from adjacent lanes, leading to inaccuracy and inefficiency in calculating lane width.
Innovation Solution
The method involves receiving and processing microwave signals using Fourier Transformation to generate frequency span information, applying a probability density function model, and employing a revised Gaussian Mixture Model for automatic learning to determine lane boundaries, reducing errors and improving calculation speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If radar microwave detector is used to count vehicles in multiple lanes, then vehicle detection capability is improved, but lane boundary identification accuracy deteriorates due to microwave reflection from adjacent lanes
Solution Approach 1:
The patent divides the frequency domain into multiple frequency spans, each corresponding to a specific lane. By segmenting the frequency information and associating it with spatial positions, the system can distinguish vehicles in different lanes even when microwave reflections occur, thus maintaining vehicle detection capability while improving lane boundary identification accuracy
Solution Approach 2:
The patent introduces frequency span information as an intermediary between vehicle detection and lane boundary identification. This frequency-based intermediary allows the system to map detected vehicles to specific lanes without direct spatial measurement, resolving the interference from adjacent lane reflections
2Ease of manufacture
If fixed lane width assumption is used for lane identification, then calculation simplicity is improved, but adaptability to different lane configurations deteriorates
Solution Approach 1:
The patent makes the lane width parameter dynamic by allowing it to be adjusted based on the detected frequency span information. Instead of using a fixed lane width, the system calculates the actual lane width from the frequency distribution of detected vehicles, enabling adaptation to different lane configurations while maintaining calculation efficiency
Solution Approach 2:
The patent changes the lane width from a fixed parameter to a variable parameter that is determined by the frequency span analysis. This parameter change allows the system to adapt to different lane widths and configurations while keeping the overall calculation process simple and efficient
3Device complexity
If single point position is used to represent vehicle position, then data processing simplicity is improved, but calculation accuracy deteriorates
Solution Approach 1:
The patent transitions from representing vehicle position as a single point in space to representing it as a frequency span in the frequency domain. This dimensional change from spatial point to frequency interval provides more information about vehicle position and lane boundary without significantly increasing data processing complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables faster and more accurate identification of lane boundaries, reducing errors in unknown areas and providing correct lane width calculations, thus enhancing practical application efficiency and reducing costs.
Implementation Method 1
the voltage signal is used as input parameter, which is converted to frequency domain signal by Fourier Transformation further
Data Source
AI summary
The invention provides a method for identification of traffic lane boundary. Firstly the microwave signal is received, and the noise reduction is treated for the microwave signal. Then the frequency domain information is employed to calculate the legal set of closed interval, in order to form the frequency span information. Finally, the probability density function model is employed to calculate the frequency span information in order to identify the traffic lane boundary.