FMCW Radar Vehicle Front Crossing Prediction
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Solution Overview
Problem
Existing methods for monitoring traffic violations using radar devices are less accurate when detecting vehicles approaching a stop line from the rear, as they rely on the rear of the vehicle passing the line, making it difficult to predict when the front of the vehicle will cross the stop line, especially with changing speeds and non-perpendicular lane directions.
Innovation Solution
A method employing an FMCW radar device positioned next to the roadway with a radar beam that covers the stop line, emitting radar radiation and measuring signals at multiple times to calculate the expected time of the vehicle's front crossing the stop line, taking into account changes in speed and lane direction, and triggering a camera to capture evidence if the violation occurs outside the green phase.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a rear-measuring radar device is used to detect vehicles approaching a stop line, then the monitoring coverage is improved, but the prediction accuracy of when the vehicle front will cross the stop line deteriorates
Solution Approach 1:
The radar system performs preliminary measurements of the rear of the vehicle at multiple positions before the vehicle reaches the stop line. By measuring the rear vehicle position and distance in advance at multiple points, the system can predict when the vehicle front will cross the stop line, compensating for the limited viewing angle of rear-measuring radar.
Solution Approach 2:
The system transitions from measuring only the rear vehicle position in a single dimension to predicting the vehicle front crossing time by incorporating multiple measurement dimensions. By taking measurements at multiple positions and times, the system creates a multi-dimensional dataset that enables accurate prediction of the vehicle front's position and crossing time despite using rear-measuring radar.
2Measurement precision
If multiple measurement times are used to track vehicle position, then the prediction accuracy is improved, but the measurement complexity and processing time increase
Solution Approach 1:
The system performs preliminary measurements at multiple fixed positions before the vehicle reaches the stop line. By establishing measurement points in advance and using predetermined calculation relationships between these positions, the system achieves accurate prediction without requiring complex real-time processing of continuous data streams.
Solution Approach 2:
The system dynamically selects and processes measurements based on the vehicle's approach to the stop line. Rather than continuously processing all possible measurements, the system adapts its measurement and processing strategy to the specific situation, optimizing the balance between accuracy and 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 method provides a more precise prediction of when the vehicle's front will cross the stop line, accounting for speed changes and lane deviations, ensuring accurate detection and documentation of traffic violations.
Implementation Method 1
an FMCW radar device is set up next to a roadway with a roadway edge and a traffic light area delimited by a stop line. The FMCW radar device is designed to emit radar radiation that forms a radar beam with a radar axis
Data Source
Figure 1a~1c
AI summary
The method involves triggering a camera (7) for producing photographic evidence, if an appropriate vehicle (3) outside of a green phase of a stop line (5) is at a photo line (10). The radial velocity of provisional expected time point at which front of appropriate vehicle crosses a stop line is calculated using path-time law based on vertical distance of stop line to a FMCW radar apparatus (1) and the setting up angle from specific position. The photo time point at which the vehicle front is located at the photo line is calculated from updated expectation time using path-time law.