Over Axle Weight Vehicle Detection Using Multi-Sensor Segmentation
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Solution Overview
Problem
Existing systems for detecting over axle weight vehicles on highways struggle to accurately record the front image of vehicles violating weight regulations due to interference from other vehicles and varying geometrical conditions, leading to incorrect identification and missed images of over axle weight vehicles.
Innovation Solution
A system comprising an axle weight detecting apparatus, a sensor, and a camera unit, with an over axle weight vehicle candidate extracting section that determines the correct vehicle by analyzing detection signals and vehicle characteristics, such as license plate types and heights, to ensure accurate identification and image capture of over axle weight vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single sensor is used to detect vehicle presence, then the system structure is simple, but the accuracy of identifying the correct over axle weight vehicle is poor due to interference from other vehicles
Solution Approach 1:
The single sensor is divided into multiple sensors (first sensor and second sensor) positioned at different locations. The first sensor detects vehicle presence at a first position, and the second sensor detects vehicle presence at a second position downstream. This segmentation allows the system to track vehicle sequences and accurately identify which vehicle corresponds to the over axle weight detection, resolving the identification accuracy problem while maintaining reasonable system complexity.
2Adaptability or versatility
If the detection position is fixed, then the system configuration is simple, but the system cannot adapt to varying geometrical conditions and vehicle types
Solution Approach 1:
The system uses multiple sensors at different positions that can detect vehicles dynamically as they pass through the detection zone. The axle weight detecting apparatus is positioned at a specific distance from the second sensor to account for vehicle length variations. This dynamic detection approach allows the system to adapt to different vehicle types and geometrical conditions without requiring complex reconfiguration, as the multi-sensor setup naturally captures vehicles of varying lengths and configurations.
3Reliability
If the camera is positioned far from the axle weight detecting apparatus, then there is less interference from other vehicles, but the probability of capturing the front image of the over axle weight vehicle decreases
Solution Approach 1:
The first sensor is positioned upstream to detect vehicle presence before the axle weight detecting apparatus. When the first sensor detects a vehicle, the system prepares to monitor the subsequent axle weight detection. This preliminary detection allows the system to anticipate which vehicle will be detected by the axle weight apparatus, enabling accurate identification and reliable front image capture while maintaining appropriate camera positioning that balances interference reduction with image capture probability.
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
The system significantly increases the probability of recording the front image of over axle weight vehicles by accurately identifying and differentiating between vehicles based on their characteristics, reducing incorrect recordings and ensuring compliance with weight regulations.
Implementation Method 1
The sensor S is a vehicle detecting apparatus that includes, for example, a pair of a phototransmitter and a photoreceiver. The sensor S detects the presence or absence of the vehicle at the detection position defined by the line determined to vertically intersect the traffic flow direction of the lane 1.
Data Source
AI summary
A technique for recording the front image of vehicles which violate the regulation in the axle weight is desired. In general, the weight of the leading axle cannot be excessively heavy, so that the over weight axle is a second or more rear side axle. Further, the distance between an axle weight detector and a vehicle detector for taking a vehicle image is normally below 8 meters. Under these conditions, when the over weight axle is detected, the over axle weight vehicle is predicted to be a vehicle being presently detected, a vehicle to be detected next, or next to the next. From the images of those vehicles, vehicles having no possibility of violating the axle weight regulation are eliminated based on a license plate read from the vehicle image or the measured vehicle height. The images not eliminated are stored as over axle weight vehicle images.