Single-Loop Inductive Speed Estimation Using Signature Regressors
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Solution Overview
Problem
Existing single-loop inductive loop sensor systems require site-specific calibration and re-estimation for accurate vehicle speed estimation, which is not transferable to different locations with varying traffic conditions, especially under congestion or heavy truck traffic.
Innovation Solution
A system that calculates two regressors, the inverse of the duration and the slew rate, from vehicle signature data, using regression models specific to vehicle categories, eliminating the need for site-specific calibration and allowing for robust speed estimation across different locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional single-loop inductive loop sensor systems use aggregate traffic speed estimation methods, then traffic count and occupancy data can be obtained, but reliable speed estimates cannot be yielded under congestion or heavy truck traffic
Solution Approach 1:
The patent segments vehicles into different categories (e.g., passenger cars, trucks, buses) based on their signature characteristics. Each vehicle category has its own speed estimation model, allowing the system to handle different vehicle types appropriately. This segmentation enables reliable speed estimation under various traffic conditions including congestion and heavy truck traffic, where conventional aggregate methods fail.
Solution Approach 2:
The patent changes the estimation approach from using a single aggregate g-factor to using vehicle-category-specific g-factors and signature-based parameters. By adjusting the parameters according to vehicle category and traffic conditions, the system achieves reliable speed estimates across diverse scenarios including congestion and heavy truck traffic.
2Measurement precision
If site-specific calibration is performed for accurate speed estimation, then local accuracy is improved, but the system cannot be transferred to different locations with varying traffic conditions
Solution Approach 1:
The patent creates a universal speed estimation system that works across multiple locations and traffic conditions. By using vehicle signature characteristics and category-based modeling, the system achieves both local accuracy and transferability. The signature-based approach captures essential vehicle properties that are consistent across different locations, eliminating the need for site-specific calibration while maintaining measurement precision.
Solution Approach 2:
The patent uses vehicle signatures as a form of template or copy that represents vehicle characteristics. These signatures serve as universal identifiers that work across different locations, allowing the system to transfer speed estimation capabilities from one site to another without recalibration. The signature copying approach maintains local accuracy while enabling broad adaptability.
3Measurement precision
If double loop speed trap configuration is used, then point speed and effective vehicle length information can be provided, but most traffic detection stations are installed in single loop configuration
Solution Approach 1:
The patent extracts the speed and length estimation capability from the double-loop configuration and implements it using only a single loop sensor. By analyzing the inductive signature waveform characteristics, the system derives both point speed and effective vehicle length information that traditionally required two loops. This extraction principle maintains measurement precision while reducing device complexity to a single-loop configuration.
Solution Approach 2:
The patent replaces the mechanical/dual-sensor approach of double-loop speed traps with an electronic/signal-processing approach using single-loop signature analysis. Instead of using two physical loops to measure speed, the system uses signal processing of the inductive signature to derive speed and length information. This substitution maintains the precision of point speed measurement while simplifying the sensor configuration to a single loop.
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
Enables accurate vehicle speed estimation without the need for re-calibration or re-estimation, providing reliable estimates across varying traffic conditions and locations, using FHWA-defined vehicle categories for consistent grouping.
Implementation Method 1
Inductive Loop Detection (ILD) technology... the Inductive Loop Signature-based detector systems measure and output the inductance changes of the inductive loops. The series of inductance changes caused by a traversing vehicle produce a waveform output and is referred as inductive loop signature or inductive vehicle signature
Data Source
AI summary
A system and method are disclosed for using vehicle signature data from a single inductive loop sensor to estimate vehicle speed. Two regressors are calculated from the vehicle signature: the “inverse of the duration” and the “slew rate”. A point is found by normalizing the vehicle signature in amplitude and determining the earliest point in the normalized signature to cross a set threshold. The slew rate is the slope of the normalized vehicle signature at this point. Regression models are generated from empirical data for several vehicle categories. Using the regression model for the category of vehicle and the two regressors vehicle speed is estimated. The regression models have been demonstrated to be robust eliminating the need for site-specific calibration or estimation.