Pavement Image Analysis for Automated PASER Rating Accuracy
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Solution Overview
Problem
Existing PASER ratings for road conditions are generated through visual inspection, requiring human intervention and are not amenable to automated assessment.
Innovation Solution
A computer-implemented method processes image data from vehicle cameras to identify road irregularities, estimate physical parameters, calculate actual locations, and generate Pavement Surface Evaluation and Rating (PASER) reports with minimal human input, associating features-of-interest with road segments and calculating PASER estimation values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automated image processing is used to generate PASER reports, then productivity and automation extent are improved, but measurement precision and reliability may deteriorate due to lack of human visual assessment
Solution Approach 1:
The patent replaces the mechanical human visual inspection system with an automated computer vision system. Image data captured by vehicle cameras is processed through algorithms that automatically identify road features, calculate PASER ratings, and generate reports, eliminating the need for human drivers to visually assess road conditions while maintaining assessment accuracy through computational methods
Solution Approach 2:
The system creates digital copies of road conditions through image data captured by cameras mounted on vehicles. These image copies are then processed and analyzed by computer algorithms to determine PASER ratings, allowing repeated measurements and analyses of the same road segments without requiring repeated human inspection
2Measurement precision
If manual windshield survey methods are used, then measurement precision is maintained through human visual assessment, but productivity and time consumption increase
Solution Approach 1:
The patent substitutes the manual human visual inspection process with automated image processing systems. Cameras mounted on vehicles capture road images that are automatically analyzed by computer algorithms, enabling rapid processing of large amounts of road data and generation of PASER reports without the time constraints of manual survey methods
Solution Approach 2:
The system enables continuous capture and processing of road image data as vehicles traverse the road system. Image data is continuously collected, processed, and analyzed in real-time or near-real-time, allowing for continuous monitoring and rapid generation of PASER reports without the interruptions and time delays inherent in manual survey methods
3Productivity
If multiple vehicle cameras are used to collect road data, then productivity and coverage area are improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent divides the road system into multiple segments and assigns different vehicles to survey specific segments. Each vehicle is equipped with cameras that capture images of their designated road segments, allowing parallel processing and data collection across multiple locations simultaneously. The system then integrates data from all vehicles to generate comprehensive PASER reports for the entire road system
Solution Approach 2:
The system uses standard vehicle cameras and existing GPS technology for data collection, making the solution broadly applicable to various vehicle types and road conditions. The image processing algorithms are designed to handle different road surface types, lighting conditions, and camera configurations, allowing the same system to operate across diverse environments without requiring specialized equipment for each scenario
Data Source
AI summary
A computer-implemented method is provided for processing image data to generate a Pavement Surface Evaluation and Rating (PASER) report for a road system. The method comprises: collecting road data including a plurality of road images; identifying a plurality of features-of-interest based on the plurality of road images, each of the features-of-interest being a road irregularity in the road system; estimating one or more physical parameters of the features-of-interest based on the road images; calculating an actual location for each of the features-of-interest based on the road data; uniquely identifying all of the features-of-interest and eliminating duplicate occurrences of a same feature-of-interest in the features-of-interest based on the road data and the actual locations of the features-of-interest; and identifying a corresponding road position for each feature-of-interest based on the road data and the actual locations of the features-of-interest.