Runway Condition Assessment Using Weighted Multi-Source Landing Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for determining runway conditions at airports are unreliable and imprecise, leading to subjective pilot reports, inaccurate friction measurements, and unnecessary runway closures, which impact airport operations and safety.
Innovation Solution
A method and system for determining runway conditions using a combination of data sources, including braking parameters from aircraft and ground-based sensors, with weighted data filtering and calculation to produce a reliable runway coefficient and confidence index, optimizing runway usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If test trucks are used to measure friction coefficients, then runway condition data can be collected, but the measurements are inaccurate and require runway closures
Solution Approach 1:
The patent replaces the mechanical test truck system with an optical measurement system using cameras and image processing. Instead of physical contact measurement that requires runway closure, the system uses visual data from aircraft landing rolls to infer friction coefficients, eliminating the need for mechanical testing equipment and runway shutdowns.
Solution Approach 2:
The system uses the aircraft's own landing roll data and visual information from cameras mounted on the aircraft or ground stations to measure runway conditions. The aircraft effectively measures the runway friction characteristics during its normal landing operation, without requiring separate test vehicles or runway closures.
2Loss of information
If radio reports from pilots are used, then runway condition information can be obtained, but the data is subjective and unreliable
Solution Approach 1:
The patent replaces subjective radio reports with objective optical measurement systems. Instead of relying on pilot memory and communication, the system uses cameras to capture visual evidence of runway conditions and image processing algorithms to objectively determine friction coefficients and contaminant presence.
Solution Approach 2:
The system continuously captures visual data during aircraft landing rolls and processes this information in real-time to provide objective feedback on runway conditions. This feedback loop uses the actual visual evidence from the landing process itself to determine runway status, rather than relying on pre-labeled or memory-based reports.
3Measurement precision
If buried sensors are used to detect contaminants, then runway condition data can be collected, but the measurements represent only a small sample area
Solution Approach 1:
The patent transitions from point-based measurements (single sensor location) to area-based measurements (multiple camera positions capturing extended runway sections). By using cameras positioned at multiple locations and capturing images during aircraft passes, the system measures contaminant distribution across the entire runway surface area rather than at isolated points.
Solution Approach 2:
The camera system serves multiple functions: it captures visual evidence of contaminants, measures friction coefficients through image analysis, and provides spatial distribution data across the runway. This multi-functional approach replaces multiple specialized sensors with a single versatile optical measurement system that covers the entire runway area.
4Reliability
If manual observations by runway inspectors are used, then runway condition assessment can be performed, but the process is time-consuming and subjective
Solution Approach 1:
The patent replaces manual visual inspection with automated optical measurement systems. Instead of inspectors physically walking the runway and taking notes, the system uses cameras and image processing algorithms to automatically detect contaminants, measure friction coefficients, and assess runway conditions continuously during aircraft operations.
Solution Approach 2:
The system provides continuous monitoring of runway conditions during aircraft landing rolls rather than periodic manual inspections. The optical measurement system operates continuously as aircraft use the runway, capturing data throughout the operational period without interruption, whereas manual inspection occurs only when inspectors are available and the runway is closed.
Data Source
AI summary
Said method for determining aircraft landing runway conditions comprises the steps of: acquiring a set of data groups of different types (D1, D2) for evaluating and monitoring runway degradation conditions; deriving weighting coefficients (Ki) from each data group; filtering the data; determining, for each data group, a partial runway condition; modifying the weighting coefficients of each data group; and combining the partial runway conditions to derive a runway condition coefficient (RWYCC) associated with a confidence index (C1) derived from the modified weighting coefficients.