Road Roughness Estimation Using Vehicle Vibration and GPS Data
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Solution Overview
Problem
Existing methods for monitoring road surface roughness are costly and inaccessible to local agencies, limiting their ability to make informed maintenance decisions and quantify environmental impacts such as fuel consumption and greenhouse gas emissions.
Innovation Solution
A method utilizing ubiquitous sensing and communication technology to collect and analyze acceleration and geolocation data from vehicles, employing a probabilistic inverse analysis framework to estimate road surface roughness and vehicle properties without the need for expensive instrumentation, enabling real-time, cost-effective monitoring of road quality and environmental impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser instrumented cars are used to measure road roughness PSD, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces complex optical/laser measurement systems with a mechanical vibration-based approach. A simple accelerometer mounted on the vehicle measures suspension vibrations, which are then used to infer road roughness characteristics. This substitution of measurement methodology dramatically reduces device complexity while maintaining measurement capability through indirect sensing of road conditions via vehicle response.
Solution Approach 2:
Instead of directly measuring road surface profile with complex instruments, the system copies the road roughness information through measurement of vehicle suspension vibrations. The accelerometer measures the vehicle's dynamic response to road inputs, creating a copied representation of road conditions that can be processed to extract roughness PSD without requiring direct road contact measurement devices.
2Area of stationary object
If laser instrumented cars are deployed for road monitoring, then measurement coverage is improved, but cost increases making it unaffordable for local agencies
Solution Approach 1:
The patent employs inexpensive accelerometers and standard data logging equipment that can be easily deployed on multiple vehicles. These low-cost sensing units can be installed on everyday vehicles without special instrumentation, enabling widespread deployment across many locations. The system trades the use of expensive, durable laser instruments for cheap, easily replaceable sensors that achieve broader coverage through quantity rather than individual sophistication.
Solution Approach 2:
The measurement system is designed to be universally applicable to any vehicle type using standard accelerometers and GPS devices. The same basic setup can be deployed on cars, trucks, and other vehicles to collect road condition data across diverse routes and terrains. This universal approach eliminates the need for specialized expensive equipment while achieving comprehensive spatial coverage through multiple ordinary vehicles.
3Ease of operation
If qualitative road condition metrics are used, then ease of operation is improved, but measurement precision and quantitative estimation capability deteriorate
Solution Approach 1:
The system transforms raw acceleration time-series data into power spectral density (PSD) parameters that quantitatively characterize road roughness across different spatial frequencies. By changing the parameter representation from simple qualitative descriptors to spectral parameters (PSD values at different wavelengths), the system enables precise quantitative assessment while maintaining operational simplicity through automated processing pipelines that handle the mathematical transformations.
Solution Approach 2:
The patent introduces an intermediary processing layer that converts complex vibration signals into meaningful road condition parameters. The accelerometer raw data passes through spectral analysis and PSD calculation intermediaries before becoming interpretable road roughness metrics. This intermediary processing chain bridges the gap between simple measurement and complex quantitative analysis, maintaining ease of operation while achieving measurement precision.
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 approach provides accurate, low-cost monitoring of road quality and environmental impact, increasing measurement coverage and reducing costs, making it suitable for local agencies, industries, and transportation companies to optimize maintenance and fuel efficiency.
Implementation Method 1
receiving, by a server over a network, driver data for a road segment from one or more sensing units in one or more vehicles
Data Source
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AI summary
A method of monitoring quality of a road segment from driver data is provided. The method includes receiving, by a server over a network, the driver data for a road segment from one or more sensing units in one or more vehicles. The method also includes calculating, in one or more computing devices, one or more quantitative pavement surface characteristics of the road segment from the driver data using a probabilistic inverse analysis framework. The method also includes identifying, in the one or more computing devices, one or more quantitative vehicle properties of the one or more vehicles from the driver data using the probabilistic inverse analysis framework. The method then includes estimating, in the one or more computing devices, one or more road quality characteristics of the road segment based on at least one of the quantitative pavement surface characteristics of the road segment and the quantitative vehicle properties of the one or more vehicles.