Road Roughness Mapping Using Multi-Vehicle Sensor Fusion
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Solution Overview
Problem
Existing road surface evaluation systems rely on captured images, which can be affected by external environments such as weather, leading to inaccurate road surface condition evaluations.
Innovation Solution
A road surface evaluation apparatus that acquires driving information from multiple vehicles, including position, acceleration, image, and sound data, to evaluate road surface roughness and update roughness information stored in a memory, while accounting for external environment factors through weight adjustments and noise removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If captured images are used to evaluate road surface condition, then visual information is obtained, but evaluation accuracy deteriorates due to weather and environmental factors
Solution Approach 1:
The patent combines multiple data sources including captured images, acceleration data from multiple vehicles, and sound data to evaluate road surface condition. By merging these different types of information, the system compensates for the limitations of image-only evaluation, particularly under adverse weather conditions, thereby improving overall evaluation accuracy.
Solution Approach 2:
The patent introduces acceleration data and sound data as intermediary indicators that can reflect road surface condition without being directly affected by weather conditions in the same way images are. These intermediary data sources serve as reliable alternatives when image quality is compromised by environmental factors.
2Reliability
If data from multiple vehicles is collected and processed, then evaluation reliability is improved, but system complexity increases
Solution Approach 1:
The server performs multiple functions including data collection from multiple vehicles, data processing, road surface evaluation, and result distribution. By concentrating these functions in a centralized system, the patent achieves high evaluation reliability through multi-vehicle data while managing complexity through functional integration rather than distributed complexity.
Solution Approach 2:
The system automatically collects, processes, and evaluates data from multiple vehicles without requiring manual intervention. The server autonomously handles data aggregation, processing, and evaluation, reducing operational complexity while maintaining high reliability through consistent automated processing of multi-vehicle data.
Data Source
AI summary
A road surface evaluation apparatus includes a microprocessor and a memory connected to the microprocessor. The memory stores map information including roughness information indicating a roughness of a surface of a road, and the microprocessor is configured to perform: acquiring as driving information of a plurality of vehicles driving on the road, position information of the plurality of vehicles, acceleration information indicating accelerations of the plurality of vehicles, driving image information including a captured image of the surface of the road, and driving sound information indicating driving sound of the plurality of vehicles; evaluating the roughness of the surface of the road based on the driving information of the plurality of vehicles; and updating the roughness information corresponding to the road stored in the memory based on an evaluation result in the evaluating.