Environmental State Estimation via Multi-Vehicle Data Aggregation
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Solution Overview
Problem
Existing environmental state estimation methods for vehicles rely on information from a single vehicle, leading to potential accuracy deterioration due to abnormal values and limited data quality, which affects the precision of rainfall, flooding, and visibility state estimations.
Innovation Solution
An environmental state estimation device that aggregates data from multiple vehicles within a prescribed area, using statistical processing to filter and combine information from rain sensors, wheel speed sensors, and imaging devices to enhance accuracy, excluding data from vehicles in unfavorable conditions such as tunnels or with low image recognition rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If environmental state estimation is performed based on information from a single vehicle, then the system complexity is low, but the estimation accuracy deteriorates due to abnormal values and limited data quality
Solution Approach 1:
The patent combines environmental state information from multiple vehicles in the same area to perform estimation. The estimation unit aggregates data from rain sensors, wheel speed sensors, and imaging devices of multiple vehicles, then performs statistical processing to calculate average values and filter abnormal data, thereby improving estimation accuracy while distributing the sensing burden across multiple vehicles
Solution Approach 2:
The estimation unit acts as an intermediary that receives environmental state information from multiple vehicles, performs statistical processing and filtering, and generates the final estimation result. This intermediary processing layer enables accurate estimation by eliminating abnormal values and averaging data across multiple sources without requiring direct complex coordination between all vehicles
2Measurement precision
If data from all vehicles is used for estimation, then the data quantity increases, but abnormal values from vehicles in unfavorable conditions (tunnels, low visibility) deteriorate the estimation accuracy
Solution Approach 1:
The estimation unit extracts and excludes abnormal values from the dataset by identifying vehicles in unfavorable conditions (such as those in tunnels or with low image recognition rates) and removing their data from the statistical processing. This extraction of abnormal data ensures that only reliable information from vehicles in normal conditions contributes to the final estimation
Solution Approach 2:
The system changes the parameter of data reliability by introducing image recognition rates as a filtering criterion. Vehicles with image recognition rates below a threshold or those detected to be in tunnels are identified as having unreliable data, and their measurements are excluded from the averaging process, thereby maintaining high data quality
Data Source
AI summary
An environmental state estimation device according to one embodiment of the present disclosure includes an environmental state estimation unit configured to estimate an environmental state of a prescribed area, based on information regarding a surrounding environmental state acquired by a plurality of vehicles in the prescribed area. A method for environmental state estimation according to another embodiment of the present disclosure includes an estimation step of an environmental state estimation device estimating an environmental state of a prescribed area, based on information regarding a surrounding environmental state acquired by a plurality of vehicles in the prescribed area. An environmental state estimation program according to still another embodiment of the present disclosure causes an environmental state estimation device to execute an estimation step of estimating an environmental state of a prescribed area, based on information regarding a surrounding environmental state acquired by a plurality of vehicles in the prescribed area.