Vehicle Flood Detection Using Wiper Data and Weather Information
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Solution Overview
Problem
Existing flood detection technologies face challenges in accurately identifying road flooding without relying on flood detection sensors, particularly due to variations in wiper speeds and rainfall estimation methods.
Innovation Solution
A flood detection system that utilizes plural kinds of running state data and weather information, including rainfall data, to identify flooding without a flood detection sensor, using a vehicle movement model derived from machine learning to predict physical quantities and improve accuracy through social networking service post information and weather data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a flood detection sensor is used to detect flooding of a road, then the detection accuracy is improved, but the device complexity and cost increase
Solution Approach 1:
The patent introduces an intermediary analysis system that processes multiple indirect data sources (wiper operation data, vehicle speed, acceleration, weather information, SNS posts) to infer flood conditions. This intermediary layer substitutes the need for direct flood detection sensors while maintaining reliable detection capability through multi-parameter analysis.
Solution Approach 2:
The patent replaces the mechanical/sensor-based direct detection approach with an information-processing system that analyzes behavioral data and weather information. Instead of using physical flood sensors, the system substitutes a computational model that processes indirect observations to determine flood presence.
2Ease of operation
If wiper speed and operation duration are used to estimate rainfall amount, then the measurement simplicity is improved, but the measurement precision deteriorates due to driver behavior variations
Solution Approach 1:
The patent merges multiple data sources including wiper operation data, vehicle speed, acceleration, weather information, and social networking service posts to compensate for the imprecision of single-source rainfall estimation. By combining these diverse inputs, the system achieves more accurate flood detection despite variations in driver behavior.
Solution Approach 2:
The patent makes the existing vehicle sensors (wiper motor, speed sensor, acceleration sensor) serve multiple functions: their primary functions remain unchanged, but they also contribute to flood detection by providing indirect rainfall and road condition information. This multi-functional use improves precision without adding dedicated flood detection hardware.
3Measurement precision
If multiple data sources and analysis methods are used to improve flood identification accuracy, then the measurement precision is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The patent utilizes data that is already being collected by the vehicle's existing systems for other purposes (wiper control, speed monitoring, navigation). These systems serve themselves by providing additional flood detection functionality without requiring separate dedicated hardware, thereby improving accuracy while limiting complexity growth.
Solution Approach 2:
The system performs preliminary data collection and processing by gathering wiper operation data, vehicle state information, and weather data that are already available or easily obtainable. By preparing this information in advance through normal vehicle operation, the system reduces the complexity of real-time flood analysis while maintaining high detection accuracy.
Data Source
AI summary
A flood detection device includes a detection result acquisition section, a weather information acquisition section and an identification section. The detection result acquisition section acquires a detection result that, on the basis of a plurality of kinds of running state data relating to running of a vehicle, detects flooding of a road on which the vehicle is running. The weather information acquisition section acquires weather information including at least one of rainfall information representing a measured rainfall amount in a region in which the vehicle is running or rainfall estimation information representing an estimated rainfall amount. The identification section uses the respective acquisition results of the detection result acquisition section and the weather information acquisition section to identify flooding of the road.