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Estimation of Water Depth on Road Surfaces Using Accelerometric Signals
Ebrahim Riahi1,2, Wiyao Edjeou2, Sébastien Buisson2
1TS2-LMA, Univ Gustave Eiffel, IFSTTAR, F-13300 Salon de Provence, France.
Sensors (Basel, Switzerland)
|November 26, 2022
Summary
Researchers explored using accelerometers to estimate road surface water depth. Accelerometer signals strongly correlate with water depth, offering potential for enhanced vehicle safety systems.
Area of Science:
- Road safety engineering
- Vehicle dynamics
- Sensor technology
Background:
- Accurate measurement of road surface water depth is crucial for vehicle safety, especially for advanced driver-assistance systems and autonomous driving.
- Traditional methods for water depth measurement can be impractical or unsafe for real-time road conditions.
Purpose of the Study:
- To evaluate the feasibility of using accelerometers to indirectly estimate water depths on road surfaces.
- To develop and validate a system for real-time water depth estimation using vehicle-mounted sensors.
Main Methods:
- An experimental study was conducted using a trailer with a wheel, towed by a van on a closed test track.
- Water was applied to the road surface, and accelerometers were mounted on the wheel arch to capture vibrations caused by water spray.
- High-speed cameras were used to visualize water flow and optimize accelerometer placement, and a filtering method was developed to remove noise from sensor signals.
Main Results:
- A strong correlation was identified between the mean amplitude of accelerometric signals and the actual water depths on the road surface.
- The developed filtering method effectively removed noise caused by trailer movement, improving signal quality.
- The influence of vehicle speed and road surface texture on the sensor signals was analyzed.
Conclusions:
- Accelerometers can effectively estimate road surface water depths indirectly through tire-induced vibrations.
- The developed system shows promise for enhancing passenger safety, particularly in the context of autonomous driving systems.
- Further research can explore real-world implementation and integration with vehicle control systems.
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