Real-Time Detection System for Road Roughness Based on Ultrasonic Technology

Area of Science:

• Engineering
• Materials Science
• Automotive Technology

Background:

• Intelligent connected vehicles and autonomous driving demand precise real-time road condition data.
• Traditional road detection methods have limitations in accuracy and real-time capability.
• Asphalt pavements are prevalent in urban environments, necessitating specific detection solutions.

Purpose of the Study:

• To develop an ultrasonic-based system for real-time road roughness detection on asphalt pavements.
• To establish a correlation between measured road roughness and the road friction coefficient.
• To provide reliable data for vehicle active safety systems and autonomous driving.

Main Methods:

• Utilized an ultrasonic transceiver module and hardware signal conditioning.
• Implemented MCU-based data processing with digital filtering and dual-parameter compensation (distance, temperature-humidity).
• Employed probabilistic statistical analysis and fuzzy inference to map echo signals to road roughness and friction coefficient.

Main Results:

• The system effectively suppresses noise and compensates for environmental interference.
• Achieved accurate real-time detection of road roughness with a relative error below 10%.
• Demonstrated a strong correlation between pavement roughness and friction coefficient on asphalt surfaces.

Conclusions:

• The proposed ultrasonic system offers a viable solution for real-time road roughness and friction coefficient estimation.
• The technology supports enhanced vehicle active safety and autonomous driving functionalities.
• Accurate road condition perception is critical for the advancement of future transportation systems.