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

With the rapid development of intelligent connected vehicles and autonomous driving, real-time and accurate road condition perception has become increasingly critical. Aiming at the limitations of traditional direct and indirect detection methods, this paper proposes an ultrasonic-based real-time detection system for road roughness. Most urban roads today feature asphalt pavements; therefore, this system focuses its research on asphalt pavements. Under the same pavement type (asphalt roads), there is a strong correlation between pavement roughness and the friction coefficient. By measuring the roughness of different pavements, the friction coefficient is estimated using the fuzzy processing method. Then the system through measuring ultrasonic echo amplitude and sensor-road distance, combined with software digital filtering, dual-parameter compensation (distance and temperature-humidity), probabilistic statistical analysis, and fuzzy inference, the mapping relationship among echo signals, road roughness and friction coefficient is established. The system mainly includes an ultrasonic transceiver module, a hardware signal conditioning module, and an MCU-based data processing, display and transmission module. Both simulated experiments and real asphalt pavement tests are carried out for verification. The results show that the system can effectively suppress noise, compensate distance attenuation and environmental interference, and achieve accurate real-time detection of road roughness, with a relative error less than 10% compared with the reference value. The proposed system can provide reliable data support for vehicle active safety systems and autonomous driving applications.