Real-Time Road Pothole Mapping Based on Vibration Analysis in Smart City

Abstract

Vehicle-road collaboration is inseparable for smart cities, and the potholes detection is an essential direction in vehicleroad collaboration. With the development of artificial surface observation technology and surveying technology, road potholes detection accuracy has improved in recent years. However, the legacy detection methods do not have the ease of service and realtime observation capability, and thus the potholes in the road cannot be mapped in time. To solve this key issue, we proposed a reflectometry method to realize real-time potholes observation with vibration signals analysis and Spatio-temporal trajectory fusion. We further developed several prototype devices for validation. These prototype devices measure the acceleration signal mounted on the wheel steering lever and implement edge signal processing and Spatio-temporal information fusion on the prototype. Observation results and Spatio-temporal information are been rapidly transmitted to the sensing server via NB-IoT. Results and analyses demonstrated that this method successfully enabled the potholes observation in real-time through light and a rapidly deployable platform that relies on repeated trajectory data from the vehicle. Results also demonstrated that this method was not limited by vehicle type, speed, or engine operating condition. In the road experiment, the proposed method provided stable, efficient, and real-time potholes observation results. Compared with traditional methods, the method reduces costs and improves sensing efficiency based on Spatio-temporal trajectory fusion, and potholes information can be prompted in real-time. This innovation provides a strategic exploration and thinking to deal with road potholes in real-time sensing.

Sustainable Road Pothole Detection: A Crowdsourcing Based Multi-Sensors Fusion Approach

“…However, the detection range based on computer vision is the entire visual field of the moving vehicle, and the detection results are also not affected by the speed of the vehicle. Chen et al [14] proposed a reflectometry method, to realize real-time potholes observation, with vibration signals analysis and spatio-temporal trajectory fusion. Akshatha et al [38] used a cloud-based collaborative approach, to fuse the results of acceleration-based detection and vision-data-based detection.…”

“…To meet current pavement maintenance needs, detecting road anomalies with high spatial and temporal coverage has been widely researched. The vibration of the vehicle is the most obvious response to the potholes on the road, and it has been demonstrated that road anomalies can be detected by establishing a relationship between some vibration signatures and road surface characteristics [7,[13][14][15]. For example, Andren [15] proposed that a road roughness spectrum could be derived from the vehicle vibration spectral density.…”

Deep Learning-based Pothole Detection for Intelligent Transportation: A YOLOv5 Approach

“…Modern cities are witnessing a rapid transformation with the integration of advanced technologies, giving rise to the concept of smart cities [1]. These cities leverage cutting-edge infrastructure, digital connectivity, and intelligent systems to enhance the quality of life for their residents [2,3]. The deployment of smart city facilities enables efficient management of resources, optimized transportation systems, and improved public services [4,5].…”

Comparison of Footrest Vibrations in the Case of an ICE-Based and Battery-Based Two-Wheeler

“…In many vehicles, the engine is positioned near the footrest area, and any imbalance in the engine can lead to the propagation of vibrations to the footrest. Engine imbalances occur due to manufacturing defects, wear and tear, uneven power delivery and the resultant vibrations of reciprocating parts [5,6].…”