Gang Qiu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Gang Qiu has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Kai Gao
College of Mechanical and Vehicle Engineering, Changsha University of Science & Technology, Changsha 410114, China
1 shared publication - Li Liu
College of Automotive and Mechanical Engineering, Changsha University of Science & Technology, Changsha 410114, China
1 shared publication - Lin Hu
Changsha University of Science and Technology
1 shared publication - Ronghua Du
College of Automotive and Mechanical Engineering, Changsha University of Science & Technology, Changsha 410114, China
1 shared publication
Latest Publications
- Open Access
Abnormal Road Surface Recognition Based on Smartphone Acceleration Sensor
In order to identify the abnormal road surface condition efficiently and at low cost, a road surface condition recognition method is proposed based on the vibration acceleration generated by a smartphone when the vehicle passes through the abnormal road surface. The improved Gaussian background model is used to extract the features of the abnormal pavement, and the k-nearest neighbor (kNN) algorithm is used to distinguish the abnormal pavement types, including pothole and bump. Comparing with the existing works, the influence of vehicles with different suspension characteristics on the detection threshold is studied in this paper, and an adaptive adjustment mechanism based on vehicle speed is proposed. After comparing the field investigation results with the algorithm recognition results, the accuracy of the proposed algorithm is rigorously evaluated. The test results show that the vehicle vibration acceleration contains the road surface condition information, which can be used to identify the abnormal road conditions. The test result shows that the accuracy of the recognition of the road surface pothole is 96.03%, and the accuracy of the road surface bump is 94.12%. The proposed road surface recognition method can be utilized to replace the special patrol vehicle for timely and low-cost road maintenance.
Open AccessAbnormal Road Surface Recognition Based on Smartphone Acceleration Sensor
In order to identify the abnormal road surface condition efficiently and at low cost, a road surface condition recognition method is proposed based on the vibration acceleration generated by a smartphone when the vehicle passes through the abnormal road surface. The improved Gaussian background model is used to extract the features of the abnormal pavement, and the k-nearest neighbor (kNN) algorithm is used to distinguish the abnormal pavement types, including pothole and bump. Comparing with the existing works, the influence of vehicles with different suspension characteristics on the detection threshold is studied in this paper, and an adaptive adjustment mechanism based on vehicle speed is proposed. After comparing the field investigation results with the algorithm recognition results, the accuracy of the proposed algorithm is rigorously evaluated. The test results show that the vehicle vibration acceleration contains the road surface condition information, which can be used to identify the abnormal road conditions. The test result shows that the accuracy of the recognition of the road surface pothole is 96.03%, and the accuracy of the road surface bump is 94.12%. The proposed road surface recognition method can be utilized to replace the special patrol vehicle for timely and low-cost road maintenance.