Large-scale road surface evaluation using dynamic responses of commercial vehicles

Response-based road condition evaluation is expected to provide road surface conditions effectively and efficiently. A large scale road surface condition evaluation using a large number of commercial vehicles is conducted based on Dynamic Response Intelligent Monitoring System (DRIMS) ; DRIMS estimate the International Roughness Index (IRI) using vehicle responses. A mobile device version of DRIMS, iDRIMS, is employed. The data is first analyzed to construct a Half-Car (HC) model of measurement vehicles. The parameters of the Half-Car (HC) model is identified through Unscented Kalman Filter(UKF) and Genetic Algorithm(GA). Then, IRI is estimated by analyzing vertical acceleration responses using the HC model. To verify the effectiveness of this method, the estimated IRI is compared with the reference IRI obtained by a road profiler. The comparison shows good agreement between iDRIMS and the reference and indicates the validity of large-scale road surface evaluation using general commercial vehicles. Finally, the data collection and analysis platform is built which succesfully collected and analyzed 6 months data from about 50 commercial vehicles.