Speed independent road classification strategy based on vehicle response: Theory and experimental validation. (15th February 2019) - Qin, Yechen; Wang, Zhenfeng; Xiang, Changle; Hashemi, Ehsan; Khajepour, Amir; Huang, Yanjun
Highlights: We propose a vehicle response based speed-independent road classification strategy. The algorithm requires few parameters and can be used for mass-produced vehicles. Simulation and field test results validate the proposed algorithm. Abstract: This paper presents a speed-independent road classification strategy (SIRCS) based on sole measurement of unsprung mass acceleration. The new method provides an easy yet accurate classification methodology. To this purpose, a classification framework with two phases named off-line and online is proposed. In the off-line phase, the transfer function from unsprung mass acceleration to the road excitation is firstly formulated, and a random forest-based frequency domain classifier is then generated according to the standard road definition of ISO 8608. In the online phase, unsprung mass acceleration and vehicle velocity are firstly combined to calculate the equivalent road profile in the spatial domain, and then a two-step road classifier attributes the road excitation to a certain level based on the power spectral density (PSD) of the equivalent road profile. Simulations are carried out for different classification intervals, varying velocity, system uncertainties and measurement noises. Road experiments are finally performed in a production vehicle to validate the proposed SIRCS. Measurement of only unsprung mass acceleration to identify road classification and less rely on the training data are the major contributions of the proposed strategy.