Road classification for two-wheeled vehicles

Abstract

This publication presents a three-part road classification system that utilises the vehicle's onboard signals of two-wheeled vehicles. First, a curve estimator was developed to identify and classify road curves. In addition, the curve estimator continuously classifies the road curviness. Second, the road slope was evaluated to determine the hilliness of a given road. Third, a modular road profile estimator has been developed to classify the road profile according to ISO 8608, which utilises the vehicle's transfer functions. The road profile estimator continuously classifies the driven road. The proposed methods for the classification of curviness, hilliness, and road roughness have been validated with measurements. The road classification system enables the collection of vehicle-independent field data of two-wheeled vehicles. The road properties are part of the customer usage profiles which are essential to define vehicle design targets.

Response-based methods to measure road surface irregularity: a state-of-the-art review

“…The road can be classified according to ISO 8608 [51] based on PSD road estimated from the PSD acc of the axle or body acceleration measurements [50]. In [52], similar results have confirmed the efficiency of the TF approach, and in [53] the TF was extended to a full-vehicle model to estimate road PSD regardless of vehicle speeds. From another point of view, dynamic tyre pressure sensor was used to estimate road profiles based on an assumption of a linear relationship between road surface profiles and tyre pressure via a TF [54].…”

Impact detection using a machine learning approach and experimental road roughness classification

“…In the present research, the current road roughness is revealed and classified, to obtain a distribution 1 of driven road classes, in the sense of field data collection. The underlying method of estimating the road roughness was developed by Gorges et al [1] and is experimentally validated in the present publication. The modular road roughness classification system utilises the vehicle's transfer functions and classifies the road profile according to ISO 8608 [2].…”

“…Furthermore, the evaluation of the current road roughness makes active suspension systems possible, as shown in [13][14][15][16][17][18][19][20][21][22][23][24]. Burger [25] and Fauriat et al [26] developed methods of deriving customer usage profiles in terms of durability, as was also the focus of Gorges et al [1]. Different techniques were utilised to estimate the road roughness.…”

“…The rather simple, but fast, approach of estimating the road profile in the frequency domain with the help of transfer functions, has been published by González et al [10] and Barbosa [35][36][37]. This approach was also utilised by Gorges et al [1] and extended to a full-vehicle model with a delayed real-wheel excitation. The novel contributions of this research were a sliding window with a small time span and velocitydependant transfer functions.…”

“…A definition and illustration of longitudinal road profiles can be found in the previous research by Gorges et al [1]. Longitudinal road profiles are defined as slices of the road surface in the direction of the road.…”