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An Intelligent Evaluation Approach for Riding Comfort Incorporating Vehicle Vibration Acceleration Distribution Characteristics.

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Title: An Intelligent Evaluation Approach for Riding Comfort Incorporating Vehicle Vibration Acceleration Distribution Characteristics.
Authors: Zhang, Jinxi1 (AUTHOR) zhangjinxi@bjut.edu.cn, Zhou, Shengnan1 (AUTHOR) zhousn@emails.bjut.edu.cn, Nie, Lei1 (AUTHOR) nielei@emails.bjut.edu.cn, Guo, Wangda1 (AUTHOR) wangdaguo@emails.bjut.edu.cn
Source: International Journal of Pavement Research & Technology. Jun2026, Vol. 19 Issue 6, p1362-1381. 20p.
Subjects: Automobile vibration, Automatic data collection systems, Surface texture, Human comfort, Surface roughness measurement, Mechanical vibration research, Road maintenance, Evaluation methodology
Geographic Terms: China
Abstract (English): With the ongoing development of China's road infrastructure and the increasing levels of motorization, the riding comfort of road facilities has become a critical concern for traffic participants. The scientific and intelligent evaluation of road facility riding comfort is of great significance for ensuring their effective construction and maintenance. Conventional riding comfort evaluation has primarily relied on the International Roughness Index (IRI), wherein higher IRI values correlate with poorer surface smoothness and reduced driving comfort. However, current IRI methods lack sophisticated intelligence capabilities and cannot achieve real-time monitoring of either IRI or driving comfort. In response to these challenges, this study introduces a self-developed intelligent data collection device for measuring vibration acceleration during vehicle operation, and establishes an innovative evaluation method that incorporates vehicle vibration acceleration distribution characteristics. Initially, we developed a preprocessing protocol for vibration acceleration data and identified relevant characteristic indicators. This foundation enabled the creation of three integrated models: a probability density model for vibration acceleration considering passenger variability, a membership degree model for vibration acceleration comfort, and a comfort rate model incorporating individual passenger differences. Subsequently, a comprehensive comfort rate model incorporating vibration acceleration distribution characteristics was constructed. The study conducted driving tests were across 7 road sections with varying surface technical performance, utilizing 11 vehicle types at different driving speeds. Through mathematical statistics and stochastic theory analysis, a Lognormal distribution model of vehicle vibration acceleration under mixed traffic conditions was established. The research results indicate that the intelligent data collection terminal exhibits excellent working stability, as well as high repeatability and reliability in data collection. The proposed evaluation model yields road surface comfort assessments that strongly correlate with established ISO evaluation methods while offering superior discrimination capabilities across various road conditions, thereby facilitating optimized road maintenance decision-making by relevant agencies. Notably, the developed driving data acquisition device offers significant cost advantages, with implementation expenses approximately 75% lower than traditional IRI detection methods. This research successfully achieves preliminary intelligent evaluation of road riding comfort through the integration of self-developed data collection terminal and innovative evaluation model, enabling indirect intelligent assessment of IRI values. The method presented herein represents a significant advancement in road quality evaluation and maintenance management, offering significant theoretical and practical contributions to the field. [ABSTRACT FROM AUTHOR]
Abstract (German): Highlights: Through a self-developed intelligent data collection device, this study empirically proved that vehicle driving vibration acceleration follows a logarithmic normal distribution pattern. Based on this finding, a logarithmic normal distribution model for vehicle vibration acceleration was developed. A road riding comfort evaluation model was established, incorporating passenger variability and the distribution characteristics of vibration acceleration. The evaluation results align with traditional evaluation methods. The proposed intelligent evaluation method for road riding comfort provides an innovative technological route for the indirect and intelligent assessment of road riding quality and surface roughness. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:With the ongoing development of China's road infrastructure and the increasing levels of motorization, the riding comfort of road facilities has become a critical concern for traffic participants. The scientific and intelligent evaluation of road facility riding comfort is of great significance for ensuring their effective construction and maintenance. Conventional riding comfort evaluation has primarily relied on the International Roughness Index (IRI), wherein higher IRI values correlate with poorer surface smoothness and reduced driving comfort. However, current IRI methods lack sophisticated intelligence capabilities and cannot achieve real-time monitoring of either IRI or driving comfort. In response to these challenges, this study introduces a self-developed intelligent data collection device for measuring vibration acceleration during vehicle operation, and establishes an innovative evaluation method that incorporates vehicle vibration acceleration distribution characteristics. Initially, we developed a preprocessing protocol for vibration acceleration data and identified relevant characteristic indicators. This foundation enabled the creation of three integrated models: a probability density model for vibration acceleration considering passenger variability, a membership degree model for vibration acceleration comfort, and a comfort rate model incorporating individual passenger differences. Subsequently, a comprehensive comfort rate model incorporating vibration acceleration distribution characteristics was constructed. The study conducted driving tests were across 7 road sections with varying surface technical performance, utilizing 11 vehicle types at different driving speeds. Through mathematical statistics and stochastic theory analysis, a Lognormal distribution model of vehicle vibration acceleration under mixed traffic conditions was established. The research results indicate that the intelligent data collection terminal exhibits excellent working stability, as well as high repeatability and reliability in data collection. The proposed evaluation model yields road surface comfort assessments that strongly correlate with established ISO evaluation methods while offering superior discrimination capabilities across various road conditions, thereby facilitating optimized road maintenance decision-making by relevant agencies. Notably, the developed driving data acquisition device offers significant cost advantages, with implementation expenses approximately 75% lower than traditional IRI detection methods. This research successfully achieves preliminary intelligent evaluation of road riding comfort through the integration of self-developed data collection terminal and innovative evaluation model, enabling indirect intelligent assessment of IRI values. The method presented herein represents a significant advancement in road quality evaluation and maintenance management, offering significant theoretical and practical contributions to the field. [ABSTRACT FROM AUTHOR]
ISSN:19971400
DOI:10.1007/s42947-025-00519-2