This paper investigates a multi-modal and human-centric framework for low-cost road roughness assessment. The evaluation was based on three complementary data sources: smartphone-based International Roughness Index (IRI) estimates from two independent smartphone-based applications; in-vehicle GNSS-IMU Receiver (Global Navigation Satellite System Receiver with Inertial Measurement Unit) measurements, and passenger Present Serviceability Ratings (PSR). Data were collected over 1700 km across Austria, Hungary, and Romania under real traffic conditions. Inter-application agreement was evaluated using correlation analysis, Intraclass Correlation Coefficient (ICC), and Bland-Altman methods. While the two smartphone applications show strong correlation, systematic bias limits their interchangeability. A significant inverse relationship between IRI and PSR confirms perceptual sensitivity to roughness, and positive correlations between IRI and vertical acceleration validate the physical linkage between pavement irregularities and vehicle dynamics. The results demonstrate the challenges of integrating consumer-grade sensing and perception-based evaluation for road roughness monitoring as an alternative to high-cost specialized survey equipment.

翻译：本文研究了一种面向低成本路面平整度评估的多模态及以人为本的框架。评估基于三种互补数据源：来自两款独立智能手机应用基于智能手机的国际平整度指数（IRI）估计；车载GNSS-IMU接收器（包含惯性测量单元的全球导航卫星系统接收器）测量数据；以及乘客现场服务能力评分（PSR）。数据在奥地利、匈牙利和罗马尼亚境内超过1700公里的真实交通条件下采集。采用相关性分析、组内相关系数（ICC）和Bland-Altman方法评估应用间的一致性。尽管两款智能手机应用表现出强相关性，但系统性偏差限制了其可互换性。IRI与PSR之间显著的负相关证实了感知对平整度的敏感性，而IRI与垂直加速度之间的正相关则验证了路面不平整与车辆动力学之间的物理联系。结果表明，将消费级感知与基于感知的评估集成用于路面平整度监测，以替代高成本专用测量设备，仍面临挑战。