The purpose of the paper is to improve the efficiency of vehicle based sensing technology in highway pavement condition assessment by evaluating the effect of four factors (sensor placement, pavement temperature, drive speed, and threshold for pavement distress classification) and providing suggestions to better improve the accuracy of pavement condition detection and minimize the interruption of pavement sensing operation. Two I-10 corridors in the Phoenix region were selected for vibration data collection and data analysis. A series of statistical analyses were performed to determine if each one of the factors has a significant impact on the pavement distress detection. The results of Analysis of Variance (ANOVA) tests and Analysis of Covariance (ANCOVA) tests show that the placement of sensors have a significant effect in the pavement condition assessments. The significant differences occurred in the group of sensors that were placed on the same side of the vehicle, as well as, in either front wheels or rear wheels of the vehicle. The effect of pavement temperature on the vehicle based sensing implementation is significant while the mean drive speed is not seen as a significant factor in the pavement condition survey. The two thresholds were determined to select points of interest (POI; cracks, potholes) for the pavement distress classification and these POIs are in good agreement with international roughness index (IRI) data in an ArcGIS map. The findings of the paper can be used to better improve the computing algorithms of vehicle based sensing techniques.

中文翻译：

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评估基于车辆的路面传感实施中因素的影响：传感器放置、路面温度、速度和阈值

本文的目的是通过评估四个因素（传感器放置、路面温度、行驶速度和路面损坏分类阈值）的影响，提高基于车辆的传感技术在高速公路路面状况评估中的效率，并提供更好改进的建议路面状况检测的准确性，并最大限度地减少路面传感操作的中断。选择凤凰城地区的两条 I-10 走廊进行振动数据收集和数据分析。进行了一系列统计分析以确定每个因素是否对路面损坏检测有重大影响。方差分析 (ANOVA) 测试和协方差分析 (ANCOVA) 测试的结果表明，传感器的放置对路面状况评估有显着影响。显着差异发生在放置在车辆同一侧以及车辆前轮或后轮的传感器组中。路面温度对基于车辆的传感实施的影响是显着的，而平均行驶速度在路面状况调查中不被视为重要因素。确定这两个阈值是为了选择兴趣点（POI；裂缝、坑洼）进行路面损坏分类，这些 POI 与 ArcGIS 地图中的国际粗糙度指数 (IRI) 数据非常一致。