ABSTRACT

Weigh-in-Motion (WIM) systems are used in order to reduce the number of overloaded vehicles. Data collected from WIM provide characteristics of vehicle axle loads that are crucial for pavement design as well as for the development of pavement distress prediction models. The inaccuracy of WIM data lead to erroneous estimation of traffic loads and in consequence inaccurate prediction of pavement distress process. The objective of the paper is to present a new methodology of heavy traffic axle load spectra (ALS) correction due to weighing errors (systematic and random) that occur in WIM systems. The theoretical solution which is proposed in the paper was validated successfully. The method enables correction of erroneous data to make traffic load statistics used for pavement design more reliable and precise, with no necessity to remove high number of records, as it is used in other methods. The practical meaning of the newly developed method was emphasised by analysis of the effect of relative and random error of WIM data on pavement fatigue life estimation, as well as on the estimated percentage of overloaded vehicles. Mechanistic-empirical approach (M-EPDG) was used for this purpose.

摘要

动态称重 (WIM) 系统用于减少超载车辆的数量。从 WIM 收集的数据提供了对路面设计以及路面故障预测模型的开发至关重要的车辆轴载特性。WIM 数据的不准确导致对交通负荷的错误估计，从而导致对路面遇险过程的不准确预测。本文的目的是提出一种新的方法来校正由于 WIM 系统中出现的称重误差（系统性和随机性）导致的重载交通轴载谱 (ALS)。论文提出的理论解决方案得到了成功验证。该方法能够纠正错误数据，使用于路面设计的交通负荷统计更加可靠和精确，无需删除大量记录，因为它用于其他方法。通过分析 WIM 数据的相对误差和随机误差对路面疲劳寿命估计以及超载车辆估计百分比的影响，强调了新开发方法的实际意义。为此目的使用了机械经验方法 (M-EPDG)。