详情

原文传递 TRAFnC-LOAD FORECASTINO USING WEIGH-IN-MOTION DATA

题名：	TRAFnC-LOAD FORECASTINO USING WEIGH-IN-MOTION DATA
作者：	Tongbin Qu, Clyde E. Lee, and Liien Huang
关键词：	Weigh-m-motion systems, vehicle classification axle weight frequency distribution, weighted average ESALs per vehicle, traffic count forecasting, traffic load forecasting
摘要：	Vehicular traffic loading is a crucial consideration for foe design and maintenance of pavements. With the help of weigh-in-motion (WIM) systems, the information about date, time, speed, lane of travel, lateral lane position, axle gracing, and wheel load for each vehicle passing a WIM she can be recorded continuously on-site and transferred to a remote computer. This study focused on using foe date from two WIM systems installed to support research on pavement performance. Date analysis involved processing the date from foe two WIM systems, summarizing the date into respective TxDOT vehicle classes, analyzing foe error records in the WIM data, and exploring trends and patterns in foe observed traffic counts. The researchers also analyzed foe axle-load frequency distribution for different axle groups within all truck classes, explored foe trend of axle-load distribution among years, and compared the difference in axle-load distribution for the same axle type at different locations in different vehicle classes. A time-series method was used to forecast traffic counts for each vehicle class based on foe trend in foe pattern of observed traffic and a growth rate for each vehicle class. Finally. cumulative traffic loading was forecasted by applying the estimates of future traffic count to the respective axle-load frequency distribution. A C-language computer program that runs on PC-compatible machines was developed to facilitate data processing for traffic-load forecasting.
报告类型：	科技报告