原文传递
Fusion of weigh-in-motion and global positioning system data to estimate truck weight distributions at traffic count sites
| 题名： | Fusion of weigh-in-motion and global positioning system data to estimate truck weight distributions at traffic count sites |
| 正文语种： | 英文 |
| 作者： | Sarah Hernandez;Kyung (Kate) Hyun |
| 作者单位： | University of Arkansas;University of Texas |
| 关键词： | Gaussian mixture model; global positioning systems (GPS); gross vehicle weight (GVW); spatial interpolation; weigh-in-motion (WIM) |
| 摘要： | Truck weight data is needed for a wide range of applications including but not limited to pavement design, weight enforcement, traffic monitoring, and freight transportation plan-ning. Unfortunately, the low spatial resolution of weight sensors along the transportation network can limit these and other potential applications. The main contribution of this paper is a methodology to estimate gross vehicle weight (GVW) distributions at traffic count sites, which collect traffic volumes but currently do not have the ability to directly measure vehicle weight. This paper presents a method for estimating GVW distributions of five-axle tractor-trailers ("3・S2") at traffic count sites by fuzing weight data from weigh-in-motion (WIM) sites with position data from global positioning system (GPS) equipped trucks. Truck travel patter ns derived from a truck GPS database were used to determi ne the degree to which a WIM and traffic count site are spatially related. A GVW distribution was then estimated by combining Gaussian mixture models (GMM) estimated at WIM sites defined to be spatially related to the traffic count site. A leave-one-out cross validation framework allowed for comparisons of estimated and measured GVW distributions at each WIM site. Coincide nee ratios and two-sample Kolmogorov-Smirnov (KS) tests were used as comparison metrics for a case study of 112 WIM sites in California. The proposed methodology provided better goodness-of-fit between observed and estimated GVW distributions compared to a baseline approach which defined the spatial relation between sites using great circle distances (GCD). |
| 出版日期： | 2020 |
| 出版年： | 2020 |
| 期刊名称： | Journal of Intelligent Transportation Systems Technology Planning and Operations |
| 卷： | Vol24 |
| 期： | No01-06 |
| 页码： | 201-215 |
相关文献
- A statistical process control approach using cumulative sum control chart analysis for traffic data quality verification and sensor calibration for weigh-in-motion systems
- Weathering WIM sensor installation
- IRD in the Ukraine
- Determining optimal sensor locations under uncertainty for a truck activity monitoring system on California freeways
- Luxembourg duty for KiTraffic Plus
- IRD wins WIM deal in Hawaii
检索历史
应用推荐
