原文传递
A statistical process control approach using cumulative sum control chart analysis for traffic data quality verification and sensor calibration for weigh-in-motion systems
| 题名： | A statistical process control approach using cumulative sum control chart analysis for traffic data quality verification and sensor calibration for weigh-in-motion systems |
| 其他题名： | American Association of State Highway and Transportation Officials.(2006).Smoothness of pavement at the approaches to WIM scales.AASHTO MP 14-05.Washington,DC:AASHTO. |
| 正文语种： | 英文 |
| 作者： | Indrajit Chatterjee |
| 关键词： | CUSUM introduction;traffic data quality;weigh-in-motion |
| 摘要： | Weigh-in-motion systems have been widely used by state agencies to collect the traffic data on major state roadways and bridges to support traffic load forecasting, pavement design and analysis, infrastructure investment decision making, and transportation planning. However, the weigh-inmotion system itself poses difficulties in obtaining accurate data due to sensor characteristics that can be sensitive to vehicle speed, weather conditions, and changes in surrounding pavement conditions. This study focuses on developing a systematic methodology to detect weigh-in-motion sensor bias and enhance current practices for weigh-in-motion calibration. A mixture modeling technique using an expectation maximization algorithm was developed to divide the vehicle class 9 gross vehicle weight into three normally distributed components: unloaded, partially loaded, and fully loaded trucks. Then the well-known statistical process control technique cumulative sum control chart analysis was applied to expectation maximization estimates of daily mean gross vehicle weight for fully loaded trucks to identify and estimate shifts in theweigh-in-motion sensor. Special attention was given to the presence of autocorrelation in the data by fitting an autoregressive time-series model and then performing cumulative sumcontrol chart analysis on the fitted residuals. Results fromthe analysis suggest that the proposed methodology is able to estimate a shift in the weigh-in-motion sensor accurately and also indicate the time point when the systemwent out of calibration. This methodology can be effectively implemented by state agencies, resulting in more accurate and reliableweigh-in-motion data. |
| 出版年： | 2017 |
| 论文唯一标识： | J-96Y2017V21N02003 |
| 英文栏目名称： | Articles |
| 期刊名称： | Journal of Intelligent Transportation Systems Technology Planning and Operations |
| 拼音刊名(出版物代码)： | J-96 |
| 卷： | 21 |
| 期： | 02 |
| 页码： | 111-122 |
相关文献
- Determining optimal sensor locations under uncertainty for a truck activity monitoring system on California freeways
- Spatiotemporal Analysis of Overloaded Vehicles on a Highway Using Weigh-in-Motion Data
- Weathering WIM sensor installation
- IRD in the Ukraine
- HYPACK to Release Real Time Point Cloud for Multibeam and Topo Laser Surveys
- FUELED by data How machine learning detects waste, fraud, maintenance needs
检索历史
应用推荐
