Statistical Validation for Short Count Traffic Counts Using Spatial Regression Model

• 발행기관: 한국자료분석학회
• 저자명: 허태영(Tae-Young Heo) 엄진기(JinKi Eom) 박희문(Hee Mun Park) 박찬근(Chan Keun Park)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.10 No.4, 1837~1848쪽, 전체 12쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2008.08.30

영문 초록

The methodology to identify the traffic count stations that have anomalous counts was developed in this paper. Our proposed approach is to develop a spatial model that would separate out systematic and spatial variability in counts so that residual uncertainty may be identified. A principal component analysis was applied by using dimension reduction dealing with census data with many attributes. This proposed method would significantly improve the process of validating traffic counts by increasing the accuracy of reported counts and by reducing the time delay between data collection and reporting.

목차

1. Introduction

2. Data

3. Modelling the Spatial Field

4. Trend fitting and selection

5. Models with Spatially Correlated Residuals of AADT

6. Results

7. Conclusions

References

키워드

Annual average daily traffic(AADT) portable traffic counters(PTC) variogram principal component analysis general least squares estimator