Browse > Article

A study on the estimation of AADT by short-term traffic volume survey  

이승재 (서울시립대학교 교통공학과)
백남철 (한국건설기술연구원)
권희정 (서울시정개발연구원)
Publication Information
Journal of Korean Society of Transportation / v.20, no.6, 2002 , pp. 59-68 More about this Journal
Abstract
AADT(Annual Average Daily Traffic) can be obtained by using short-term counted traffic data rather than using traffic data collected for 365 days. The process is a very important in estimating AADT using short-term traffic count data. Therefore, There have been many studies about estimating AADT. In this Paper, we tried to improve the process of the AADT estimation based on the former AADT estimation researches. Firstly, we found the factor showing differences among groups. To do so, we examined hourly variables(divided to total hours, weekday hours. Saturday hours, Sunday hours, weekday and Sunday hours, and weekday and Saturday hours) every time changing the number of groups. After all, we selected the hourly variables of Sunday and weekday as the factor showing differences among groups. Secondly, we classified 200 locations into 10 groups through cluster analysis using only monthly variables. The nile of deciding the number of groups is maximizing deviation among hourly variables of each group. Thirdly, we classified 200 locations which had been used in the second step into the 10 groups by applying statistical techniques such as Discriminant analysis and Neural network. This step is for testing the rate of distinguish between the right group including each location and a wrong one. In conclusion, the result of this study's method was closer to real AADT value than that of the former method. and this study significantly contributes to improve the method of AADT estimation.
Keywords
AADT 추정;군집분석;그룹할당;판별분석;신경망;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 /
[ 한국건설기술연구원 ] / 연평균 일 교통량 추정을 위한 도로교통량 조사지점의 그룹핑 연구
2 불규칙변동 분해 시계분열분석 기법을 사용한 AADT 추정 /
[ 이승재;백남철;권희정;최대순;도명식 ] / 대한교통학회지   과학기술학회마을
3 /
[ FHWA ] / Traffic Monitoring Guide
4 Neural networks as alternative to traditional factor approach of annual average daily traffic estimation from traffic counts /
[ Satish C. Sharma Pawan Lingras Fei Xu Guo X Liv ] / TRR1660
5 /
[ 김대수 ] / 신경망의 이론과 응용
6 SAS라는 이름의 통계상자 /
[ 김정련 ] / 데이터플러스