DEVELOPMENT AND EVALUATION OF A STATISTICALLY RELIABLE TRAFFIC COUNTING PROGRAM

被引:9
作者
FAGHRI, A
CHAKROBORTY, P
机构
[1] Department of Civil Engineering, University of Delaware, Newark, Delaware
关键词
ANNUAL AVERAGE DAILY TRAFFIC (AADT); CLUSTER ANALYSIS; REGRESSION ANALYSIS; SEASONAL FACTORS; GROWTH FACTORS;
D O I
10.1080/03081069408717545
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
This paper reviews the existing procedures to compute the seasonal factors, growth factors, and the number of automatic traffic recorder stations (ATRs) for developing a statistically reliable traffic counting program. The review is based on, (i) theoretical evaluation of the procedures, (ii) analysis of the results obtained from applying these procedures to extensive real life data, and (iii) experience of past researchers with these methods. The paper primarily deals with existing statistical procedures for determining seasonal factors, since it is believed that these factors play the most important role in estimating Annual Average Daily Traffic (AADTs) from short counts. The procedure of cluster analysis (which is most commonly used to determine seasonal factors) is critically reviewed. The shortcomings of this method motivated the development of a different statistical procedure, based on regression analysis, to determine seasonal factors. It is shown that this newly developed method gives better results than the cluster analysis techniques. Furthermore, separate sections are dedicated to a thorough analysis of determination of number of ATR stations and computation of growth factors.
引用
收藏
页码:223 / 237
页数:15
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