Citation

Garber NJ, Bayat-Mokhtari F. Transp. Res. Rec. 1986; 1090: 1-7.

Copyright

(Copyright © 1986, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

unavailable

PMID

unavailable

Abstract

Most state transportation agencies are making a major effort to reduce their annual expenditures on traffic counts yet maintain the desired level of accuracy. These state agencies are therefore developing traffic count programs based on collecting data on a statistically selected sample of highway sections. The assumption is that if road sections can be put into groups such that each group contains sections of highways with similar characteristics, then data collected on a statistically selected sample of selections in any one group will provide traffic data representative of all sections within that group. The main variables used for this grouping are now the FHWA classification system and the average annual daily traffic (AADT) of the road. Unfortunately, the FHWA system can be subjective in cases, and in most cases the AADT of the highway section is unknown or wrong. Estimates of the coefficients of variation of the AADT of groups formed by the standard procedure have therefore tended to be high, which means that large sample sizes are needed to obtain the required accuracy. Consequently, the cost of collecting annual traffic data has not been reduced significantly. In this paper is presented a clustering technique that does not require a knowledge of the link AADTs but does require the use of certain characteristics, such as terrain, land use, and vehicle mix, which are shown to be surrogates of the AADT and can be easily obtained. The technique was used in grouping highway links in the Richmond area of Virginia, and it was found that estimates of the coefficients of variation from sample data were much lower than those recommended by the FHWA. It is concluded that the required sample sizes for annual traffic data collection are lower and this is reflected in lower costs.

Language: en

Keywords

TRAFFIC SURVEYS; HIGHWAY ADMINISTRATION; TRANSPORTATION - Traffic Control; HIGHWAY TRAFFIC CONTROL - Management