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Journal Article

Citation

Hocherman I, Hakkert AS, Bar-Ziv J. Transp. Res. Rec. 1988; 1168: 31-38.

Copyright

(Copyright © 1988, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

unavailable

PMID

unavailable

Abstract

The main issue of this paper is whether the distribution of pedestrian volumes during the day can be generalized in a way similar to vehicular flow distribution, so that the daily average can be deduced from short counts. Hourly whole day counts in 86 urban locations were used to determine the typical daily distributions of crossing pedestrians in residential and central business district streets in Israel. For each hour, the standard deviation and coefficient of variation were calculated, as measures of variation among locations, to determine the best time of day for performing short counts. The standard deviation of the hourly rate was generally 1 to 3.5 percent of the total daily volume. The coefficient of variation was generally 20 to 50 percent of the average hourly volume. Hours during nonpeak periods and afternoon peak were identified with relatively low dispersion. These hours should be preferred whenever short counts are performed for the purpose of risk estimates. The average daily estimates can be improved by using counts of 2 or more hours. In addition, 135 daily counts in 15-min intervals were used to examine the adequacy of such short counts for estimating hourly flows in residential locations. The four 15-min counts in each full hour were regarded as four independent samples from the same distribution. Coefficients of variation (CVs) amoung the 15-min counts were calculated for each hour and averaged over locations. The CVs varied across hours but in each cased were greater than 30 percent. It was concluded that 15-min counts should not be used for the estimation of hourly pedestrian flows in residential areas.

Record URL:
http://onlinepubs.trb.org/Onlinepubs/trr/1988/1168/1168-005.pdf


Language: en

Keywords

Street Traffic Control; Statistical Methods; Data Processing; Roads and Streets--Human Factors

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