Day-of-Year Scaling Factors and Design Considerations for Nonmotorized Traffic Monitoring Programs. Issue 1 (January 2014)

• Record Type: Journal Article
• Authors: Hankey, Steve; Lindsey, Greg; Marshall, Julian
• Is Part Of: Transportation research record. Volume 2468:Issue 1(2014)
• Page Start: 64
• Page End: 73
• Publication Date: 2014-01
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.3141/2468-08
• Languages: English
• ISSNs: 0361-1981

Abstract

General procedures, including the estimation of annual average daily traffic (AADT) from short-duration counts, have not been established for nonmotorized traffic monitoring programs. Continuous counts of nonmotorized traffic were collected at six locations on the off-street trail network in Minneapolis, Minnesota, in 2011. A new approach for estimating AADT values from short-duration counts, the use of day-of-year factors, is demonstrated. Analyses of variability in count data can be used to design a monitoring program that uses both continuous and short-duration counts of nonmotorized traffic. Five core conclusions may be useful for developing nonmotorized monitoring programs: ( a ) day-of-year scaling factors have smaller error than does the standard (day-of-week and month-of-year) method of AADT estimation, especially from short-duration counts (<1 week); ( b ) extrapolation error decreases with short-duration-count length, with only marginal gains in accuracy for counts longer than 1 week; ( c ) errors in estimating AADT values are lowest when short-duration counts are taken in summer (or spring, summer, and fall) months (April through October); ( d ) the impact of sampling on consecutive (successive) versus nonconsecutive (separate) days on AADT estimation is minimal but may reduce labor requirements; and ( e ) the design of a traffic monitoring program depends on the acceptable error, equipment availability, and monitoring period duration. Trade-offs in short-duration-count lengths and estimate accuracy will depend on resource constraints. Analysts can use day-of-year factors to improve the accuracy of AADT estimation. Analyses of variability in traffic counts can strengthen the design of monitoring programs.