Day-of-Year Scaling Factors and Design Considerations for Nonmotorized Traffic Monitoring Programs
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.
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