Minimizing Annual Average Daily Nonmotorized Traffic Estimation Errors: How Many Counters Are Needed per Factor Group?

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Transportation Research Record: Journal of the Transportation Research Board

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Accurate estimates of bicycle and pedestrian volume inform safety studies, trend monitoring, and infrastructure improvements. The Federal Highway Administration’s Traffic Monitoring Guide advises current practice for estimation of nonmotorized traffic. While methodologies have been developed to minimize error in estimation of annual average daily nonmotorized traffic (AADNT), challenges persist. This study provides new guidance for monitoring and volume estimation of nonmotorized traffic. Using continuous count data from 102 sites across six cities, the findings confirm that mean absolute percent error (MAPE) in estimated AADNT is minimized when seven-day short duration counts are collected in June through September and for 24-h counts, when data are collected Tuesdays through Thursdays (except for pedestrian-only counts). MAPE across all days (except holidays) and seasons was 34% for 24-h and 20–22% for seven-day short duration counts. The magnitude of bicycle and pedestrian volumes did not significantly affect estimation errors. For factor groups larger than one counter, the length of short duration samples may influence accuracy of AADNT estimates more than the number of counters per group, all else equal. To maximize precision of estimates of AADNT, four or more counters per factor group for bicycle and five or more for pedestrian travel monitoring are recommended. These findings provide guidance for practitioners seeking to establish or improve nonmotorized traffic monitoring programs.

Federal, state, and local agencies desire accurate estimates of demand for bicycling and walking to plan and manage transportation systems, meet people’s needs for commerce, recreation, and health, and create prosperous and safe communities. The Federal Highway Administration (FHWA) Traffic Monitoring Guide (TMG) for estimating annual average daily motor vehicle traffic (AADT) informs current practice in nonmotorized traffic estimation (1). Estimates of AADT are produced by establishing integrated networks of monitoring locations and using ratios, or factors, derived from temporal traffic patterns observed at permanent locations to extrapolate short duration counts to estimates of AADT, or in the case of bicycling and walking, annual average daily bicycle/pedestrian/nonmotorized traffic (AADBT/AADPT/AADNT). Because bicycle and pedestrian traffic varies more across seasons and in response to weather than vehicular traffic, standard methods for monitoring and for extrapolating short duration vehicle counts must be adapted to nonmotorized modes. Although researchers have made progress in developing methods that minimize error in estimates of AADNT, methodological challenges remain.

This paper contributes to the literature on traffic monitoring by providing new guidance for monitoring and extrapolating nonmotorized traffic counts. Drawing on an extensive continuous count dataset of 102 monitoring sites in Arlington, VA; Boulder, CO; Mt Vernon, WA; Portland, OR; San Diego, CA; and Seattle, WA, the study validates previous findings about optimal timing and duration of short duration counts and presents new findings about other aspects of monitoring, including the number of sites needed in factor groups to produce more reliable estimates of AADNT.


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