Guidebook on Pedestrian and Bicycle Volume Data Collection (2014)

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138 A p p e n d i x d A day-of-year expansion factor can be applied in lieu of the traditional combination of day- of-week and month-of-year factors. This approach has been shown to substantially outperform the traditional approach in both bicycle-only monitoring situations and in mixed bicycle and pedestrian situations (Hankey et al. 2014, Nosal et al. 2014). A separate adjustment factor is gen- erated for every day of the year for each factor group of interest. Short-term counts conducted within a given factor group can then be expanded to estimate AABT or AAPT. Expansions based on just 1 day of short-term count data were found to have a mean error of 14 to 21% with the day-of-year approach, compared to 24 to 40% with the traditional approach, as shown in Figure D-1. This range of error rates can likely be attributed to dif- ferences in the data collection sites—the low end comes from sites very near to each other, whereas the high end comes from sites dispersed over a larger area. As the number of days of data used for the short-term count is increased, the error rate further decreases, finally approaching a value of about 12% after 7 days. The traditional approach approaches a similar error rate, but only after 14 to 21 days of data collection. Whenever possible, short-term counts should be taken for 1-week periods to ensure accurate long-term volume estimates. (Hankey et al. 2014, Nosal et al. 2014). The day-of-year approach has one substantial advantage over the traditional factoring approach when it comes to weather. In the traditional approach, weather is not taken into account unless the count estimate is multiplied by an additional “weather factor.” However, assuming that weather patterns are fairly consistent between the continuous count site and the short-term count site, weather effects are implicitly accounted for with the day-of-year patterns because every day of short-term data is matched to continuous count data from the exact same day. To implement the day-of-year factoring method, a full year’s worth of continuous count data has to exist for at least one site in each factor group within the count study area, and this full year must include the days on which short-term counts were conducted. As stated before, at least 1 week of short-term counts should be available if possible, but as little as 1 day’s worth of data can be used. Calculate the proportion of the total annual traffic that each day of the year represents—this is the day-of-year factor: , , ,1 365DOY VOL VOL k i k i k jj∑ = = where VOLk,i is the volume at site k on day i. Day-of-Year Factoring Approach

day-of-Year Factoring Approach 139 To apply these factors at a short-term count site l, where data has been collected for m full days, use the following (where SDT is the Short-Duration Total, VOL is the volume for a given site and day, and AADT is the annual average daily traffic):  , ,1 , , , SDT VOL AADT SDT DOY l m l dd m l m l m l dd m ∑ ∑ = = = If multiple continuous count sites are available for a specific factor group within the region, some discretion is needed in estimating the day-of-year factors. One approach is to average the factors from each of the sites in the group. Alternatively, the geographically closest continuous count site in the factor group could be used. These methods have not been rigorously tested, so local experimentation is encouraged. Figure D-1. Plot of AADT prediction by count duration and count expansion approach. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 0 5 10 15 20 25 30 Vo lu m e Es m a on Pe rc en tE rr or Number of Days of Data Collecon Tradional Method (Nosal et al. 2014) Day of Year method (Nosal et al. 2014) Tradional Method (Hankey et al. 2014) Day of Year method (Hankey et al. 2014)

Abbreviations and acronyms used without definitions in TRB publications: A4A Airlines for America AAAE American Association of Airport Executives AASHO American Association of State Highway Officials AASHTO American Association of State Highway and Transportation Officials ACI–NA Airports Council International–North America ACRP Airport Cooperative Research Program ADA Americans with Disabilities Act APTA American Public Transportation Association ASCE American Society of Civil Engineers ASME American Society of Mechanical Engineers ASTM American Society for Testing and Materials ATA American Trucking Associations CTAA Community Transportation Association of America CTBSSP Commercial Truck and Bus Safety Synthesis Program DHS Department of Homeland Security DOE Department of Energy EPA Environmental Protection Agency FAA Federal Aviation Administration FHWA Federal Highway Administration FMCSA Federal Motor Carrier Safety Administration FRA Federal Railroad Administration FTA Federal Transit Administration HMCRP Hazardous Materials Cooperative Research Program IEEE Institute of Electrical and Electronics Engineers ISTEA Intermodal Surface Transportation Efficiency Act of 1991 ITE Institute of Transportation Engineers MAP-21 Moving Ahead for Progress in the 21st Century Act (2012) NASA National Aeronautics and Space Administration NASAO National Association of State Aviation Officials NCFRP National Cooperative Freight Research Program NCHRP National Cooperative Highway Research Program NHTSA National Highway Traffic Safety Administration NTSB National Transportation Safety Board PHMSA Pipeline and Hazardous Materials Safety Administration RITA Research and Innovative Technology Administration SAE Society of Automotive Engineers SAFETEA-LU Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (2005) TCRP Transit Cooperative Research Program TEA-21 Transportation Equity Act for the 21st Century (1998) TRB Transportation Research Board TSA Transportation Security Administration U.S.DOT United States Department of Transportation