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National Bicycle & Pedestrian Documentation Project. Charlie Denney, Alta Planning + Design. Alta Planning + Design with Institute of Transportation Engineers (ITE). Outline. What is the National Bicycle Pedestrian Documentation Project (NBPD)? Technology for Your Count
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National Bicycle & Pedestrian Documentation Project Charlie Denney, Alta Planning + Design Alta Planning + Design with Institute of Transportation Engineers (ITE)
Outline What is the National Bicycle Pedestrian Documentation Project (NBPD)? Technology for Your Count Extrapolating Counts 2
A pro bono effort by Alta Planning + Design with support from ITE Annual bicycle and pedestrian count and survey effort Fulfill need for in-depth analysis of factors why people walk and bike Objectives Consistent data collection Open data access Shared research What is NBPD? 3
Lack of consistent data Non-motorized modes lack of funding Analysis for other modes are based on marginal data yet receive substantive funding Need for NBPD 4
Counts from over 500 locations in 60 communities Washington State Bicycle and Pedestrian Documentation Project (http://wsdot.wa.gov/bike/Count.htm) Arlington County, VA Adjust counts done almost any period on multi-use paths and pedestrian districts to an annual figure Related projects include Seamless Travel in San Diego County 4 Federally funded Non-Motorized Transportation Pilot Projects New website: www.bikepeddocumentation.org Accomplishments 5
NBPD Count Dates and Times Tuesday, September 10 through Thursday, September 12 Saturday, September 14 through Sunday, September 15 Recommended Times Weekday, 5-7 PM Saturday, 12 noon – 2PM Secondary Times Weekday, 7 AM to 7 PM Saturday, 7 AM to 7 PM 2013 Official National Count/Survey Days
Choosing a Location Historic count location Existing or proposed facility High collision area Smart growth, mix of land uses Transit access Bottleneck or pinch areas Stakeholder recommendations
Count Effort Budget Manual count person hours vs. cost of count machines Duration of Count Effort Quarterly, bi-annual, yearly Year long Type of data Volume Behavior, i.e., helmet use, wrong-way riding Gender Manual vs. Automatic Counts 9
Error Factors All automatic count technologies have an error factor Error rates vary by technology Adjustments Typical calibration involves a comparison of manual and automatic counts From comparison a correction factor can be derived. Error Factors and Adjustments 11
Considerations Who are you counting? Bicycles? Pedestrians? Both? Do you need to differentiate between bicyclists and pedestrians? Technology cost What is your budget? Staff time cost What is your budget? Technology for your Count 12
Data Access and Analysis Data can be used for: Demand projections Exposure analysis Estimate of benefits Trip generation Overall trends in activity Facility operation and design Land use and design 13
Arlington, VA • Started with manual counts • Experimented with automated counters • Full program with 28 automated counters • Sharing with Washington, DC and NPS
Caltrans/San Diego • Caltrans/TSC • 2.5 year study • 40 historic locations • 40 new locations • 80 total count locations • AM weekday peak (all) • Midday weekend peak (all) • PM weekday peak (20 selected)
Analysis: Key Observed Patterns Significant hourly variation weekday/weekend variation monthly variation No generalized ‘peak’ period More variability in recreational travel patterns (vs. utilitarian travel) Accept variation as part of normal estimating process 20
Extrapolating Counts Standard technique used in travel demand modeling Utilize automatic 24 hour counts to determine hourly, daily, monthly and annual rates (adjustment factors) Extrapolate manual hourly counts to daily, monthly or annual estimates
Extrapolating Counts We recommend a combination of automatic counts (annual) manual counts (hourly)
Extrapolation Example Detailed instructions available online 4-5 PM Tuesday count 100 bicycles Adjustment factor = .07 100/.07 = 1,429 Daily to weekly trips 1429 daily trips on Tuesday Adjustment factor = .13 1429/.13 = 10,992 Weekly to monthly 4.33 weeks per month 10,992 * 4.33 = 47,595 Hourly Adjustment Factors
Other Uses - Estimating Demand Utilize count data to identify factors correlated with biking and walking Our research found Employment Density R = .976 Multi-use trail within ¼ mile R = .879
Conclusions/Next Steps Regional differences in seasonal patterns Unlike vehicle use patterns Estimate models will need regional factors Climate Visitors Need for more 365-day count machines To count pedestrians and on-street bicyclists Need for standardized counting methodology to yield improved data 25
Thank You More information: Alta Planning + Design www.altaplanning.com www.bikepeddocumentation.org Jennifer Donlon jenniferdonlon@altaplanning.com Charlie Denney charliedenney@altaplanning.com Institute of Transportation Engineers http://www.ite.org/councils/Ped_Bike/trips.asp 26