Guidebook on Pedestrian and Bicycle Volume Data Collection (2014) / Chapter Skim
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Pages 103-116
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From page 103... ...
103 A p p e n d i x A Case Study 1: Alameda County Use of Continuous Count Patterns to Compare Short Pedestrian Counts Alameda County, California, used approximately 1 month of automated count data to identify patterns of pedestrian activity at 13 sidewalk locations in 2008. Having continuous pedestrian activity pattern data helped address common challenges faced when comparing short (e.g., 2-hour)
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104 Guidebook on pedestrian and Bicycle Volume data Collection Source: Robert Schneider, UC Berkeley SafeTREC. 0.0% 0.2% 0.4% 0.6% 0.8% 1.0% 1.2% 1.4% 12 A M 4 A M 8 A M 12 P M 4 PM 8 PM 12 A M 4 A M 8 A M 12 P M 4 PM 8 PM 12 A M 4 A M 8 A M 12 P M 4 PM 8 PM 12 A M 4 A M 8 A M 12 P M 4 PM 8 PM 12 A M 4 A M 8 A M 12 P M 4 PM 8 PM 12 A M 4 A M 8 A M 12 P M 4 PM 8 PM 12 A M 4 A M 8 A M 12 P M 4 PM 8 PM ruoHrep e muloV nairtsedeP ylkee WfotnecreP Hour of Week M T W Th F Sa Su Figure A-1.
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Case Studies 105 on a Wednesday, the weekly volume estimate would be about 7,500 pedestrians (100/0.0133 = 7,519) , a difference of about 1,800 pedestrians compared to the weekly estimate produced by the unadjusted factor using the general county pattern.
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From page 106... ...
106 Guidebook on pedestrian and Bicycle Volume data Collection Although the initial purpose was to provide baseline data on pedestrian and bicycle volumes, the Arlington County counting program has served additional purposes. For example, the measured activity patterns show that bicycles are used for various reasons.
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Case Studies 107 Case Study 3: San Francisco, California Pedestrian Volume Patterns Provide Data for a Community-Wide Demand Model The San Francisco Municipal Transportation Agency (SFMTA) and San Francisco County Transportation Authority (SFCTA)
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108 Guidebook on Pedestrian and Bicycle Volume Data Collection meters, proximity to a university campus, and traffic signals, and were negatively associated with steep slopes. The model equation was then used to estimate pedestrian volumes at all 8,100 intersections in San Francisco (see Figure A-7)
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Case Studies 109 reported crashes at each intersection during a 10-year period. Crash rates were also calculated by hour of the day.
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110 Guidebook on pedestrian and Bicycle Volume data Collection state without volunteer resources. Each community has a Local Count Coordinator (often from a local transportation agency)
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Case Studies 111 Source: Cascade Bicycle Club (2013)
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112 Guidebook on pedestrian and Bicycle Volume data Collection a rich set of information about trail use patterns. The City of Columbus funded the study, purchasing three passive infrared counters and installing them permanently at three locations.
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From page 113... ...
Case Studies 113 to MORPC, "The counts are meant to serve as a baseline to document changes over time, while also assisting with grant applications, providing information to elected officials, and supporting/ justifying budget decisions. The trail counts inform the process of evaluating whether to widen selected trails." Case Study 7: San Diego County Systematic Process Used to Select Permanent Count Sites The County of San Diego Health and Human Services Agency, San Diego Association of Governments, and San Diego State University have partnered to install automated pedestrian and bicycle counters throughout the region.
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114 Guidebook on Pedestrian and Bicycle Volume Data Collection Source: Nordback, Michael, and Janson (2013)
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From page 115... ...
Case Studies 115 Case Study 9: Minneapolis Counts Are Used to Map Pedestrian and Bicycle Volumes Throughout the Community The City of Minneapolis, Minnesota, began collecting annual pedestrian and bicycle counts in 2007. With the assistance of Transit for Livable Communities (TLC)
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From page 116... ...
116 Guidebook on Pedestrian and Bicycle Volume Data Collection 1.The pictured profiles are the mean values of the facilities belonging to each classification. Source: Miranda-Moreno et al.
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