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Strategies for Monitoring Multiuse Trail Networks
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Strategies for Monitoring Multiuse Trail Networks (2017)Strategies for Monitoring Multiuse Trail …Bicycle and Pedestrian Data Collection Manual (2017)Bicycle and Pedestrian Data C…Monitoring and Modeling of Urban Trail Traffic: Validation of Direct Demand Models in Minneapolis, Minnesota, and Columbus, Ohio (2016)Monitoring and Modeling of Ur…Nonmotorized Site Selection Methods for Continuous and Short-Duration Volume Counting (2015)Nonmotorized Site Selection M…Methods and Technologies for Pedestrian and Bicycle Volume Data Collection (2014)Methods and Technologies for …Methodology to Characterize Ideal Short-Term Counting Conditions and Improve AADT Estimation Accuracy Using a Regression-Based Correcting Function (2014)Methodology to Characterize I…Institutionalizing Bicycle and Pedestrian Monitoring Programs in Three States (2014)Institutionalizing Bicycle an…Incorporating Weather (2014)Incorporating WeatherEstimation of Annual Average Daily Bicycle Traffic with Adjustment Factors (2014)Estimation of Annual Average …Day-of-Year Scaling Factors and Design Considerations for Nonmotorized Traffic Monitoring Programs (2014)Day-of-Year Scaling Factors a…Estimating Mixed-Mode Urban Trail Traffic Using Negative Binomial Regression Models (2013)Estimating Mixed-Mode Urban T…Estimating Annual Average Daily Bicyclists (2013)Estimating Annual Average Dai…Classification of Bicycle Traffic Patterns in Five North American Cities (2013)Classification of Bicycle Tra…Automated Bicycle Counts (2010)Automated Bicycle CountsEstimating urban trail traffic: Methods for existing and proposed trails (2007)Estimating urban trail traffi…The effect of weather and climate on bicycle commuting (1999)Weather factor impacts on commuting to work by bicycle (2011)Weather or Not to Cycle (2011)Adding temporal information to direct-demand models: Hourly estimation of bicycle and pedestrian traffic in Blacksburg, VA (2018)Daily Bicycle Traffic Volume Estimation: Comparison of Historical Average and Count Models (2018)Minimizing Annual Average Daily Nonmotorized Traffic Estimation Errors: How Many Counters Are Needed per Factor Group? (2019)Weather and cycling—a first approach to the effects of weather conditions on cycling (2007)Development of a cycling data model: City of Vancouver case study (2015)Exploring temporal fluctuations of daily cycling demand on Dutch cycle paths: the influence of weather on cycling (2012)Toward a Better Estimation of Annual Average Daily Bicycle Traffic: Comparison of Methods for Calculating Daily Adjustment Factors (2016)Challenges and Opportunities of Emerging Data Sources to Estimate Network-Wide Bike Counts (2021)Exploring Data Fusion Techniques to Estimate Network-Wide Bicycle Volumes (2022)How the built environment affects physical activity (2002)Linking objectively measured physical activity with objectively measured urban form (2005)Travel and the Built Environment (2010)Spatial models of active travel in small communities: Merging the goals of traffic monitoring and direct-demand modeling (2017)Real-time prediction of public bike sharing system demand using generalized extreme value count model (2020)Use of Greenway Trails in Indiana (2004)Neighborhood Correlates of Urban Trail Use (2006)Urban trails and demand response to weather variations (2018)All work and no play? The role of instrumental and affective factors in work and leisure journeys by different travel modes (2005)Bicycling for Transportation and Health: The Role of Infrastructure (2009)Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies (2011)Facility-Demand Models of Peak Period Pedestrian and Bicycle Traffic: Comparison of Fully Specified and Reduced-Form Models (2016)Estimation of Average Annual Daily Bicycle Counts using Crowdsourced Strava Data (2020)Guide for the Development of Bicycle Facilities (1999)An environmental intervention to promote walking and cycling—the impact of a newly constructed Rail Trail in Western Sydney (2003)Performance Evaluation and Correction Functions for Automated Pedestrian and Bicycle Counting Technologies (2016)Random parameter models for estimating statewide daily bicycle counts using crowdsourced data (2020)Sources and Applications of Emerging Active Travel Data: A Review of the Literature (2021)Bicycle and Pedestrian Counts at Signalized Intersections Using Existing Infrastructure (2017)Development of Daily Adjustment Factors for Bicycle Traffic (2013)A sinusoidal model for seasonal bicycle demand estimation (2016)Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All Bicyclists (2019)
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References

  • 2013Estimating Annual Average Daily Bicyclists91 cited
  • 2013Classification of Bicycle Traffic Patterns in Five North American Cities83 cited
  • 2014Day-of-Year Scaling Factors and Design Considerations for Nonmotorized Traffic Monitoring Programs57 cited
  • 2007Estimating urban trail traffic: Methods for existing and proposed trails55 cited
  • 2013Estimating Mixed-Mode Urban Trail Traffic Using Negative Binomial Regression Models49 cited
  • 2014Estimation of Annual Average Daily Bicycle Traffic with Adjustment Factors44 cited
  • 2014Methodology to Characterize Ideal Short-Term Counting Conditions and Improve AADT Estimation Accuracy Using a Regression-Based Correcting Function39 cited
  • 2010Automated Bicycle Counts37 cited
  • 2014Methods and Technologies for Pedestrian and Bicycle Volume Data Collection35 cited
  • 2014Incorporating Weather28 cited
  • 2016Monitoring and Modeling of Urban Trail Traffic: Validation of Direct Demand Models in Minneapolis, Minnesota, and Columbus, Ohio25 cited
  • 2014Institutionalizing Bicycle and Pedestrian Monitoring Programs in Three States18 cited
  • 2017Bicycle and Pedestrian Data Collection Manual14 cited
  • 2015Nonmotorized Site Selection Methods for Continuous and Short-Duration Volume Counting8 cited

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