01588677

Component

https://doi.org/10.3141/2586-06

Transportation planners and engineers need better spatial estimates of walking and cycling traffic to assess exposure to hazards, evaluate infrastructure investments, and locate facilities. Facility-demand models are potentially useful for generating spatial estimates of traffic volumes. Few facility-demand models have explored trade-offs between fully specified (i.e., exploratory) models and reduced-form models easily applied in the field. Presented are facility-demand models based on peak period (4 to 6 p.m.) counts of pedestrian and bicycle traffic in Minneapolis, Minnesota. The count database (n = 954 observations; 471 locations) has sufficient spatial density (~3 locations km–²) to develop spatially resolved models (i.e., ~100-m resolution). The modeling approach employs a stepwise linear regression method allowing for varying the spatial scale of independent (land use and transportation) variables. Compared were fully specified (statistically optimal) models and supervised, reduced-form models that included fewer variables based on theoretical validity. Reduced-form core models had modest goodness of fit (adjusted R²: ~.5) and included independent variables with large (industrial area and population density) and small (bicycle facilities, retail area, open space, transit stops) spatial scales. Also developed were reduced-form, time-averaged models for a subset of count sites having multiple observations (n = 84). With the use of reduced-form models (independent variables ranged from four to nine among models), block-level traffic estimates were generated (n = 13,886). Results suggest that reduced-form models perform nearly as well as fully specified models and are easier to apply and interpret. This work could be extended by assessing model performance when estimates of annual average traffic are used in model building.

01595162

16-5371

English

pp 48–58

2016

Transportation Research Record: Journal of the Transportation Research Board

9780309441322

Print

Figures (3) ; Maps; References (35) ; Tables (3)

Bicycling; Pedestrian traffic; Traffic volume; Transportation planning

Minneapolis (Minnesota)

Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting

PRP, TRIS, TRB, ATRI

Jan 12 2016 6:20PM

• Adaptive Walk Intervals
• Analysis of Road User Behavior and Safety During New York City’s Summer Streets Program
• Countdown Pedestrian Signals With and Without the Flashing Hand: Field Study
• Effect of Distractions on a Pedestrian’s Waiting Behavior at Traffic Signals: Observational Study
• Effectiveness of Changes in Street Layout and Design for Reducing Barriers to Walking
• How Far Is Too Far? Providing Safe and Comfortable Walking Environments
• Multiobjective Evaluation of Midblock Crosswalks on Urban Streets Based on TOPSIS and Entropy Methods
• Panic That Spreads Sociobehavioral Contagion in Pedestrian Evacuations
• Pedestrian Crosswalk Safety at Nonsignalized Crossings During Nighttime: Use of Thermal Video Data and Surrogate Safety Measures
• Pedestrian Gap Acceptance Behavior in Street Designs with Elements of Shared Space
• Road User Behaviors at Pedestrian Hybrid Beacons
• Road, Traffic, and Human Factors of Pedestrian Crossing Behavior: Integrated Choice and Latent Variables Models
• Variables Influencing Efficacy of Gateway In-Street Sign Configuration on Yielding at Crosswalks