Look for Patterns
Once you have the continuous count data, the next step is to plot it by time of day, day of week, and month of the year and look for patterns over the course of the day, the week, and the year. Do you see weekday peaks in traffic during the typical commuting times (7:00 AM to 9:00 AM and 4:00 PM to 6:00 PM)? Do you see higher traffic on weekdays or on weekends? Do you see very low volumes in winter and relatively high volumes in summer, or is traffic relatively consistent independent on season?
Below are some typical patterns of bicycle and pedestrian traffic volumes over the day and week as a percent of the Annual Average Daily Bicyclists/Pedestrians (AADBP).
This document details how to compute AADBP according to the AASHTO method in order to create traffic pattern plots.
After reviewing the existing non-motorized program (both what is being done and what is needed), Step 3 is to determine those traffic patterns that are to be monitored. Part of this determination will depend upon the functional road classes and bicyclist and pedestrian facilities of interest. For example, do State DOTs want to collect pedestrian and bicyclist count data on local streets, shared use paths, and pedestrian facilities that are considered off-system (i.e., not included on the State highway system)? In some cases, State DOT funding has been used for non-motorized projects on local streets and shared use paths through the Transportation Enhancements (TE) or Congestion Mitigation and Air Quality (CMAQ) funding categories.
Once the non-motorized network to be monitored has been defined, one should determine the most likely types of traffic patterns that are expected on this network. In most cases, the non-motorized network will include facilities that have a mix of commute, recreational, and utilitarian trips. Depending upon the relative proportions of these different trip types, distinct traffic patterns will emerge. These patterns should be used in the Step 4 to establish seasonal pattern groups.
The most common way to determine typical traffic pattern groups is through the visual analysis and charting of existing data. Continuous count data is preferred for this step, but short-duration counts (multiple full days, but not two-hour counts on a single day) may also be used with caution.