Characterizing the Impacts of Phasing, Environment, and Temporal Factors on Pedestrian Demand at Traffic Signals

There is a need for more and higher quality data on pedestrian demand patterns for a number of applications in planning, transportation engineering, public health, and other areas. It is particularly desirable to better characterize the influence of daily, weekly, and annual variations; the impact of weather and special events; and the effects of changes in pedestrian phasing. This paper proposes and demonstrates a methodology for quantifying the relative demand for pedestrian service at a signalized intersection by using the percent of signal cycles per hour in which the pedestrian phase was actuated. Although this performance measure does not by itself provide a pedestrian count, it can be used as a surrogate to characterize how pedestrian volumes vary due to operating conditions. More importantly, since this technique does not require new sensors, the data can be collected at thousands of intersections across the nation where pedestrian push buttons are in use. This paper documents findings from over a year of data collection at a signalized intersection on a college campus. The effects of daily/weekly/annual variations, special events, weather (temperature and precipitation), seasonal changes in activity patterns, and changes in pedestrian signal phasing are documented. A Tobit model is used to account for the influences of these variables and understand how they co-influence pedestrian activity. The implementation of an exclusive pedestrian phase is associated with a 9% increase in pedestrian phase utilization at the intersection. This change is associated with a decrease in user cost relative to performing midblock crossings. The modeled impact of snowfall events adds further insight by showing that as the user cost of making midblock crossings increases, pedestrian activity at the intersection increases