Civil Engineering


Date of this Version



A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Civil Engineering, Under the Supervision of Professor Anuj Sharma. Lincoln, Nebraska: July 2011

Copyright 2011 Jacob N. Schmitz


Pedestrian countdown timers are becoming common at urban and suburban intersections. The added information that pedestrian countdown timers provide to pedestrians can also be used by approaching drivers. A before and after case study on the effects that pedestrian countdown timers have on safety and efficiency of operations was performed at two signalized intersections in Lincoln, Nebraska. The effects on both drivers and pedestrians were analyzed. Performance measures for pedestrian analysis include pedestrian compliance and average pedestrian walking speed. Performance measures for the driver analysis include probability of stopping and speed at the stop bar of vehicles during the yellow phase (vehicles passing through the intersection during the yellow phase). Data was collected using a Wide Area Detector and a Pan-Tilt-Zoom video camera. Data was collected using state of the art data collection software, Wonderware, which displayed all traffic and pedestrian signal information, vehicle detections, individual vehicle speeds and distances from stop bar, and the video from the PTZ camera all on one computer screen.

Statistical models were estimated to understand the effects that pedestrian countdown timers have on the performance measures. The resulting models identified statistically significant factors that affected the performance measures. Pedestrian countdown timers were found to increase pedestrian walking speed by 0.2 ft/sec, and decrease speed at the stop bar of vehicles during the yellow phase by 1.0 mi/hr. The probability of stopping curve became steeper after installation of pedestrian countdown timers, but the difference in probability of stopping was not statistically significant.

Advisor: Anuj Sharma