MPC Research Reports
Report Details

Title:	Utilizing Traffic Signal Pedestrian Push-Button Data for Pedestrian Planning and Safety Analysis
Authors:	Patrick Singleton, Amir Rafe, Prasanna Humagain, Ferdousy Runa, Ahadul Islam, and Michelle Mekker
University:	Utah State University
Publication Date:	Jun 2024
Report #:	MPC-24-525
Project #:	MPC-622
TRID #:	01923705
Keywords:	crash severity, data analysis, machine learning, pedestrian actuated controllers, pedestrian safety, pedestrian vehicle crashes, traffic signal controllers, traffic surveillance, traffic volume

Abstract

Transportation planning, traffic monitoring, and traffic safety analysis require detailed information about pedestrian volumes, but such data are usually lacking. Fortunately, recent research has demonstrated the accuracy of pedestrian volumes estimated from push-button data contained within high-resolution traffic signal controller log data. Such data are available continuously for many locations. This project takes advantage of these novel pedestrian traffic signal data to advance pedestrian traffic monitoring and improve pedestrian traffic safety by applying them as estimates of volume and exposure, often alongside advanced machine learning techniques. Through a series of five studies, we identify temporal patterns in pedestrian activity; study the accuracy of pedestrian volume estimation methods over time; use machine learning methods to improve the quality and completeness of pedestrian time-series data; analyze crashes to identify a "safety in numbers" effect for pedestrians; and apply a new deep learning model to better understand factors affecting pedestrian crash severity. Altogether, this work leverages novel pedestrian traffic signal data to further research and efforts in pedestrian traffic monitoring and safety.

How to Cite

Singleton, Patrick, Amir Rafe, Prasanna Humagain, Ferdousy Runa, Ahadul Islam, and Michelle Mekker. Utilizing Traffic Signal Pedestrian Push-Button Data for Pedestrian Planning and Safety Analysis, MPC-24-525. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2024.