A Scalable Data Analytics and Visualization System for City-wide Traffic Signal Data-sets

Abstract

The advent of new traffic data collection tools such as high-resolution signalized intersection controller logs opens up a new space of possibilities for traffic management. In this work, we describe the high resolution datasets, apply appropriate machine learning methods to obtain relevant information from the said datasets and develop visualization tools to provide traffic engineers with suitable interfaces, thereby enabling new insights into traffic signal performance management. The eventual goal of this study is to enable automated analysis and help create operational performance measures for signalized intersections while aiding traffic administrators in their quest to design 21st century signal policies.