Rijurekha Sen, Andrew Cross, Aditya Vashistha, Venkat Padmanabhan, Edward Cutrell, and William Thies
Monitoring traffic density and speed helps to better manage traffic flows and plan transportation infrastructure and policy. In this paper, we present techniques to measure traffic density and speed in unlaned traffic, prevalent in developing countries, and apply those techniques to better understand traffic patterns in Bengaluru, India. Our techniques, based on video processing of traffic, result in about 11% average error for density and speed compared to manuallyobserved ground truth values. Though we started with intuitive and straight-forward image processing tools, due to a myriad of non-trivial issues posed by the heterogeneous and chaotic traffic in Bengaluru, our techniques have grown to be non-obvious. We describe the techniques and their evaluation, with details of why simpler methods failed under various circumstances. We also apply our techniques to quantify the congestion during peak hours and to estimate the gains achievable by shifting a fraction of traffic to other time periods. Finally, we measure the fundamental curves of transportation engineering, relating speed vs. density and flow vs. speed, which are integral tools for policy makers.
|Published in||Proceedings of ACM Symposium on Computing for Development (DEV 2013)|