About

Road traffic jams continue to remain a major problem in most cities around the world, especially in developing regions resulting in massive delays, increased fuel wastage and monetary losses. Due to the poorly planned road networks, a common outcome in many developing regions is the presence of small critical areas which are common hot-spots for congestion; poor traffic management around these hotspots potentially results in elongated traffic jams. In this paper, we first present a simple automated image processing mechanism for detecting the congestion levels in road traffic by processing CCTV camera image feeds. Our algorithm is specifically designed for noisy traffic feeds with poor image quality. Based on live CCTV camera feeds from multiple traffic signals in Kenya and Brazil, we show evidence of this congestion collapse behavior lasting long time-periods across multiple locations. To partially alleviate this problem, we present a local de-congestion protocol that coordinates traffic signal behavior within a small area and can locally prevent congestion collapse sustaining time variant traffic bursts. Based on a simulation based analysis on simple network topologies, we show that our local de-congestion protocol can enhance road capacity and prevent congestion collapse in localized settings.

Publications

Road Traffic Congestion in the Developing World [pdf]
Vipin Jain, Ashlesh Sharma and Lakshminarayanan Subramanian
Proceedings of the 2nd ACM Symposium on Computing for Development (DEV), 2012

People

Jerome White
New York University Abu Dhabi

Vipin Jain
Courant Institute of Mathematical Sciences, New York University

Lakshminarayanan Subramanian
Courant Institute of Mathematical Sciences, New York University
Center for Technology and Economic Development, NYUAD