RoadSoundSense: Acoustic sensing based road congestion monitoring in developing regions

Road congestion is a common problem all over the world. In many developed countries, automated congestion detection techniques have been deployed, that are used in road travel assisting applications. But these techniques are mostly inapplicable in many developing regions due to high cost and their assumptions of orderly traffic. Efforts in developing regions have been few. In this paper, we present RoadSoundSense, an acoustic sensing based technique, for near real time congestion monitoring on chaotic roads, at a moderate cost. We present the detailed design of an acoustic sensing hardware prototype, which has to be deployed by the side of the road to be monitored. This unit samples and processes road noise to compute various metrics like amount of vehicular honks and vehicle speed distribution, with speeds calculated from honks using differential Doppler shift. The metrics are sent to a remote server over GPRS every alternate minute. Based on the metric values, the server can decide the traffic condition on the road. Data from deployment of this prototype in six different Mumbai roads, validated against manually observed ground truth, shows feasibility of per minute congestion monitoring from a remote server. K-means clustering gives on average 90% accuracy to group unlabeled data on a new road into two clusters of congested and free-flow. Deployment data from one road for six days shows the temporal variation in traffic state for that road. Though we test our technique in Mumbai, we believe that most of our claims and experimental results can be extended to city roads of other developing regions as well.