Opportunistic sensing based detection of crowdedness in public transport buses

Abstract

This paper presents an opportunistic sensing based solution to detect crowdedness in public transportation buses. The solution uses data of accelerometer and Global Positioning System (GPS) sensors available in smartphones carried by the commuters. These data are used to accurately identify bus boarding event and whether a commuter got a seat during his/her trip. The solution is energy efficient as it uses power hungry GPS very conservatively and keeps it off majority of the times.The solution is evaluated using data collected over the arterial roads of Ahmedabad and Gandhinagar city. The length of routes varies from 25 to 45 kilometers. The effect of application penetration on crowdedness detection in buses is also evaluated. It is found that the penetration of 8 to 12% in commuter population can detect the crowdedness for more than 80% of route segments on the test routes. Further, the solution results in the energy-saving of about 50% compared to a solution that requires GPS data continuously. We also present the bus scheduling scheme that uses the historical data of bus-crowdedness to schedule the feeder buses on the crowded segments of the route.