In the present scenario, developing countries like India are facing huge traffic congestion problems. Commuters have to wait long hours for arrival of buses, and when the bus arrives it is often found to be overcrowded, causing inconvenience in the commuters and discouraging them to use public transit system. The ITS(Intelligent Transport System) developed so far does provide arrival time of buses in real time but such systems are rare which provide the passenger occupancy in real time. Most of such installations use extortionate devices like passenger counting devices, cameras etc installed on the buses and at the bus stops. In this paper we propose a cost effective user participation based mode of collecting information about occupancy level of public transportation system using the potential of smartphones. Smartphones have inbuilt sensors like GPS which can be used to extract locational intelligence of the commuters. Hence, information gets crowdsourced from commuters and they themselves can provide information about occupancy level of a bus using their smartphones. The information so collected is stored in a historical database which is analyzed and processed to obtain occupancy level patterns for different routes on different days. The patterns observed are used to make predictions of occupancy level in a bus. Our results show that it is possible to achieve an accuracy to a level of 91.86 percent.
['Megha Chaudhary', 'Aneesh Bansal', 'Divya Bansal', 'Bhaskaran Raman', 'K. K. Ramakrishnan', 'Naveen Aggarwal']
Finding occupancy in buses using crowdsourced data from smartphones