Abstract:
Traffic jam in Dhaka city, the capital city of Bangladesh and one of the most densely populated cities in the world, is one of the major problems for the commuters. The city dwellers have been experiencing intolerable traffic jam every day. Though the authority is trying to reduce the traffic congestion by building new roads and enforcing new rules for vehicles on the roads, unfortunately, they do not result in any visible improvement of the condition. The main reason is the inability to assess and predict the traffic condition of the road in real-time. Due to huge infrastructural cost, the city does not have the facility to collect traffic data by deploying sensors. In this thesis, we overcome this limitation by exploiting mobile phone call details record (CDR) data collected by mobile phone operators for billing purpose. We propose a methodology to estimate travel time between any two major locations of Dhaka city from the aggregated information of a high volume of users’ mobile phone CDR data. Our experimental results based on real CDR dataset of 2.87 millions of users of the largest mobile operator, Grameenphone Ltd., show that we can effectively predict travel time between any two major junctions and any two minor locations of the city with an average accuracy of 87% and 76% respectively.
