Public vehicle ETA system using machine learning

Abstract

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.Cataloged from PDF version of thesis.Includes bibliographical references.Traffic Jam impact our day to day life in more ways than we can think of. Our system aims to work on that particular problem to reduce the number of vehicles on the road by encouraging more people to get on public transport to make public transport more efficient for the people who are less keen on taking them due to time delays. Our system uses regression analysis on a data set collected on a specific route to estimate the arrival time of a public transport at a desired travel time. This gives the user a clear idea of the time required to travel between points and thus can utilize their time in an efficient way by not having to wait for a transport. The system uses a compiled data set to analyze historical data and then use regression analysis to predict the arrival time for particular location of the user.Md. Miraz KabirFarhan Sadik AkilOhinur Makamay MahmoodB. Computer Science and Engineerin