  This report explores the use of machine learning techniques to accurately
predict travel times in city streets and highways using floating car data
(location information of user vehicles on a road network). The aim of this
report is twofold, first we present a general architecture of solving this
problem, then present and evaluate few techniques on real floating car data
gathered over a month on a 5 Km highway in New Delhi.
