  Estimating the travel time of any route is of great importance for trip
planners, traffic operators, online taxi dispatching and ride-sharing
platforms, and navigation provider systems. With the advance of technology,
many traveling cars, including online taxi dispatch systems' vehicles are
equipped with Global Positioning System (GPS) devices that can report the
location of the vehicle every few seconds. This paper uses GPS data and the
Matrix Factorization techniques to estimate the travel times on all road
segments and time intervals simultaneously. We aggregate GPS data into a
matrix, where each cell of the original matrix contains the average vehicle
speed for a segment and a specific time interval. One of the problems with this
matrix is its high sparsity. We use Alternating Least Squares (ALS) method
along with a regularization term to factorize the matrix. Since this approach
can solve the sparsity problem that arises from the absence of cars in many
road segments in a specific time interval, matrix factorization is suitable for
estimating the travel time. Our comprehensive evaluation results using real
data provided by one of the largest online taxi dispatching systems in Iran,
shows the strength of our proposed method.
