Abstract
Modern nations consider the free flow of citizens and goods as a key component of their sustained economical development. Subsequently, optimizing (reducing) travel times has an important global impact on saving time and reducing prices. The availability of big data sources (e.g.: GPS records) offers the possibility to analyze historical trends, in order to predict accurate travel times for future travels.
Throughout this seminar, the problem of routing in transportation networks will be tackled from a data analysis perspective. Machine learning methods which build statistical models from historical traffic data will be assessed and presented.
A list of state of the art publications focusing on traffic management, efficient routing and estimation of travel times is provided to students, who will prepare in turn for presenting those studies in the classroom.
Instructor: Josif Grabocka