  The goal of the IARAI competition traffic4cast was to predict the city-wide
traffic status within a 15-minute time window, based on information from the
previous hour. The traffic status was given as multi-channel images (one pixel
roughly corresponds to 100x100 meters), where one channel indicated the traffic
volume, another one the average speed of vehicles, and a third one their rough
heading. As part of our work on the competition, we evaluated many different
network architectures, analyzed the statistical properties of the given data in
detail, and thought about how to transform the problem to be able to take
additional spatio-temporal context-information into account, such as the street
network, the positions of traffic lights, or the weather. This document
summarizes our efforts that led to our best submission, and gives some insights
about which other approaches we evaluated, and why they did not work as well as
imagined.
