Multi-modal data fusion for big events

Abstract

Amsterdam, like many other metropolitan areas, faces a number of serious transportation related challenges. These range from severe congestion problems on the freeway and city road network, overloading of the train stations during peak hours, limited accessibility for goods distribution, parking regulation, massive (and sometimes high-risk) pedestrian flows during events, poor connectivity of public transport services, the high demand on cycling infrastructure and the fact that different transport modes compete over the same, scarcely available space. Specific situations in which many of these problems coincide are large scale events such as concerts, soccer matches and city-wide festivities. These events generate huge crowds which visit specific sites and arrive by many different modalities. Examples in Amsterdam are Kings' day, SAIL, and days in which multiple large public events take place simultaneously in specific areas. The first step to address these challenges and unravel the underlying traffic and travel processes is to collect and archive all relevant multi-modal transportation data.