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Multi-Modal Data Fusion for Big Events [Research News]

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Multi-Modal Data Fusion for Big Events [Research News]


Amsterdam, like several alternative metropolitan areas, faces a variety of significant transportation related challenges. These vary from severe congestion issues on the freeway and town road network, overloading of the train stations during peak hours, limited accessibility for goods distribution, parking regulation, huge (and typically high-risk) pedestrian flows during events, poor connectivity of public transport services, the high demand on cycling infrastructure and the fact that completely different transport modes compete over the same, scarcely accessible area. Specific things in which several of these issues coincide are massive scale events like concerts, soccer matches and town-wide festivities. These events generate huge crowds which visit specific sites and arrive by many totally different modalities. Examples in Amsterdam are Kings' day, SAIL, and days in that multiple giant public events occur simultaneously in specific areas. The primary step to address these challenges and unravel the underlying traffic and travel processes is to gather and archive all relevant multi-modal transportation information.

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Multi-Modal Data Fusion for Big Events [Research News] - 4.9 out of 5 based on 71 votes

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