From Big Data to Smart Data

Efficient and reliable public transport is a linchpin for sustainable urban mobility. These days, modern smart card-based ticketing systems generate vast amounts of data on public transport usage every day. While such data is currently mainly used for various ridership analyses, the huge potential to employ it for simulation-based planning remained untapped so far.

 


Big Data transport simulation with MATSim from FCL on Vimeo.

 

The Mobility and Transportation Planning module applies diverse statistical models to extract critical behavioural and operational parameters to set up a Multi-Agent Transport SIMulation (MATSim) model. What sets the model apart from existing approaches is that it accounts for dynamic phenomena such as bus bunching, vehicle overcrowding and congestion. Hence, for the first time, public transport operators and transport planning authorities will be able to evaluate the impact of alternative vehicles types, new service lines and entire new network configurations not only with regards to ridership, but also service reliability, crowdedness and individual customer satisfaction.