The key aim of the MATSim Singapore project is to develop a large-scale, agent-and activity based transport demand model for Singapore. Large-scale means that all personal travel of an entire day in Singapore are being simulated. Agent-based means that Singapore’s population is being represented on the level of each individual by a synthetic population. And activity-based means that we derive travel demand from activities being conducted at distinct locations at distinct times of day.
Singapore’s transport system during the morning peak modelled with MATSim Singapore.
MATSim Singapore is designed to answer various transport and urban planning related questions. The range of transport related application stretches from predicting the ridership and reliability of new public transport services to various effects that an alternative road pricing scheme might evoke.
Compared to existing aggregated travel demand models, the key advantage is that MATSim is fully temporally dynamic and spatially disaggregated. This allows for example to capture the higher willingness to pay for road tolls of high income or time-constrained persons, to evaluate new mobility services such as car sharing and address new questions related to e-mobility, for example how electric cars can contribute to a smart grid. In the field of urban planning, it allows to assess the transport impact of new, more mixed used urban developments, compute detailed accessibility measures on the level of individual buildings which then can be used to estimate how transport infrastructure affects real estate values
MATSim Singapore has been implemented using the Open Source Software MATSim (www.matsim.org) which has been initiated by researchers at ETH Zurich and TU Berlin and is now also being further developed at the Future Cities Laboratory in Singapore. The development of Singapore required innovative extension to the source code such as a new public transport router, map matching of bus route tools and demand modelling routines.
To make the wealth of information provided by agent-based transport demand models, travel diary surveys and automatically collected public transport smart card records better accessible for planning practice, we developed a Decision Support System on urban mobility in a spatial database. Using business analytics software as a front end, the system allows explorative, interactive analysis and visualisation. We established this new Decision Support Sytem an integral part of MATSim Singapore. This will support to bridge the gap between research and practice when it comes to applications of large-scale, agent-based transport demand models.