MATSim Singapore
Jan 2015 - Mar 2017
Understanding and evaluating large-scale transport policy interventions
Transport systems of today are changing rapidly. As ride-sharing gathers momentum, companies are continuing to offer an array of services that appeal to different population segments. The improvement of non-motorised accessibility in neighbourhoods can dramatically affect the number of motorised trips people make in the day. The convenience that internet shopping and deliveries offer are reducing the number of discretionary trips people make. Moreover, government policies could well be the game changer in mode share and transport system performance overnight. On the horizon, autonomous vehicles are promising its own universe of prospects and pitfalls.
With these rapid developments, it has become increasingly important to anticipate the reaction of individual users to these interventions, and how this translates, from the bottom-up, into larger-scale system performance. MATSim Singapore attempts to reproduce the activity and travel decision-making behaviour of an entire commuting population, and the performance of the transport in response to these demands.
In a collaboration with the Urban Redevelopment Authority and the Land Transport Authority of Singapore, MATSim Singapore is a pioneering effort to put the latest transport planning tools from the research domain in the hands of planners, for them to understand and evaluate the effects of land-use and transport policy interventions on transport system performance.
The simulation model was built using the latest available data sets provided by various authorities in Singapore. It forms the basis for further exploratory studies, testing the feasibility of autonomous vehicles and motorcycles in the Singapore urban environment.
Publications
- chevron_right Sun, L., Erath, A., 2015. A Bayesian network approach for population synthesis. Transportation Research Part C: Emerging Technologies 61, 49–62.
- chevron_right Vitins, B., Erath, A., Axhausen, K.W., 2016. Integration of a Capacity Constrained Workplace Choice Model: Recent Developments and Applications for an Agent-Based Simulation in Singapore (Work Report). Singapore.
- external page call_made Sun, L., Erath, A., Cai M., 2018. A hierarchical mixture modeling framework for population synthesis. Transportation Research Part B: Methodological 114, 191-212.