Othman, N. B., Jayaraman, V., Chan, W., Loh, Z. X. K., Rajendram, R., Mepparambath, R. M., Agrawal, P., Ramli, M. A., & Qin, Z. (2023). SUMMIT: A multi-modal agent-based co-simulation of urban public transport with applications in contingency planning. Simulation Modelling Practice and Theory, 126, 102760. https://doi.org/10.1016/j.simpat.2023.102760
Abstract:
In this article, we present SUMMIT (Singapore Urban Multi-Modal Integrated Transport Simulator), a multi-modal agent-based simulation platform for public transport calibrated using real world mobility data sets from Singapore. SUMMIT uses a co-simulation approach in order to model multiple modes of public transport in tandem with commuters seamlessly transitioning between different mode simulations. This is implemented through a message passing framework codenamed Fabric (Fast, Agent-Based, Reproducible, Integrated Co-simulation) which helps to align and synchronise the simulation as it transitions through the different simulation time steps. Three stand-alone simulators, each modelling a key mode in the Singapore public transport system, namely train, bus and taxi, are integrated with a commuter control model, which simulates the commuter behaviour and takes care of commuters’ transfer between different modes. We present one application of SUMMIT in public transport contingency planning, where train services are disrupted in multiple lines of Singapore Mass Rapid Transit (MRT) network. Different scenarios are simulated and key performance indicators are compared to help planners evaluate the efficacy of mitigation measures. The results show that bridging bus services, a commonly used mitigation measure, are effective in reducing crowd sizes within the train stations. However, we demonstrate that bridging buses could also result in worsening of commuters’ travel time due to over-demand for these buses. Our results also show early dissemination of information to commuters during a train service disruption could reduce the negative impacts of the disruption event significantly.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the National Research Foundation / Land Transport Authority - UMGC-L005
Grant Reference no. : UMGC-L005