Some coverage of our works on mass rapid transit system modeling
A*STAR researchers develop predictive model for mass-transit train overloading 24 November 2014 Researchers at A*STAR in Singapore have developed a model that uses smartcard ticket data to provide valuable predictive data on potential train overloading for Singapore’s public transport system. This will enable system planners to address critical bottlenecks as the system stretches to accommodate an expanding population. More than one million commuters—roughly 20% of Singapore’s population—use the mass rapid transit (MRT) system every day. With the population slated to increase by 26% by 2030, this growth needs to be managed in a way that prevents system delays and overcrowding. A suboptimal transport system could lead to dissatisfied customers and higher economic costs. To conduct their investigation, Christopher Monterola and colleagues at the A*STAR Institute of High Perf...