A major government transport agency in South-East Asia servicing a population of 5.7 million with services like buses and metro. Responsible for planning, designing, building and maintaining the land transport infrastructure and systems, they aim to bring about a more inclusive public transport system. They aim to leverage technology to strengthen their rail and bus infrastructure to provide exciting options for future land transport.
The agency sought to explore graph analytics to optimize the scenario prediction of the public transport network to predict the potential impact of bus service modifications, to address possible issues of over-provisioning. Specifically, the client wishes to accurately predict measurable impacts such as the number of passengers affected, average journey time increase, if they were to modify, reduce, or remove existing bus services.