The provision of real-time information for passengers in metro networks case studies : London and Hong Kong

This study looks at discovering information about the dynamics of a metro network, in real-time, using entry and exit data from the passengers’ smart cards. The data shows to be a valuable source of information about the current conditions of the network for both operators and passengers. An algorithm was developed which used real-time data to determine journey time characteristics, and to determine deviations from normal travel time and the extent to which these constitute a delay. This study focuses on the London Underground network and the Hong Kong MTR network as case studies to test the algorithm using the data produced by the automated ticketing systems. It aims to mine the data to provide information that can be used by passengers of the network. This information can lead to passengers knowing optimal routes, a realistic travel time and the number of minutes a delay may cost them; when the delay may be caused by congestion or service problems. Operationally this can allow for delay status reports to be more realistic, dynamic and responsive to crowding and provide information to the operators about the dynamics of the network in realtime.