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When an unexpected metro disruption occurs, metro managers need to rescheduletimetables to avoid trains going into the disruption area, and transportpassengers stranded at disruption stations as quickly as possible. This paperproposes a two-stage optimization model to jointly make decisions for twotasks. In the first stage, the timetable rescheduling problem with cancellationand short-turning strategies is formulated as a mixed integer linearprogramming (MILP). In particular, the instantaneous parameters and variablesare used to describe the accumulation of time-varying passenger flow. In thesecond one, a system-optimal dynamic traffic assignment (SODTA) model isemployed to dynamically schedule response vehicles, which is able to capturethe dynamic traffic and congestion. Numerical cases of Beijing Metro Line 9verify the efficiency and effectiveness of our proposed model, and results showthat: (1) when occurring a disruption event during peak hours, the impact onthe normal timetable is greater, and passengers in the direction with fewertrain services are more affected; (2) if passengers stranded at the terminalstations of disruption area are not transported in time, they will rapidlyincrease at a speed of more than 300 passengers per minute; (3) compared withthe fixed shortest path, using the response vehicles reduces the total traveltime about 7%. However, it results in increased travel time for somepassengers.

Integrated optimization of train timetables rescheduling and response vehicles on a disrupted metro line