  When an unexpected metro disruption occurs, metro managers need to reschedule
timetables to avoid trains going into the disruption area, and transport
passengers stranded at disruption stations as quickly as possible. This paper
proposes a two-stage optimization model to jointly make decisions for two
tasks. In the first stage, the timetable rescheduling problem with cancellation
and short-turning strategies is formulated as a mixed integer linear
programming (MILP). In particular, the instantaneous parameters and variables
are used to describe the accumulation of time-varying passenger flow. In the
second one, a system-optimal dynamic traffic assignment (SODTA) model is
employed to dynamically schedule response vehicles, which is able to capture
the dynamic traffic and congestion. Numerical cases of Beijing Metro Line 9
verify the efficiency and effectiveness of our proposed model, and results show
that: (1) when occurring a disruption event during peak hours, the impact on
the normal timetable is greater, and passengers in the direction with fewer
train services are more affected; (2) if passengers stranded at the terminal
stations of disruption area are not transported in time, they will rapidly
increase at a speed of more than 300 passengers per minute; (3) compared with
the fixed shortest path, using the response vehicles reduces the total travel
time about 7%. However, it results in increased travel time for some
passengers.
