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

TL;DR

This paper presents a two-stage optimization model for rescheduling metro train timetables and dynamically dispatching response vehicles during disruptions, improving response efficiency and passenger flow management.

Contribution

It introduces a novel joint optimization framework combining MILP for timetable rescheduling and SODTA for vehicle dispatching, considering real-time passenger flow data.

Findings

Response vehicles reduce total travel time by about 7%.

Passenger stranded rate increases rapidly without timely response.

Peak hour disruptions cause greater timetable impacts.

Abstract

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.