Abstract
Passengers on metro platforms can board a train only when the train has surplus capacity and the dwell time is sufficient, while the latter condition is omitted in previous studies. Taking into account the impacts of train capacity and dwell time on passengers boarding, this study develops a model on optimizing metro timetable to reduce passenger travel time and metro operating cost, through regulating trains' inter-station run-time, dwell time and headway. The NSGA-II algorithm is employed to obtain the near-optimal Pareto Frontier of the proposed model. To address insufficient dwell time scheduled in the timetable, three operating strategies are proposed and compared: a. sticking to nominal timetable; b. extending dwell time only; c. extending dwell time and recovering delay as soon as possible by compressing train inter-station run-time. Case studies on real-life metro line prove that some passengers cannot board the train during peak hours due to insufficient dwell time. In this context, strategy a brings low-quality service because passengers are stranded at platform even though the train has surplus capacity. In contrast, more passengers can board the train with strategies b and c because dwell time is extended for passengers' boarding when train has surplus capacity. Compared to strategy b, strategy c reduces the average in-vehicle time of passengers by 2.5% through compressing inter-station run-time to recover the delay. The timetable optimized based on strategy c saves total travel time of passengers by 3.1% without increasing operating cost when compared to the practical timetable.
Highlights
Metro is a key component of public transit systems, where passengers mainly concern their travel times and expect to arrive at their destinations as soon as possible [1]
As single objective optimization or converting different criterions into one objective cannot reflect the interests of stakeholders, we explore the interaction between different objectives through attaining the near-optimal Pareto front of passenger travel time and operating cost
The results demonstrate that EXDL and EXRE strategies contribute to the improvement on service quality, while EXRE strategies can reduce in-vehicle time by compressing inter-stations running times at the expense of slight increment in energy consumption
Summary
Metro is a key component of public transit systems, where passengers mainly concern their travel times and expect to arrive at their destinations as soon as possible [1]. Zhang et al [13] investigated the timetable optimization problem under congested conditions, and two non-linear models were formulated to design timetables with the objective of minimizing passenger travel time under the constraints of train operations, passenger boarding and alighting processes. The key to timetable formulation is to determine train inter-station runtimes, dwell times and service headways, to minimize operating cost and passenger travel time in the planning horizon Tp. B. In the first two scenarios, formulas (16-18) that applied in OTAB strategy are implemented to calculate effective loading time and the number of boarded passengers This is because passenger’s boarding process can be finished within the scheduled or prolonged dwell time. Passenger can never board train j which has no surplus capacity left at station n
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