Optimized Skip-Stop Metro Line Operation Using Smart Card Data

Abstract

Skip-stop operation is a low cost approach to improving the efficiency of metro operation and passenger travel experience. This paper proposes a novel method to optimize the skip-stop scheme for bidirectional metro lines so that the average passenger travel time can be minimized. Different from the conventional "A/B" scheme, the proposed Flexible Skip-Stop Scheme (FSSS) can better accommodate spatially and temporally varied passenger demand. A genetic algorithm (GA) based approach is then developed to efficiently search for the optimal solution. A case study is conducted based on a real world bidirectional metro line in Shenzhen, China, using the time-dependent passenger demand extracted from smart card data. It is found that the optimized skip-stop operation is able to reduce the average passenger travel time and transit agencies may benefit from this scheme due to energy and operational cost savings. Analyses are made to evaluate the effects of that fact that certain number of passengers fail to board the right train (due to skip operation). Results show that FSSS always outperforms the all-stop scheme even when most passengers of the skipped OD pairs are confused and cannot get on the right train.

A matheuristic for optimizing skip–stop operation strategies in rail transit lines

“…Constraints (2) (4) imply that if it is decided to pick up travellers from an origin-destination pair, the respective service s will have to stop at both stations. Constraints (5) indicate the nature of the variables used in the model.…”

“…This proposal was known as the A/b skip-stop plan (see [2]). As illustrative examples, the skip-stop operation mode has been used (and/or is being used) in practice in Santiago de Chile since 2001 [3], in bogota's Transmilenio system [4], in Los Angeles's Metro Rapid system [5], in Singapur's Transit Link [6] and in the bus line that connects the East zone of Seville area with its historic centre [7]. Figure 1 shows four train services that run along a railway corridor with seven stations.…”

Combinatorial Optimization of Service Order and Overtaking for Demand-Oriented Timetabling in a Single Railway Line

“…To the best of our knowledge, many demand-oriented timetable models have been developed. Besides, stop-skipping conditions have been considered in some of the models [5,6]. However, the combinatorial influence of train service order and overtaking condition on the timetabling is not fully elucidated in these existing studies.…”

“…Railway timetabling has been widely addressed by providing a closed analytical form for determining the involved time rates, e.g., travel times, dwell times [1], inversion times, buffer times [2], reserve times, and layover times [3]. Besides, some researchers have studied the problem of train timetable optimization to improve its performance by considering stop-skipping [4][5][6], overtaking, and service scheduling [7,8].…”

“…A Lagrangian relaxation-based heuristic algorithm is proposed to solve the model. Zhang [6] considered flexible skip-stop scheme and proposed a mixed-integer nonlinear programming model to minimize the average passenger travel time. Shen [55] and Zhang [56] proposed timetabling model to minimize the passenger travel time under congestion conditions.…”