Maximizing number of direct trips for a skip-stop policy in metro systems

Salama, Mohamed; Abdelhafiez, Ehab A.; Shalaby, Mohamed

doi:10.1016/j.cie.2019.106091

Cited by 9 publications

(12 citation statements)

References 19 publications

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“…Research has been conducted on skip-stop strategy and express/local strategy to maintain the high scheduled speed of urban railway ( 10 ). Skip-stop strategy consists of “skipped stations” where certain types of trains stop and “transfer stations” where all types of trains stop ( 11 – 20 ). Express/local strategy operates express trains that stop only at high-demand stations and local trains that stop at all stations ( 21 – 24 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Most studies developed skip-stop strategy to minimize travel time ( 1 , 11 – 13 , 16 , 17 , 19 , 20 ). These studies divided travel time into waiting time, transfer time, and in-vehicle time to minimize travel time.…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, issues associated with equity have not been considered in most skip-stop research. Typically, most skip-stop research aims to maximize efficiency by reducing total travel time, operating costs, or energy consumption, without considering equity issues ( 9 – 27 ). Paradoxically, passengers at some origin stations may experience inequitable services, that is, travel time disparities, as a result of strategies that only improve efficiency.…”

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confidence: 99%

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Multi-Objective Optimization for Skip-Stop Strategy Based on Smartcard Data Considering Total Travel Time and Equity

Han

Lee

Kim

2021

Transportation Research Record: Journal of the Transportation R

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With the rise of urban sprawl, urban railways extend out further to the city’s outer district, installing additional stations. Passengers who travel from the outer district to the center of the city therefore experience long travel times. Although skip-stop strategy helps save total travel time, deviation of travel time among all origin–destination pairs may be increased, leading to equity problems. This study aims to minimize the inequity and total travel time through train stop planning and train scheduling. A coefficient of variation is adopted as a measure of inequity. The problem is formulated as a multi-objective mixed integer nonlinear programming model. Origin–destination demand is extracted from smartcard data and a case study of four urban railway lines in Seoul is conducted. The results indicate that the number of transfer stations for equity-oriented skip-stop strategy is smaller than that for total-travel-time-oriented skip-stop strategy. We also discover that as the number of transfer stations rises, inequity increases and total travel time is reduced. For skip-stop strategy considering total travel time and equity simultaneously, average total travel time and the average deviation are reduced by up to 10.3% and 10.6%, respectively, compared with those of all-stop strategy. We analyze the gradient of Pareto optimal sets to find out which factors (equity or total travel time) are more significant. Skip-stop strategy on lines 5 and 9 can be designed based on equity, while line 4 can be planned based on total travel time.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

mentioning

confidence: 99%

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Multi-Objective Optimization for Skip-Stop Strategy Based on Smartcard Data Considering Total Travel Time and Equity

Han

Lee

Kim

2021

Transportation Research Record: Journal of the Transportation R

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“…This problem was formulated differently in [36] with the consideration of the constraint on the transfers which can be made only at AB stations for those passengers whose destinations are skipped and a genetic algorithm was developed to generate optimal schedule. Salama et al [37] presents a model to maximize the number of direct trips in a stop-skipping policy given than the number of stations to be skipped has been already determined.…”

Section: Literature Reviewmentioning

confidence: 99%

Rebalancing the Passenger Flow Between Subways and Buses: A Periodic Stop-Skipping Strategy

Yang

Lai

et al. 2020

IEEE Access

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Urban subway, because of its speed and punctuality, receives considerable popularity and injects great vitality into the city's economic development. However, overcrowding frequently observed in subway carriages during peak hours potentially leads to an increase in accident risk, while there are still some spaces available in buses in some situations. Such imbalance between the two public transits, which was examined based on the load ratios reported for Beijing public transits in a map App, motives us to develop a periodic stop-skipping strategy to shift the excessive demand from subway to bus to alleviate the overloaded situations while to reduce the unwanted influence on the passengers. To achieve such bi-objectives, we propose a non-linear model with consideration of the passengers' choice under the stop-skipping operation. To avoid to exhaustively examine all stop patterns, the stop patterns required to evaluate are identified theoretically. We develop a genetic algorithm to generate the optimal plan, with the triggering mechanism devised to give the priority to the safety objective. With the calibrated choice model, four sets of numerical experiments were performed to evaluate the proposed approach. The results indicate that our approach can effectively alleviate the overcrowding while the efficiency can be increased in some circumstances as the remaining bus capacity is utilized. The optimality and the efficiency of the algorithm and the effectiveness of the triggering mechanism were also verified. The proposed approach can be applied as an effective and economical way to rebalance the peak demand when the bus capacity is surplus.

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“…Economic parameters were employed in the model to generate the cost function. Abdelhafiez et al [11], Cao et al [12], and Salama et al [13] compared the performances of different A/B stop-skipping strategies.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Urban Metro Management Approach for Crowd Density Control

Zhou

Zheng

Cen

et al. 2021

Journal of Advanced Transportation

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Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the arrival of crowds. A two-layer transportation network, which includes a pedestrian network and the urban metro network, is proposed to better simulate the crowd gathering process. Urban smartcard data is used to obtain actual passenger travel demand. The objective function of the developed model minimizes the passengers’ total waiting time cost and travel time cost under the pedestrian density constraint and the crowd density constraint. The developed model is tested in an actual case of large crowding events occurred in Shenzhen, a major southern city of China. The obtained train stop-skipping schemes can effectively maintain crowd density in its safety range.

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Maximizing number of direct trips for a skip-stop policy in metro systems

Cited by 9 publications

References 19 publications

Multi-Objective Optimization for Skip-Stop Strategy Based on Smartcard Data Considering Total Travel Time and Equity

Multi-Objective Optimization for Skip-Stop Strategy Based on Smartcard Data Considering Total Travel Time and Equity

Rebalancing the Passenger Flow Between Subways and Buses: A Periodic Stop-Skipping Strategy

A Data-Driven Urban Metro Management Approach for Crowd Density Control

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