Precise estimation of connections of metro passengers from Smart Card data

Hong, Sung-Pil; Min, Yunhong; Park, Myoung-Ju; Kim, KyungMin; Oh, Suk Mun

doi:10.1007/s11116-015-9617-y

Cited by 55 publications

(56 citation statements)

References 21 publications

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“…For the FSSS, we manually set SS to include 20 low demand stations, that is, SS = {10, 13,14,18,21,22,23,27,28,29,32,33,34,38,39,40,43,47, 48, 51}. The corresponding chromosome length is 200 (20 binary variables multiple 10 trains).…”

Section: Skip-stop Optimization Resultsmentioning

confidence: 99%

“…Munizaga and Palma [32] proposed a method to estimate metro passenger OD using GPS data and smart card data in Santiago. Hong et al [33] developed an approach that can match passenger trips to trains. Zhang et al [22] formulated a model to optimize the urban rail operation based on the detailed passenger transaction data during weekdays.…”

Section: Data Processing and Experiments Setupmentioning

confidence: 99%

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Optimized Skip-Stop Metro Line Operation Using Smart Card Data

Peitong¹,

Sun²,

Liu³

2017

Journal of Advanced Transportation

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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.

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Section: Skip-stop Optimization Resultsmentioning

confidence: 99%

Section: Data Processing and Experiments Setupmentioning

confidence: 99%

Optimized Skip-Stop Metro Line Operation Using Smart Card Data

Peitong¹,

Sun²,

Liu³

2017

Journal of Advanced Transportation

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“…Also, we demonstrate that crowding decreases the overall welfare of metro passengers. The model is tested on the real path choice data acquired by the recent algorithm by Hong et al (2015) known to detect the real path choice from Smart Card data in more than 90% of the cases. …”

mentioning

confidence: 99%

Does crowding affect the path choice of metro passengers?

Kim

Hong

et al. 2015

Transportation Research Part A: Policy and Practice

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“…

Abstract Based on an observation that tag-out times of passengers from Smart Card data were clustered, Hong et al [1] recently developed a precise algorithm that detects a logical path for metro passengers. The logical path means the sequence of train boarding and alighting.

…”

mentioning

confidence: 99%

Tracing a Logical Path of Passengers: A Case study of Seoul Metro Line 9

Kim¹,

Oh²,

Hong³

et al. 2015

Journal of the Korean society for railway

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Based on an observation that tag-out times of passengers from Smart Card data were clustered, Hong et al. [1] recently developed a precise algorithm that detects a logical path for metro passengers. The logical path means the sequence of train boarding and alighting. In this paper, we observe that tag-out times of passengers in Seoul Metro Line 9 were also clustered; we trace an actual logical path of passengers by applying the algorithm. As a result, we identify 91% of passengers successfully and find their logical paths; we also investigate passengers'preferences between express and local trains.

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Precise estimation of connections of metro passengers from Smart Card data

Cited by 55 publications

References 21 publications

Optimized Skip-Stop Metro Line Operation Using Smart Card Data

Optimized Skip-Stop Metro Line Operation Using Smart Card Data

Does crowding affect the path choice of metro passengers?

Tracing a Logical Path of Passengers: A Case study of Seoul Metro Line 9

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