Data-driven disruption response planning for a Mass Rapid Transit System

Chunling Luo; Xinrong Li; Yuan Zhou; Aakil M. Caunhye; Umberto Alibrandi; Nazli Y. Aydin; Carlo Ratti; David Eckhoff; Iva Bojic

doi:10.1007/978-981-13-8683-1_21

Data-driven disruption response planning for a Mass Rapid Transit System

Chunling Luo^*, Xinrong Li, Yuan Zhou, Aakil M. Caunhye, Umberto Alibrandi, Nazli Y. Aydin, Carlo Ratti, David Eckhoff, Iva Bojic

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

This paper studies the disruption management of a Mass Rapid Transit (MRT) network with data obtained from transportation smart cards. We introduce an optimization model for the development of efficient bus bridging services to minimize the negative effects of MRT disruption. Compared with existing approaches, our model considers the available capacity of existing buses when designing the routes and headways/frequencies of bus bridging services. The proposed model is demonstrated through one case study that assumes MRT disruption in the central business district area of Singapore. The case study shows that our approach can effectively reduce the travel delay of commuters and increase the number of commuters that can be served.

Original language	English
Title of host publication	Smart Transportation Systems 2019
Editors	Xiaobo Qu, Lu Zhen, Lakhmi C. Jain, Robert J. Howlett
Publisher	Springer
Pages	205-213
Number of pages	9
ISBN (Print)	9789811386824
DOIs	https://doi.org/10.1007/978-981-13-8683-1_21
Publication status	Published - 7 Jun 2019
Event	2nd KES International Symposium on Smart Transportation Systems, KES-STS 2019 - St. Julians, Malta Duration: 17 Jun 2019 → 19 Jun 2019

Publication series

Name	Smart Innovation, Systems and Technologies
Volume	149
ISSN (Print)	2190-3018
ISSN (Electronic)	2190-3026

Conference

Conference	2nd KES International Symposium on Smart Transportation Systems, KES-STS 2019
Country/Territory	Malta
City	St. Julians
Period	17/06/19 → 19/06/19

Access to Document

10.1007/978-981-13-8683-1_21

Cite this

Luo, C., Li, X., Zhou, Y., Caunhye, A. M., Alibrandi, U., Aydin, N. Y., Ratti, C., Eckhoff, D., & Bojic, I. (2019). Data-driven disruption response planning for a Mass Rapid Transit System. In X. Qu, L. Zhen, L. C. Jain, & R. J. Howlett (Eds.), Smart Transportation Systems 2019 (pp. 205-213). (Smart Innovation, Systems and Technologies; Vol. 149). Springer. https://doi.org/10.1007/978-981-13-8683-1_21

@inproceedings{d2d1d1b6625f479b866dfa6ea10e0f5d,

title = "Data-driven disruption response planning for a Mass Rapid Transit System",

abstract = "This paper studies the disruption management of a Mass Rapid Transit (MRT) network with data obtained from transportation smart cards. We introduce an optimization model for the development of efficient bus bridging services to minimize the negative effects of MRT disruption. Compared with existing approaches, our model considers the available capacity of existing buses when designing the routes and headways/frequencies of bus bridging services. The proposed model is demonstrated through one case study that assumes MRT disruption in the central business district area of Singapore. The case study shows that our approach can effectively reduce the travel delay of commuters and increase the number of commuters that can be served.",

author = "Chunling Luo and Xinrong Li and Yuan Zhou and Caunhye, {Aakil M.} and Umberto Alibrandi and Aydin, {Nazli Y.} and Carlo Ratti and David Eckhoff and Iva Bojic",

year = "2019",

month = jun,

day = "7",

doi = "10.1007/978-981-13-8683-1_21",

language = "English",

isbn = "9789811386824",

series = "Smart Innovation, Systems and Technologies",

publisher = "Springer",

pages = "205--213",

editor = "Xiaobo Qu and Lu Zhen and Jain, {Lakhmi C.} and Howlett, {Robert J.}",

booktitle = "Smart Transportation Systems 2019",

address = "United Kingdom",

note = "2nd KES International Symposium on Smart Transportation Systems, KES-STS 2019 ; Conference date: 17-06-2019 Through 19-06-2019",

}

Luo, C, Li, X, Zhou, Y, Caunhye, AM, Alibrandi, U, Aydin, NY, Ratti, C, Eckhoff, D & Bojic, I 2019, Data-driven disruption response planning for a Mass Rapid Transit System. in X Qu, L Zhen, LC Jain & RJ Howlett (eds), Smart Transportation Systems 2019. Smart Innovation, Systems and Technologies, vol. 149, Springer, pp. 205-213, 2nd KES International Symposium on Smart Transportation Systems, KES-STS 2019, St. Julians, Malta, 17/06/19. https://doi.org/10.1007/978-981-13-8683-1_21

Data-driven disruption response planning for a Mass Rapid Transit System. / Luo, Chunling; Li, Xinrong; Zhou, Yuan et al.
Smart Transportation Systems 2019. ed. / Xiaobo Qu; Lu Zhen; Lakhmi C. Jain; Robert J. Howlett. Springer, 2019. p. 205-213 (Smart Innovation, Systems and Technologies; Vol. 149).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Data-driven disruption response planning for a Mass Rapid Transit System

AU - Luo, Chunling

AU - Li, Xinrong

AU - Zhou, Yuan

AU - Caunhye, Aakil M.

AU - Alibrandi, Umberto

AU - Aydin, Nazli Y.

AU - Ratti, Carlo

AU - Eckhoff, David

AU - Bojic, Iva

PY - 2019/6/7

Y1 - 2019/6/7

N2 - This paper studies the disruption management of a Mass Rapid Transit (MRT) network with data obtained from transportation smart cards. We introduce an optimization model for the development of efficient bus bridging services to minimize the negative effects of MRT disruption. Compared with existing approaches, our model considers the available capacity of existing buses when designing the routes and headways/frequencies of bus bridging services. The proposed model is demonstrated through one case study that assumes MRT disruption in the central business district area of Singapore. The case study shows that our approach can effectively reduce the travel delay of commuters and increase the number of commuters that can be served.

AB - This paper studies the disruption management of a Mass Rapid Transit (MRT) network with data obtained from transportation smart cards. We introduce an optimization model for the development of efficient bus bridging services to minimize the negative effects of MRT disruption. Compared with existing approaches, our model considers the available capacity of existing buses when designing the routes and headways/frequencies of bus bridging services. The proposed model is demonstrated through one case study that assumes MRT disruption in the central business district area of Singapore. The case study shows that our approach can effectively reduce the travel delay of commuters and increase the number of commuters that can be served.

UR - http://www.scopus.com/inward/record.url?scp=85067307649&partnerID=8YFLogxK

U2 - 10.1007/978-981-13-8683-1_21

DO - 10.1007/978-981-13-8683-1_21

M3 - Conference contribution

AN - SCOPUS:85067307649

SN - 9789811386824

T3 - Smart Innovation, Systems and Technologies

SP - 205

EP - 213

BT - Smart Transportation Systems 2019

A2 - Qu, Xiaobo

A2 - Zhen, Lu

A2 - Jain, Lakhmi C.

A2 - Howlett, Robert J.

PB - Springer

T2 - 2nd KES International Symposium on Smart Transportation Systems, KES-STS 2019

Y2 - 17 June 2019 through 19 June 2019

ER -

Data-driven disruption response planning for a Mass Rapid Transit System

Abstract / Description of output

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this