Evaluating the resilience and recovery of public transit system using big data

Case study from New Jersey

Sandeep Mudigonda, Kaan Ozbay, Bekir Bartin

Research output: Contribution to journalArticle

Abstract

Analyzing resilience and vulnerability of public transit networks is extremely important in the context of natural disasters as they are essential for evacuation. In this study, the public transit systems in New Jersey based on their vulnerability, resilience, and efficiency during the recovery period following Hurricane Sandy were analyzed. Diverse traffic, infrastructure, events, and web-based sources of Big Data are applied. Due to the sparsity of public transit performance measures for vulnerability, recovery, and resilience, various measures from existing literature were adapted for public transit. Following Hurricane Sandy, the bus transit network of NJ Transit (NJT) recovered much faster than its rail network. This was observed because the road infrastructure recovered much faster as compared to rail and subway networks. Additionally, the most critical link for the NJT buses remained intact during the hurricane whereas rail and subway systems suffered loss of power for driving and signaling. Performance measures such as critical links identification, change in travel time, friability, and resilience triangles for specific bus routes on the NJT bus network were estimated. Transit agencies can use these measures and methodologies in planning and preparing for disasters to study route vulnerability and transit network resilience and standardize performance measures.

Original languageEnglish (US)
Pages (from-to)1-29
Number of pages29
JournalJournal of Transportation Safety and Security
DOIs
StateAccepted/In press - Mar 22 2018

Fingerprint

resilience
Hurricanes
Rails
Recovery
Subways
vulnerability
Disasters
Travel time
traffic infrastructure
performance
Planning
Big data
disaster
natural disaster
travel
road
infrastructure
efficiency
planning
event

Keywords

  • Big Data
  • natural disaster
  • public transit
  • recovery
  • resilience
  • vulnerability

ASJC Scopus subject areas

  • Transportation
  • Safety Research

Cite this

Evaluating the resilience and recovery of public transit system using big data : Case study from New Jersey. / Mudigonda, Sandeep; Ozbay, Kaan; Bartin, Bekir.

In: Journal of Transportation Safety and Security, 22.03.2018, p. 1-29.

Research output: Contribution to journalArticle

@article{84f800ac85a0475fba446460a84823e9,
title = "Evaluating the resilience and recovery of public transit system using big data: Case study from New Jersey",
abstract = "Analyzing resilience and vulnerability of public transit networks is extremely important in the context of natural disasters as they are essential for evacuation. In this study, the public transit systems in New Jersey based on their vulnerability, resilience, and efficiency during the recovery period following Hurricane Sandy were analyzed. Diverse traffic, infrastructure, events, and web-based sources of Big Data are applied. Due to the sparsity of public transit performance measures for vulnerability, recovery, and resilience, various measures from existing literature were adapted for public transit. Following Hurricane Sandy, the bus transit network of NJ Transit (NJT) recovered much faster than its rail network. This was observed because the road infrastructure recovered much faster as compared to rail and subway networks. Additionally, the most critical link for the NJT buses remained intact during the hurricane whereas rail and subway systems suffered loss of power for driving and signaling. Performance measures such as critical links identification, change in travel time, friability, and resilience triangles for specific bus routes on the NJT bus network were estimated. Transit agencies can use these measures and methodologies in planning and preparing for disasters to study route vulnerability and transit network resilience and standardize performance measures.",
keywords = "Big Data, natural disaster, public transit, recovery, resilience, vulnerability",
author = "Sandeep Mudigonda and Kaan Ozbay and Bekir Bartin",
year = "2018",
month = "3",
day = "22",
doi = "10.1080/19439962.2018.1436105",
language = "English (US)",
pages = "1--29",
journal = "Journal of Transportation Safety and Security",
issn = "1943-9962",
publisher = "Taylor and Francis Ltd.",

}

TY - JOUR

T1 - Evaluating the resilience and recovery of public transit system using big data

T2 - Case study from New Jersey

AU - Mudigonda, Sandeep

AU - Ozbay, Kaan

AU - Bartin, Bekir

PY - 2018/3/22

Y1 - 2018/3/22

N2 - Analyzing resilience and vulnerability of public transit networks is extremely important in the context of natural disasters as they are essential for evacuation. In this study, the public transit systems in New Jersey based on their vulnerability, resilience, and efficiency during the recovery period following Hurricane Sandy were analyzed. Diverse traffic, infrastructure, events, and web-based sources of Big Data are applied. Due to the sparsity of public transit performance measures for vulnerability, recovery, and resilience, various measures from existing literature were adapted for public transit. Following Hurricane Sandy, the bus transit network of NJ Transit (NJT) recovered much faster than its rail network. This was observed because the road infrastructure recovered much faster as compared to rail and subway networks. Additionally, the most critical link for the NJT buses remained intact during the hurricane whereas rail and subway systems suffered loss of power for driving and signaling. Performance measures such as critical links identification, change in travel time, friability, and resilience triangles for specific bus routes on the NJT bus network were estimated. Transit agencies can use these measures and methodologies in planning and preparing for disasters to study route vulnerability and transit network resilience and standardize performance measures.

AB - Analyzing resilience and vulnerability of public transit networks is extremely important in the context of natural disasters as they are essential for evacuation. In this study, the public transit systems in New Jersey based on their vulnerability, resilience, and efficiency during the recovery period following Hurricane Sandy were analyzed. Diverse traffic, infrastructure, events, and web-based sources of Big Data are applied. Due to the sparsity of public transit performance measures for vulnerability, recovery, and resilience, various measures from existing literature were adapted for public transit. Following Hurricane Sandy, the bus transit network of NJ Transit (NJT) recovered much faster than its rail network. This was observed because the road infrastructure recovered much faster as compared to rail and subway networks. Additionally, the most critical link for the NJT buses remained intact during the hurricane whereas rail and subway systems suffered loss of power for driving and signaling. Performance measures such as critical links identification, change in travel time, friability, and resilience triangles for specific bus routes on the NJT bus network were estimated. Transit agencies can use these measures and methodologies in planning and preparing for disasters to study route vulnerability and transit network resilience and standardize performance measures.

KW - Big Data

KW - natural disaster

KW - public transit

KW - recovery

KW - resilience

KW - vulnerability

UR - http://www.scopus.com/inward/record.url?scp=85044463691&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85044463691&partnerID=8YFLogxK

U2 - 10.1080/19439962.2018.1436105

DO - 10.1080/19439962.2018.1436105

M3 - Article

SP - 1

EP - 29

JO - Journal of Transportation Safety and Security

JF - Journal of Transportation Safety and Security

SN - 1943-9962

ER -