Assisting Road Users Exposed to Nuisance Flooding

Hannoun, Gaby Joe; Murray‐Tuite, Pamela; Heaslip, Kevin; Fuentes, Antonio

doi:10.1061/jtepbs.0000391

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…As CAV deployment is expected to affect the transportation system performance, several studies have considered a mixed-traffic environment with different penetration rates of CAVs and estimated the level of service (LOS) ( 10, 32, 33 ). Several studies investigated the impacts of CAVs during natural disasters such as floods or earthquakes ( 11, 34 ). Zhu and Ukkusuri proposed an optimal car-following parameter estimation approach to calibrate the car-following behavior of connected vehicles (CV) in a no-disaster mixed-traffic environment and measured the travel time and traveled distance using connected vehicle (CV) data ( 10 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Zhu and Ukkusuri proposed an optimal car-following parameter estimation approach to calibrate the car-following behavior of connected vehicles (CV) in a no-disaster mixed-traffic environment and measured the travel time and traveled distance using connected vehicle (CV) data ( 10 ). Another study proposed a framework with CV technology that optimally routes the vehicles in a flooding scenario by applying the time-dependent hyper-star algorithm ( 11 ). Last, researchers also showed that a higher penetration of CVs and longer evacuation time improves the evacuation operation in a CV environment ( 34 ).…”

Section: Literature Reviewmentioning

confidence: 99%

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Evaluation of Transportation System Resilience in the Presence of Connected and Automated Vehicles

Ahmed

Dey

Fries

2019

Transportation Research Record: Journal of the Transportation R

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Large-scale natural disasters challenge the resilience of the surface transportation system. The objective of this research was to develop a resilience model of the surface transportation system with a mixed-traffic environment and considering varying Connected and Automated Vehicle (CAV) penetration scenarios. As deployment of CAVs is expected to improve traffic operations, a resilience model was developed in this research to evaluate the resilience performance of a transportation system with several CAV penetration levels (0%, 25%, 50%, 75%, and 100%) for a given budget and recovery time. The proposed resilience quantification model was applied on a roadway network considering several disaster scenarios. The network capacity in relation to trips at any phase of disaster was compared with the pre-disaster trips to determine the system resilience. The capacity variation and the travel time variation were also estimated. The analysis showed that the resilience of the transportation system improved with CAVs in relation to travel time and capacity improvement. Link travel times were significantly improved by higher CAV penetration rate. The findings also suggested that higher penetration of CAVs (i.e., 50% or more) increased the recovery costs. For example, the recovery costs needed for medium and large-scale disasters were 50% and 90% higher, respectively, compared with the recovery costs for a small-scale disaster. These higher costs were primarily for the repair and replacement of intelligent infrastructure required to support the operation of CAVs.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of Transportation System Resilience in the Presence of Connected and Automated Vehicles

Ahmed

Dey

Fries

2019

Transportation Research Record: Journal of the Transportation R

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Using crowdsourced data to estimate passenger vehicle travel delays from nuisance flooding

Zahura,

Goodall,

Chen

2024

Transportation Research Part D: Transport and Environment

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A Systematic Review: To Increase Transportation Infrastructure Resilience to Flooding Events

Watson

Ahn

2022

Applied Sciences

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This study investigated literature databases of Google Scholar and Scopus from 1900 to 2021 and reviewed relevant studies conducted to increase transportation infrastructure resilience to flood events. This review has three objectives: (1) determine which natural hazard or natural disaster had the most vulnerability studies; (2) identify which infrastructure type was most prevalent in studies related to flood resilience infrastructure; and (3) investigate the current stage of research. This review was conducted with three stages. Based on stage one, floods have been extremely present in research from 1981 to 2021. Based on stage two, transportation infrastructure was most studied in studies related to flood resilience. Based on stage three, this systematic review focused on a total of 133 peer-reviewed, journal articles written in English. In stage three, six research categories were identified: (1) flood risk analysis; (2) implementation of real-time flood forecasting and prediction; (3) investigation of flood impacts on transportation infrastructure; (4) vulnerability analysis of transportation infrastructure; (5) response and preparatory measures towards flood events; and (6) several other studies that could be related to transportation infrastructure resilience to flood events. Current stage of studies for increasing transportation resilience to flood events was investigated within these six categories. Current stage of studies shows efforts to advance modeling systems, improve data collections and analysis (e.g., real-time data collections, imagery analysis), enhance methodologies to assess vulnerabilities, and more.

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Assisting Road Users Exposed to Nuisance Flooding

Cited by 3 publications

References 26 publications

Evaluation of Transportation System Resilience in the Presence of Connected and Automated Vehicles

Evaluation of Transportation System Resilience in the Presence of Connected and Automated Vehicles

Using crowdsourced data to estimate passenger vehicle travel delays from nuisance flooding

A Systematic Review: To Increase Transportation Infrastructure Resilience to Flooding Events

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