Proactive Management of Mobility Impact of Interdependent Subsurface Utility and Roadway Construction through Incentives [supporting datasets]

Zhang, Zhuoran; Akinci, Burcu; Qian, Sean; Mobility21, Carnegie Mellon University

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Proactive Management of Mobility Impact of Interdependent Subsurface Utility and Roadway Construction through Incentives [supporting datasets]

2021-04-14
By Zhang, Zhuoran ; Akinci, Burcu ; Qian, Sean

[PDF-164.32 KB]

English

Details Supporting Files Publications Related Documents You May Also Like

Details:

Creators:

Zhang, Zhuoran ; Akinci, Burcu ; Qian, Sean

Zhang, Zhuoran ; Akinci, Burcu ; Qian, Sean Less -
Corporate Creators:

Mobility21, Carnegie Mellon University
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Case Studies Construction Scheduling Costs Crash Risk Forecasting Detours Dynamic Traffic Assignment Highway Bridges Pollutants Road Construction Travel Time Work Zones
Resource Type:

Dataset
Geographical Coverage:

United States ; Pittsburgh (Pennsylvania)

United States ; Pittsburgh (Pennsylvania) Less -
Corporate Publisher:

Mobility21, Carnegie Mellon University
Abstract:

This study aims to assist maintenance agencies in scheduling maintenance activities when assessing the impacts of conducting maintenance on a bridge and the cost of the detour, and the risk of crashes during the presence of the maintenance activity. Firstly, the authors build a predictive infrastructure maintenance expenditure model that predicts the reduced annual routine maintenance expenditure of one bridge whose structural conditions are improved due to the scheduled maintenance. Secondly, the authors applied a mesoscopic dynamic traffic assignment model to estimate the detour cost of work zones incurred by road users in high spatial and temporal resolution (miles and minutes) and a regional traffic network. The authors performed a case study on one real-world bridge in Pittsburgh. The simulated results provide an estimation of detour cost incurred by road users, including travel time and CO₂ emissions. Thirdly, the authors proposed a causal inference model based on regression discontinuity design (RDD) to estimate the traffic crash risk caused by the presence of work zones. It helps highway agencies to predict the safety impact of one scheduled maintenance activity.
Format:

ZIP
Funding:

69A3551747111
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha256:383a893b509cfc9e690d7f7eee8dd20e5ee1051b6216b08c31c7d4db1878ef1b
Download URL:

https://rosap.ntl.bts.gov/view/dot/61743/dot_61743_DS1.pdf
File Type:

Metadata File

json

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