Development of an Emission-Based Selection Algorithm to Optimize Variable Message Sign Locations

Sharifi, Farinoush; Xu, Yanzhi (Ann)

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Development of an Emission-Based Selection Algorithm to Optimize Variable Message Sign Locations

2020-11-01
By Sharifi, Farinoush ; Xu, Yanzhi (Ann)

File Language:

English

Details

Creators:

Sharifi, Farinoush ; Xu, Yanzhi (Ann)
Corporate Creators:

Center for Advancing Research in Transportation Emissions, Energy, and Health. Texas A&M Transportation Institute
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
Subject/TRT Terms:
Publication/ Report Number:

165820-00005
Resource Type:

Tech Report
Geographical Coverage:

Texas ; United States
Edition:

Final Report 9/1/2019–8/31/2020
Corporate Publisher:

Center for Advancing Research in Transportation Emissions, Energy, and Health. Texas A&M Transportation Institute
Abstract:

This project devised an optimization method to site variable message signs (VMSs) for traffic incident management. The optimization objective is to maximize the economic utility of each VMS, considering both the monetary value of time and value of emissions. The method includes an integrated traffic and emissions simulation module and an optimization module that stochastically sample from real-world incident data. The method was applied to El Paso, Texas, as a case study. The case study demonstrated convergence of the optimization process, arriving at a stable set of optimal sites given various input assumptions. The optimally sited VMSs showed favorable societal return on investment in congestion relief and emissions reduction.
Format:

PDF
Funding:

69A3551747128
Download URL:

https://rosap.ntl.bts.gov/view/dot/68366/dot_68366_DS1.pdf
File Type:

[PDF - 1.49 MB]
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:99d3ce24a5f0db7ac17e127bdbac706ef2cd51131098b40f8593ba3d5ca52ad80a8f0ed08dd02c3a7c993e278aedb71281d302735af820e502c6135a3cf64a36

File Language:

English

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