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Using Connected Vehicle Trajectory Data to Evaluate the Impact of Automated Work Zone Speed Enforcement

Work zone safety is a high priority for transportation agencies across the United States. Enforcing speed compliance in work zones is an important factor for reducing the frequency and severity of crashes. This paper uses connected vehicle trajectory data to evaluate the impact of automated work zon...

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Autores principales: Mathew, Jijo K., Li, Howell, Landvater, Hannah, Bullock, Darcy M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024971/
https://www.ncbi.nlm.nih.gov/pubmed/35458870
http://dx.doi.org/10.3390/s22082885
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author Mathew, Jijo K.
Li, Howell
Landvater, Hannah
Bullock, Darcy M.
author_facet Mathew, Jijo K.
Li, Howell
Landvater, Hannah
Bullock, Darcy M.
author_sort Mathew, Jijo K.
collection PubMed
description Work zone safety is a high priority for transportation agencies across the United States. Enforcing speed compliance in work zones is an important factor for reducing the frequency and severity of crashes. This paper uses connected vehicle trajectory data to evaluate the impact of automated work zone speed enforcement on three work zones in Pennsylvania and two work zones in Indiana. Analysis was conducted on more than 300 million datapoints from over 71 billion records between April and August 2021. Speed distribution and speed compliance studies with and without automated enforcement were conducted along every tenth of a mile, and the results found that overall speed compliance inside the work zones increased with the presence of enforcement. In the three Pennsylvania work zones analyzed, the proportions of vehicles travelling within the allowable 11 mph tolerance were 63%, 75% and 84%. In contrast, in Indiana, a state with no automated enforcement, the proportions of vehicles travelling within the same 11 mph tolerance were found to be 25% and 50%. Shorter work zones (less than 3 miles) were associated with better compliance than longer work zones. Spatial analysis also found that speeds rebounded within 1–2 miles after leaving the enforcement location.
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spelling pubmed-90249712022-04-23 Using Connected Vehicle Trajectory Data to Evaluate the Impact of Automated Work Zone Speed Enforcement Mathew, Jijo K. Li, Howell Landvater, Hannah Bullock, Darcy M. Sensors (Basel) Article Work zone safety is a high priority for transportation agencies across the United States. Enforcing speed compliance in work zones is an important factor for reducing the frequency and severity of crashes. This paper uses connected vehicle trajectory data to evaluate the impact of automated work zone speed enforcement on three work zones in Pennsylvania and two work zones in Indiana. Analysis was conducted on more than 300 million datapoints from over 71 billion records between April and August 2021. Speed distribution and speed compliance studies with and without automated enforcement were conducted along every tenth of a mile, and the results found that overall speed compliance inside the work zones increased with the presence of enforcement. In the three Pennsylvania work zones analyzed, the proportions of vehicles travelling within the allowable 11 mph tolerance were 63%, 75% and 84%. In contrast, in Indiana, a state with no automated enforcement, the proportions of vehicles travelling within the same 11 mph tolerance were found to be 25% and 50%. Shorter work zones (less than 3 miles) were associated with better compliance than longer work zones. Spatial analysis also found that speeds rebounded within 1–2 miles after leaving the enforcement location. MDPI 2022-04-09 /pmc/articles/PMC9024971/ /pubmed/35458870 http://dx.doi.org/10.3390/s22082885 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mathew, Jijo K.
Li, Howell
Landvater, Hannah
Bullock, Darcy M.
Using Connected Vehicle Trajectory Data to Evaluate the Impact of Automated Work Zone Speed Enforcement
title Using Connected Vehicle Trajectory Data to Evaluate the Impact of Automated Work Zone Speed Enforcement
title_full Using Connected Vehicle Trajectory Data to Evaluate the Impact of Automated Work Zone Speed Enforcement
title_fullStr Using Connected Vehicle Trajectory Data to Evaluate the Impact of Automated Work Zone Speed Enforcement
title_full_unstemmed Using Connected Vehicle Trajectory Data to Evaluate the Impact of Automated Work Zone Speed Enforcement
title_short Using Connected Vehicle Trajectory Data to Evaluate the Impact of Automated Work Zone Speed Enforcement
title_sort using connected vehicle trajectory data to evaluate the impact of automated work zone speed enforcement
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024971/
https://www.ncbi.nlm.nih.gov/pubmed/35458870
http://dx.doi.org/10.3390/s22082885
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