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Leveraging probe data to model speeding on urban limited access highway segments: Examining the impact of operational performance, roadway characteristics, and COVID-19 pandemic.

Authors :
Marshall, Ennis
Shirazi, Mohammadali
Shahlaee, Amir
Ivan, John N.
Source :
Accident Analysis & Prevention. Jul2023, Vol. 187, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

• Using probe data, we estimated the traffic density information on limited access highways. • We used a mixed effect binomial model to link the odds of speeding to traffic density, roadway characteristics, and COVID-19 phases. • We analyzed and compared speeding in two U.S. states, Maine, and Connecticut. • We found that a better level of service such as A, or B (low density) results in higher odds of speeding. • We found that speeding substantially increased during COVID-19 stay-at-home orders and continued to happen even one year after the orders. Stay-at-home orders - imposed to prevent the spread of COVID-19 - drastically changed the way highways operate. Despite lower traffic volumes during these times, the rate of fatal and serious injury crashes increased significantly across the United States due to increased speeding on roads with less traffic congestion and lower levels of speed enforcement. This paper uses a mixed effect binomial regression model to investigate the impact of stay-at-home orders on odds of speeding on urban limited access highway segments in Maine and Connecticut. This paper also establishes a link between traffic density and the odds of speeding. For this purpose, hourly speed and volume probe data were collected on limited access highway segments for the U.S. states of Maine and Connecticut to estimate the traffic density. The traffic density was then combined with the roadway geometric characteristics, speed limit, as well as dummy variables denoting the time of the week, time of the day, COVID-19 phases (before, during and after stay-at-home order), and the interactions between them. Density, represented in the model as Level of Service, was found to be associated with the odds of speeding, with better levels of service such as A, or B (low density) resulting in the higher odds that drivers would speed. We also found that narrower shoulder width could result in lower odds of speeding. Furthermore, we found that during the stay-at-home order, the odds of speeding by more than 10, 15, and 20 mph increased respectively by 54%, 71% and 85% in Connecticut, and by 15%, 36%, and 65% in Maine during evening peak hours. Additionally, one year after the onset of the pandemic, during evening peak hours, the odds of speeding greater than 10, 15, and 20 mph were still 35%, 29%, and 19% greater in Connecticut and 35% 35% and 20% greater in Maine compared to before pandemic. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00014575
Volume :
187
Database :
Academic Search Index
Journal :
Accident Analysis & Prevention
Publication Type :
Academic Journal
Accession number :
163587394
Full Text :
https://doi.org/10.1016/j.aap.2023.107038