Spatio-Temporal Analysis of Highway Congestion and Accidents: A Case Study of Interstate 285 in Georgia

<p>Road traffic crashes threaten thousands of drivers every day and significant efforts have been put forth to reduce the number of traffic crashes and their impact. Traffic congestion could be both a result of and a contributing factor to traffic crashes. The aim of this study is to investigate spatio-temporal traffic congestion and crash patterns to gain a better understanding of the causation of congestion and accidents, and their interaction. The Interstate 285 (I-285) in Georgia was used as a case study. With the aid of Geographic Information Systems (GIS), spatial clustering and densities of accidents were performed by following Anselin Local Moran’s I method of spatial auto correlation. The results indicated that the location of high-high accident clusters was in the northern half of the I-285 for all crash types. Additionally, geometric and traffic-related variables were correlated with accidents using logistic regression. The results showed that road segments involving merging, diverging, or weaving lanes had a positive correlation with the number of accidents. Specifically, the merging segments exhibited the highest crash frequency, followed by weaving and diverging segments. On the other hand, the road curvature did not play a significant role in crash occurrence, which is likely due to the gentleness of the road curvatures along the I-285 loop. However, the impact of acceleration on crash frequency remained inconclusive. It appeared that a lower average traffic speed correlated with a higher crash frequency, which may be due to a slow-down condition prior to crash occurrence.</p>

Name thesis:degree_name

Master of Science in Construction Engineering

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Construction Engineering

Year dc:date.available

2019

Author dc:creator

• Zhan-Moodie, Melodi

Contributors dc:contributor

• Jidong Yang

• congestion map
• Transportation Engineering

Repository record dc:identifier

https://digitalcommons.kennesaw.edu/msce_etd/3

OAI identifier oai:identifier

oai:digitalcommons.kennesaw.edu:msce_etd-1003