IPOD Abstract for presentation (Poster or Podium) with a Paper in the Conference Proceedings
Data Sensing and Analytics
Kazi T. Huda, Master of Science in Civil Engineering (he/him/his)
Graduate Research Assistant
University of North Carolina Charlotte
Charlotte, NC, United States
Yuting Chen, PhD
Assistant Professor
UNC Charlotte
Charlotte, NC, United States
Don Chen, PhD, LEED A.P.
Professor
UNC Charlotte
Charlotte, North Carolina, United States
Srinivas S. Pulugurtha, P.E., F.ASCE
Professor & Research Director
The University of North Carolina at Charlotte (UNC Charlotte), United States
Yuting Chen, PhD
UNC Charlotte
Charlotte, North Carolina, United States
Highway work zones present significant safety concerns. This study aims to identify spatial and temporal factors that affect the number of highway work zone crashes in North Carolina (NC). The data from 2000 to 2020 were directedly obtained from NC Department of Transportation. Descriptive statistics, exploratory analysis, and time series analysis were employed in the analysis. It was found that crashes occurred most frequently in construction-related work zones, work zones with ongoing activities, clear weather conditions and dry surface conditions during daytime and right next to the work area. The time series analysis identified multiple trends and a seasonal pattern in monthly crash frequencies. Further, the study developed a Holt-Winters time series prediction model, which had a 16 percent mean absolute percentage error. This indicates that the crash month is an important factor in highway work zone crash modeling along with geometric and traffic variables.