Integrating Novel Connected Vehicle Event Data for Proactive Road Safety Improvement

Despite substantial progress in advancing road safety, fatalities and injuries from road crashes continue to pose a major public health concern globally. This dissertation explored the integration of novel Connected Vehicle (CV) hard braking event (HBE) data for proactive road safety improvement. It comprised four distinct but related studies. The first part of the dissertation presents a systematic review of existing studies on the use of CV events and related data in road safety research, focusing on data combinations, study contexts, and methodological approaches. The study adopted a modified PICO framework popularly used in medical science reviews by considering road crashes as a public health issue needing proactive intervention. A total of 21 papers were included in the final analysis based on a detailed synthesis of search results from multiple databases. The second part of the dissertation examined the correlation between historical crashes and HBE across different roadway functional classes and urbanized and rural areas in Alabama. The correlation was conducted at the segment level to provide a preliminary insight into the classes of roadways where HBE could be most appropriate as surrogates of historical crashes. The third part of the dissertation utilized multiple statistical approaches to investigate the potential integration of HBE as crash surrogates for proactive safety screening of arterial road networks. This study focused primarily on comparing the identified hotspots based on different crash types and HBE to justify the suitability of HBE as surrogates for proactive roadway screening. The fourth part of the dissertation employed an interpretable machine learning technique to examine the individual and interactive effects of HBE risk factors alongside traditional risk factors on crash frequency. This study provides insights into how the interaction of risk factors from CV, roadways, and traffic attributes could influence crash frequency, thereby providing additional information for proactive road safety improvement measures. Overall, this dissertation contributes to advancing road safety and provides valuable insights for the proactive evaluation of roadway safety performance by safety agencies to identify and remedy safety issues in advance, thereby limiting future crashes.

Grantor dc:publisher

University of Alabama Libraries

Year dc:date.issued

2024

Author dc:creator

• Okafor, Sunday

Advisor dc:contributor.advisor

• Jones, Steven L.

Contributors dc:contributor

• Hainen, Alexander
• Liu, Jun
• Penmetsa, Praveena
• Powell, Lawrence

Statement dc:rights

• All rights reserved by the author unless otherwise indicated.

Language dc:language.iso

en_US, English

Dc Identifier Other

1083481

OAI identifier oai:identifier

oai:ir.ua.edu:123456789/14405