TY - JOUR
T1 - Exploring the combined effects of driving situations on freeway rear-end crash risk using naturalistic driving study data
AU - Wu, Kun Feng (Ken)
AU - Wang, Lan
N1 - Funding Information:
The authors would like to thank the reviewers for all of their careful, constructive and insightful comments and suggestions. The authors thank the Ministry of Science and Technology, Republic of China (Taiwan) , for financially supporting this research ( 108-2628-E-009-003-MY2 ). The authors wish also to acknowledge and thank the professionals at the Federal Highway Administration and Virginia Tech Transportation Institute for facilitating acquisition of the data.
PY - 2021/2
Y1 - 2021/2
N2 - The causes and the crash-generating processes of freeway rear-end (FRE) crashes are complicated. Previous studies have highlighted the many contributing factors to crash occurrences on freeways, such as traffic flow conditions, driver-following behavior, driver attention allocation, driver characteristics, the driving environment, and drivers’ interactions with surrounding vehicles, etc. Nevertheless, few studies have looked into the combined effects of these factors on FRE crash risk as a whole. This study focuses on characterizing the sequential crash generating process of the interactions between traffic flow conditions, roadway attributes, driver behavior, event attributes, and precipitating events in FRE crashes. A sequential modeling framework for modeling the sequential and combined effects on FRE crash risk was constructed by applying structural equation modeling (SEM). The Second Highway Strategic Research Program (SHRP2) Naturalistic Driving Study (NDS) data was utilized for this purpose as this data provides extensive information concerning what happened before crashes and near-crashes. A total of 17 and 433 FRE crashes and near-crashes, respectively, were included in this study. It was found that (1) FRE crashes were associated with the sequential and combined effects of those factors above; (2) certain types of speed oscillations were identified as precursors to sudden braking when vehicles ahead decelerated or stopped-and-went; and (3) many factors were identified as being associated with driver perception time and crash occurrence.
AB - The causes and the crash-generating processes of freeway rear-end (FRE) crashes are complicated. Previous studies have highlighted the many contributing factors to crash occurrences on freeways, such as traffic flow conditions, driver-following behavior, driver attention allocation, driver characteristics, the driving environment, and drivers’ interactions with surrounding vehicles, etc. Nevertheless, few studies have looked into the combined effects of these factors on FRE crash risk as a whole. This study focuses on characterizing the sequential crash generating process of the interactions between traffic flow conditions, roadway attributes, driver behavior, event attributes, and precipitating events in FRE crashes. A sequential modeling framework for modeling the sequential and combined effects on FRE crash risk was constructed by applying structural equation modeling (SEM). The Second Highway Strategic Research Program (SHRP2) Naturalistic Driving Study (NDS) data was utilized for this purpose as this data provides extensive information concerning what happened before crashes and near-crashes. A total of 17 and 433 FRE crashes and near-crashes, respectively, were included in this study. It was found that (1) FRE crashes were associated with the sequential and combined effects of those factors above; (2) certain types of speed oscillations were identified as precursors to sudden braking when vehicles ahead decelerated or stopped-and-went; and (3) many factors were identified as being associated with driver perception time and crash occurrence.
KW - NDS
KW - Rear-end crash
KW - SEM
KW - SHRP2
UR - http://www.scopus.com/inward/record.url?scp=85097144198&partnerID=8YFLogxK
U2 - 10.1016/j.aap.2020.105866
DO - 10.1016/j.aap.2020.105866
M3 - Article
C2 - 33276188
AN - SCOPUS:85097144198
SN - 0001-4575
VL - 150
JO - Accident Analysis and Prevention
JF - Accident Analysis and Prevention
M1 - 105866
ER -
