TY - JOUR
T1 - Estimating Incident Duration Considering the Unobserved Heterogeneity of Risk Factors for Trucks Transporting HAZMAT on Expressways
AU - Hong, Jungyeol
AU - Tamakloe, Reuben
AU - Park, Dongjoo
AU - Choi, Yoonhyuk
N1 - Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2019.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Traffic accidents involving vehicles transporting hazardous materials (HAZMAT) on expressways not only delay traffic flow but can also cause large-scale casualties and socio-economic losses. Therefore, rapid response to and prevention of these accidents is important to minimize such loss. To ensure more efficient accident response, this study applied a random parameter hazard-based Weibull modeling approach to measure the relationship between crash characteristics and accident duration for trucks transporting HAZMAT. The study focuses on finding the key factors that have an impact on the accident duration of these vehicles as well as a statistical method to estimate the accident duration. The analysis is based on raw crash data from 2007 to 2017, obtained from the Korea Expressway Corporation, of crashes that involved HAZMAT trucks. The study found that crashes occurring during peak times of the day; crashes occurring on segments at the mainline, ramp, and roadways with a guardrail; and the number of vehicles involved in a crash, result in random parameters. In addition, the weather, season, crash severity, truck size, crash location, type of accident report, roadside features (e.g., guardrails), and status after a crash, can be used to explain the accident duration. The random parameters hazard-based model is found to have a better fit than a fixed model since it is able to capture the unobserved heterogeneity in the hazard function.
AB - Traffic accidents involving vehicles transporting hazardous materials (HAZMAT) on expressways not only delay traffic flow but can also cause large-scale casualties and socio-economic losses. Therefore, rapid response to and prevention of these accidents is important to minimize such loss. To ensure more efficient accident response, this study applied a random parameter hazard-based Weibull modeling approach to measure the relationship between crash characteristics and accident duration for trucks transporting HAZMAT. The study focuses on finding the key factors that have an impact on the accident duration of these vehicles as well as a statistical method to estimate the accident duration. The analysis is based on raw crash data from 2007 to 2017, obtained from the Korea Expressway Corporation, of crashes that involved HAZMAT trucks. The study found that crashes occurring during peak times of the day; crashes occurring on segments at the mainline, ramp, and roadways with a guardrail; and the number of vehicles involved in a crash, result in random parameters. In addition, the weather, season, crash severity, truck size, crash location, type of accident report, roadside features (e.g., guardrails), and status after a crash, can be used to explain the accident duration. The random parameters hazard-based model is found to have a better fit than a fixed model since it is able to capture the unobserved heterogeneity in the hazard function.
UR - http://www.scopus.com/inward/record.url?scp=85061909577&partnerID=8YFLogxK
U2 - 10.1177/0361198119827925
DO - 10.1177/0361198119827925
M3 - Article
AN - SCOPUS:85061909577
SN - 0361-1981
VL - 2673
SP - 232
EP - 242
JO - Transportation Research Record
JF - Transportation Research Record
IS - 2
ER -