In the context of traffic incident duration, specific hazard distributions are suggested by empirical and theoretical analyses using different incident datasets with different supplier TAK-700 incident types and locales. Previous studies have noted various distributions of incident duration, such as log-normal distribution, log-logistic distribution, Weibull distribution, and generalized F distribution. Studies have revealed that the distribution of incident durations can be viewed as log-normal [20, 21]. A different study [5] that focused

on the South Korean freeway system indicated that log-normal is an acceptable, but not the best, distribution for traffic durations. Other researchers have found that the log-logistic distribution is best for traffic incident duration/clearance time. Jones et al. [30] used AFT models with log-logistic distribution on freeway incident records in Seattle to investigate the factors affecting traffic incident duration time. Chung [31] used the log-logistic

AFT model to develop a traffic incident duration time prediction model; the resulting mean absolute percentage error (MAPE) showed that the developed model can provide a reasonable prediction based on a two-year incident duration dataset drawn from the Korea Highway Corporation on 24 major freeways in Korea. Using another dataset obtained from the Korea Highway Corporation, the log-logistic AFT model has also been used to analyze the critical factors affecting incident duration [5]. Qi and Teng [32] developed an online incident duration prediction model based on a log-logistic AFT model. Hu et al. [33] used a log-logistic AFT model to predict incident duration time for in-vehicle navigation systems based on Transport Protocol Experts Group data in London and obtained a reasonable result. Wang et al. [29] estimated traffic duration times by using a log-logistic AFT model based on traffic

incidents occurring on a freeway in China. The Weibull distribution has also been used in previous studies. Nam and Mannering [4] studied Batimastat three duration phases (i.e., detection/reporting, response, and clearance times), and the results revealed that the Weibull AFT model with gamma heterogeneity is appropriate for detection/reporting and response time, whereas the log-logistic AFT model is appropriate for clearance time. Kang and Fang [34] used the Weibull AFT model to predict traffic incident duration time in China. To test the goodness of fit, Alkaabi et al. [35] used the Weibull AFT model without gamma heterogeneity to analyze traffic incident clearance time in Abu Dhabi, United Arab Emirates. Tavassoli Hojati et al.