Development of a subway operation incident delay model using accelerated failure time approaches
mode - subway/metro, place - asia, operations - performance
Subway operation incidents, Accelerated failure time model, Hazard function, Incident delays
This study aims to develop a subway operational incident delay model using the parametric accelerated time failure (AFT) approach. Six parametric AFT models including the log-logistic, lognormal and Weibull models, with fixed and random parameters are built based on the Hong Kong subway operation incident data from 2005 to 2012, respectively. In addition, the Weibull model with gamma heterogeneity is also considered to compare the model performance. The goodness-of-fit test results show that the log-logistic AFT model with random parameters is most suitable for estimating the subway incident delay. First, the results show that a longer subway operation incident delay is highly correlated with the following factors: power cable failure, signal cable failure, turnout communication disruption and crashes involving a casualty. Vehicle failure makes the least impact on the increment of subway operation incident delay. According to these results, several possible measures, such as the use of short-distance and wireless communication technology (e.g., Wifi and Zigbee) are suggested to shorten the delay caused by subway operation incidents. Finally, the temporal transferability test results show that the developed log-logistic AFT model with random parameters is stable over time.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Weng, J., Zheng, Y., Yan, X. & Meng, Q. (2014). Development of a subway operation incident delay model using accelerated failure time approaches. Accident Analysis & Prevention, Vol. 73, pp. 12–19.