Development of a maximum likelihood regression tree-based model for Predicting subway incident delay

作者：Weng, Jinxian^*; Zheng, Yang; Qu, Xiaobo; Yan, Xuedong

来源：Transportation Research Part C: Emerging Technologies , 2015, 57: 30-41.

DOI：10.1016/j.trc.2015.06.003

• Subway incidents
• Delay
• Maximum likelihood regression tree
• Accelerated failure time

This study aims to develop a maximum likelihood regression tree-based model to predict subway incident delays, which are major negative impacts caused by subway incidents from the commuter's perspective. Using the Hong Kong subway incident data from 2005 and 2009, a tree comprising 10 terminal nodes is selected to predict subway incident delays in a case study. An accelerated failure time (AFT) analysis is conducted separately for each terminal node. The goodness-of-fit results show that undeveloped model outperforms the traditional AFT models with fixed and random effects because it can overcome the heterogeneity problem and over-fitting effects. The developed model is beneficial for subway engineers looking to propose effective strategies for reducing subway incident delays, especially in super-large-sized cities with huge public travel demand.

• 出版日期2015-8
• 单位北京交通大学; 上海海事大学