Time-varying effects of influential factors on incident clearance time using a non-proportional hazard-based model

被引:34
|
作者
Hou, Lin [1 ]
Lao, Yunteng [2 ]
Wang, Yinhai [2 ]
Zhang, Zuo [1 ]
Zhang, Yi [1 ]
Li, Zhiheng [1 ]
机构
[1] Tsinghua Univ, Dept Automat, Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China
[2] Univ Washington, Dept Civil & Environm Engn, Seattle, WA 98195 USA
基金
中国国家自然科学基金;
关键词
Traffic incident; Clearance time; Hazard-based model; Non-proportionality; Time-varying effect; PROPORTIONAL HAZARDS; DURATION MODELS; HETEROGENEITY; FREQUENCY;
D O I
10.1016/j.tra.2014.02.014
中图分类号
F [经济];
学科分类号
02 ;
摘要
Incident clearance time is a major performance measure of the traffic emergency management. A clear understanding of the contributing factors and their effects on incident clearance time is essential for optimal incident management resource allocations. Most previous studies simply considered the average effects of the influential factors. Although the time-varying effects are also important for incident management agencies, they were not sufficiently investigated. To fill up the gap, this study develops a non-proportional hazard-based duration model for analyzing the time-varying effects of influential factors on incident clearance time. This study follows a systematic approach incorporating the following three procedures: proportionality test, model development/estimation, and effectiveness test. Applying the proposed model to the 2009 Washington State Incident Tracking System data, five factors were found to have significant but constant (or time independent) effects on the clearance time, which is similar to the findings from previous studies. However, our model also discovered thirteen variables that have significant time-varying impacts on clearance hazard. These factors cannot be identified through the conventional methods used in most previous studies. The influential factors are investigated from both macroscopic and microscopic perspectives. The population average effect evaluation provides the macroscopic insight and benefits long-term incident management, and the time-dependent pattern identification offers microscopic and time-sequential insight and benefits the specific incident clearance process. Published by Elsevier Ltd.
引用
收藏
页码:12 / 24
页数:13
相关论文
共 50 条
  • [1] Semi-Parametric Non-Proportional Hazard Model with Time Varying Covariate
    Adeleke, Kazeem A.
    Abiodun, Alfred A.
    Ipinyomi, R. A.
    JOURNAL OF MODERN APPLIED STATISTICAL METHODS, 2015, 14 (02) : 68 - 87
  • [2] Using fractional polynomials and restricted cubic splines to model non-proportional hazards or time-varying covariate effects in the Cox regression model
    Austin, Peter C.
    Fang, Jiming
    Lee, Douglas S.
    STATISTICS IN MEDICINE, 2022, 41 (03) : 612 - 624
  • [3] The Hazard of Non-proportional Hazards in Time to Event Analysis
    Meuli, Lorenz
    Kuemmerli, Christoph
    EUROPEAN JOURNAL OF VASCULAR AND ENDOVASCULAR SURGERY, 2021, 62 (03) : 495 - 498
  • [4] Incorporating real-time weather conditions into analyzing clearance time of freeway accidents: A grouped random parameters hazard-based duration model with time-varying covariates
    Zeng, Qiang
    Wang, Fangzhou
    Chen, Tiantian
    Sze, N. N.
    ANALYTIC METHODS IN ACCIDENT RESEARCH, 2023, 38
  • [5] A comparative analysis of freeway crash incident clearance time using random parameter and latent class hazard-based duration model
    Islam, Naima
    Adanu, Emmanuel K.
    Hainen, Alexander M.
    Burdette, Steve
    Smith, Randy
    Jones, Steven
    Accident Analysis and Prevention, 2021, 160
  • [6] A comparative analysis of freeway crash incident clearance time using random parameter and latent class hazard-based duration model
    Islam, Naima
    Adanu, Emmanuel K.
    Hainen, Alexander M.
    Burdette, Steve
    Smith, Randy
    Jones, Steven
    ACCIDENT ANALYSIS AND PREVENTION, 2021, 160
  • [7] On estimation and tests of time-varying effects in the proportional hazards model
    Scheike, TH
    Martinussen, T
    SCANDINAVIAN JOURNAL OF STATISTICS, 2004, 31 (01) : 51 - 62
  • [8] The hazard of using the Poisson model to cope with immortal time bias in the case of time-varying hazard
    Rea, Federico
    Morabito, Gabriella
    Corrao, Giovanni
    Cantarutti, Anna
    BMC MEDICAL RESEARCH METHODOLOGY, 2024, 24 (01)
  • [9] Multi-level time-varying causality analysis of secondary conflicts based on hazard-based duration models
    Zhong, Hao
    Wang, Ling
    Huang, Helai
    Ma, Wanjing
    ACCIDENT ANALYSIS AND PREVENTION, 2024, 205
  • [10] Use of time-varying coefficients in a Cox regression model when the proportional hazard assumption is violated
    Maofeng Wang
    Weimin Li
    Nadir Yehya
    Garrett Keim
    Neal J. Thomas
    Intensive Care Medicine, 2018, 44 : 2017 - 2019