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Time-varying effects of influential factors on incident clearance time using a non-proportional hazard-based model
Institution:1. Department of Civil and Urban Engineering, Center for Urban Science and Progress (CUSP), New York University (NYU), One MetroTech Center, 19th Floor, Office 1919Q, Brooklyn, NY 11201, USA;2. Department of Civil and Urban Engineering, Center for Urban Science and Progress (CUSP), New York University (NYU), One MetroTech Center, 19th Floor, Brooklyn, NY 11201, USA;3. Department of Civil and Urban Engineering, New York University (NYU), One MetroTech Center, 19th Floor, Office 1919N, Brooklyn, NY 11201, USA
Abstract: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.
Keywords:Traffic incident  Clearance time  Hazard-based model  Non-proportionality  Time-varying effect
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