Faculty of Engineering, Architecture and Information Technology, The University of Queensland, Australia.
Accid Anal Prev. 2013 Mar;52:171-81. doi: 10.1016/j.aap.2012.12.037. Epub 2013 Jan 16.
Assessing and prioritising cost-effective strategies to mitigate the impacts of traffic incidents and accidents on non-recurrent congestion on major roads represents a significant challenge for road network managers. This research examines the influence of numerous factors associated with incidents of various types on their duration. It presents a comprehensive traffic incident data mining and analysis by developing an incident duration model based on twelve months of incident data obtained from the Australian freeway network. Parametric accelerated failure time (AFT) survival models of incident duration were developed, including log-logistic, lognormal, and Weibul-considering both fixed and random parameters, as well as a Weibull model with gamma heterogeneity. The Weibull AFT models with random parameters were appropriate for modelling incident duration arising from crashes and hazards. A Weibull model with gamma heterogeneity was most suitable for modelling incident duration of stationary vehicles. Significant variables affecting incident duration include characteristics of the incidents (severity, type, towing requirements, etc.), and location, time of day, and traffic characteristics of the incident. Moreover, the findings reveal no significant effects of infrastructure and weather on incident duration. A significant and unique contribution of this paper is that the durations of each type of incident are uniquely different and respond to different factors. The results of this study are useful for traffic incident management agencies to implement strategies to reduce incident duration, leading to reduced congestion, secondary incidents, and the associated human and economic losses.
评估和优先考虑减轻交通事件和事故对主要道路非经常性拥堵影响的成本效益策略，是道路网络管理者面临的一项重大挑战。本研究考察了与各种类型事件相关的许多因素对其持续时间的影响。通过开发基于从澳大利亚高速公路网络获得的十二个月事件数据的事件持续时间模型，对事件数据进行了全面的挖掘和分析。考虑了固定和随机参数的对数逻辑、对数正态和威布尔分布，以及具有伽马异质性的威布尔模型，建立了事件持续时间的参数加速失效时间（AFT）生存模型。威布尔 AFT 模型的随机参数适用于建模由碰撞和危险引起的事件持续时间。具有伽马异质性的威布尔模型最适合建模静止车辆的事件持续时间。影响事件持续时间的显著变量包括事件特征（严重程度、类型、拖曳要求等）以及事件位置、一天中的时间和交通特征。此外，研究结果表明基础设施和天气对事件持续时间没有显著影响。本文的一个重要贡献是，每种类型的事件的持续时间都是独特的，对不同的因素做出反应。本研究的结果有助于交通事件管理机构实施减少事件持续时间的策略，从而减少拥堵、二次事故以及相关的人员和经济损失。
