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对包括事件检测和恢复时间在内的交通事件总持续时间进行建模。

Modelling total duration of traffic incidents including incident detection and recovery time.

作者信息

Tavassoli Hojati Ahmad, Ferreira Luis, Washington Simon, Charles Phil, Shobeirinejad Ameneh

机构信息

School of Civil Engineering, The University of Queensland, Australia.

School of Civil Engineering, The University of Queensland, Australia.

出版信息

Accid Anal Prev. 2014 Oct;71:296-305. doi: 10.1016/j.aap.2014.06.006. Epub 2014 Jun 27.

Abstract

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an 'integrated database' is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.

摘要

交通事故是造成非经常性拥堵的关键因素,可能会导致严重延误。了解影响事故持续时间的因素对于实施有效的缓解策略非常重要。为了识别和量化影响因素的作用,本文提出了一种基于“综合数据库”历史数据研究事故总持续时间的方法。利用澳大利亚昆士兰州东南部网络中选定的高速公路路段建立事故持续时间模型。这些模型将事故检测和恢复时间作为事故持续时间的组成部分。采用基于风险的持续时间建模方法,将事故持续时间建模为各种影响交通事故持续时间的因素的函数。开发了参数化加速失效时间生存模型,以捕捉作为解释变量函数的异质性,包括固定参数和随机参数规范。分析表明,影响事故持续时间的因素包括事故特征(严重程度、类型、伤害、医疗需求等)、基础设施特征(路肩可用性)、一天中的时间和交通特征。结果表明,事件类型的持续时间各不相同,因此需要采取不同的应对措施来有效清除这些事件。此外,结果突出了随机参数模型所捕捉到的未观察到的事故持续时间异质性的存在,这表明在未来的建模工作中需要考虑其他因素。

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