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Analysing freeway traffic- incident duration using an Australian data set

机译:使用澳大利亚数据集分析高速公路交通事故持续时间

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This paper investigates incident duration and identifies contributing variables for Australian conditions. The paper presents a new framework for comprehensive traffic-incident data mining and analysis towards an incident delay model and travel-time reliability modelling. Twelve months of data were collected, analysed and the results are presented in this paper. The findings suggest that debris, breakdown and multiple-vehicle crashes are the major sources of incidents on freeways. Furthermore, freeway incident duration varied across the types of incident and time of the day, and whether it was a week day or weekend day. However, there were no significant differences in relation to day, week or month of the year. Significant variables on incident duration were identified using an ANOVA test for each type of incident. In addition, the findings of this study reveal a high variance of incident duration within each incident type. A variety of probability distribution functions were employed to test the best model for the duration frequency distribution for each category of incident. Log-normal distribution was found to be more appropriate for crashes, but log-logistic distribution was more appropriate for hazards and stationary-vehicle incidents.
机译:本文调查了事故持续时间,并确定了影响澳大利亚状况的因素。本文针对事件延迟模型和旅行时间可靠性建模,提供了一个用于全面的交通事件数据挖掘和分析的新框架。收集,分析了十二个月的数据,并在本文中介绍了结果。研究结果表明,碎屑,故障和多车碰撞是高速公路事故的主要来源。此外,高速公路事故的持续时间因事故的类型和一天中的时间而异,无论是工作日还是周末。但是,与一年中的日,周或月没有明显差异。使用ANOVA测试针对每种事件类型,确定事件持续时间的重要变量。此外,这项研究的发现还揭示了每种事件类型内事件持续时间的巨大差异。各种概率分布函数用于测试每种事件类别的持续时间频率分布的最佳模型。发现对数正态分布更适合于撞车,但对数逻辑分布更适合于危险和固定车辆事故。

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