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Estimation of travel time distributions for urban roads using GPS trajectories of vehicles: a case of Athens, Greece

机译:利用车辆GPS轨迹估算城市道路的旅行时间分布:一种雅典,希腊的案例

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Investigating travel time distribution and associated variability is important for a variety of transport planning, traffic management, and control projects. Studies that investigated travel time distribution tend to be limited to explore changes in characteristics of distribution with respect to space and time of day. Given the availability of big dataset that contains seven different types of vehicle trajectories in the city of Athens for around 56,000 trips which are traversing on more than 1.8 million road links, this study presents the detailed investigation of travel time distribution in different spatiotemporal settings. The study considered four different types of urban roads and six time intervals along with consideration of weekdays and weekends. The empirical investigation employed Kruskal-Wallis, Chi-square, and Kolmogorov-Smirnov tests to fit travel time data into seven unimodal statistical distributions that are found in the literature to describe travel time distribution. It is found that lognormal distribution outperformed other distribution, and all of the considered categories of travel time data are well-fitted to this distribution. Additionally, parameters of lognormal distribution for different categories of travel time data are not significantly different from each other, which led to the conclusion that travel time distribution is roughly independent of space and time, which is in agreement with a few earlier studies that are limited in their scope especially in relation with availability of data. With this important finding, this study estimate values of travel time variability for different classes of individuals employing a standard approach that requires time of day independent standardized distribution of travel time. It is estimated that for Athens population value of travel time variability is approximately half of the value of travel time. This is useful to carry out cost-benefit analyses for mobility-related projects in Athens, Greece.
机译:调查旅行时间分配和相关的可变性对于各种运输计划,交通管理和控制项目非常重要。调查的旅行时间分布的研究往往限于探讨相对于空间和时间的分布特征的变化。鉴于在雅典市中包含七种不同类型的车辆轨迹的大数据集的可用性约为56,000次旅行,这项研究旨在提供超过180万道路链接,详细调查不同的时空环境中的旅行时间分布。这项研究审议了四种不同类型的城市道路和六次时间间隔,同时考虑了平日和周末。经验研究采用Kruskal-Wallis,Chi-Square和Kolmogorov-Smirnov测试,将旅行时间数据适合于文献中发现的七种单峰统计分布,以描述行程时间分布。结果发现,Lognormal分布优于其他分布,所有考虑的旅行时间数据数据都适合该分布。另外,针对不同类别的旅行时间数据的Lognormal分布的参数彼此没有显着差异,这导致了行进时间分布大致独立于空间和时间,这与有限的一些早期研究一致在他们的范围内,特别是与数据的可用性相关。通过这一重要的发现,本研究估计了采用标准方法的不同类别的不同类别的旅行时间变异值,这需要一天的日常标准化旅行时间。据估计,对于雅典人口价值的旅行时间可变性大约是旅行时间价值的一半。这对于对希腊雅典的流动相关项目进行成本效益分析是有用的。

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