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Analysis of bus travel time distributions for varying horizons and real-time applications

机译:分析不同视野和实时应用的公交车出行时间分布

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摘要

Given the increasing interest in real-time bus arrival information, producing reliable estimation is essential to maximize the benefits of real-time systems. The primary objectives of this paper are to analyze the changes of bus travel time characteristics as pseudo horizon varies and how such characteristics can be applied to real-time bus arrival estimation. In this study, "horizon" refers to the distance between a real-time bus location and a bus stop, whereas "pseudo horizon" refers to the distance from a GPS point to an upstream GPS point. In contrast to existing methods that provide point estimates of bus arrival times, this study provides interval estimates that take into account the uncertainty of future bus arrival times given that early and late buses have their own respective ramifications. A methodology is developed to analyze the bus travel time distribution systematically based on different pseudo horizons since such distributions are critical to producing reliable bus arrival information. The analysis of real transit GPS data shows a significant change in bus travel time characteristics around a pseudo horizon range of 8 km. The analysis of changes in probability densities with pseudo horizons shows that bus travel time distribution converges from a rightly skewed distribution to a more symmetrical distribution from a shorter to a longer pseudo horizon. Lognormal and normal distributions are found to be the best models for before and after a cut-off horizon of 7-8 km, respectively. Instead of a single distribution, the outcomes of this study suggest a combination of probability distributions based on the estimation horizon to be used to provide better bus arrival time estimations.
机译:鉴于对实时公交车到站信息的兴趣日益增加,产生可靠的估算对于最大化实时系统的效益至关重要。本文的主要目的是分析随着伪地平线变化的公交车出行时间特性的变化,以及如何将这些特性应用于实时公交到达估计。在这项研究中,“水平”是指实时巴士位置与公交车站之间的距离,而“伪地平线”是指从GPS点到上游GPS点的距离。与提供公交车到达时间的点估计的现有方法相比,本研究提供的间隔估算考虑了未来公交车到达时间的不确定性,因为早晚的公交车有各自的影响。由于这种分布对于产生可靠的公共汽车到达信息是至关重要的,因此开发了一种方法来基于不同的伪地平线系统地分析公共汽车的行驶时间分布。对实际公交GPS数据的分析显示,在8 km的伪地平线范围内,公交车出行时间特性发生了显着变化。对伪视界概率密度变化的分析表明,公交车旅行时间分布从右偏斜分布收敛到从较短伪视界到较长伪视界的对称分布。发现对数正态分布和正态分布分别是7-8 km截止地平线之前和之后的最佳模型。代替单一分布,本研究的结果表明,基于估计范围的概率分布组合将用于提供更好的公交车到达时间估计。

著录项

  • 来源
    《Transportation research》 |2018年第1期|453-466|共14页
  • 作者单位

    Univ Calgary, Schulich Sch Engn, Dept Civil Engn, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada;

    Univ Calgary, Schulich Sch Engn, Dept Civil Engn, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada;

    Univ Calgary, Schulich Sch Engn, Dept Civil Engn, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Distribution; Interval; Horizon; Arrival; Travel time; Real-time;

    机译:分布;间隔;水平;到达;旅行时间;实时;

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