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Modeling bus bunching using massive location and fare collection data

机译:使用大量位置和票价收集数据对公交车群进行建模

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Bus bunching is a well-known phenomenon for operators, users and regulators of high-frequency bus services. Bus operations are usually affected by increasing differences in the time intervals (headways) between consecutive buses. The effect of this variability is that buses tend to group into bunches of two or more, which severely affects the quality of service and the operational efficiency. The aim of this paper is to analyze which factors are associated to the phenomenon, using massive data from high-frequency services available in Santiago (Chile) and common-route services in Gatineau (Canada). The data is obtained from the bus GPS and AFC systems and are processed to obtain headways between buses. Using data from one week, we develop models to explain the variation of the continuous and discrete indicators of bus bunching as a function of variables related to the operation, variables related to the demand structure, and variables related to the infrastructure. Some of the factors that contribute to increase bus bunching are: stops located toward the end of the route, high scheduled frequency, irregular bus dispatch headways, non-homogeneous fleet, high demand, and high variability of demand. The results are useful for the design of quality indexes to measure bunching in bus operations, and for the design and operation of bus routes, taking into consideration the potential bus bunching problems.
机译:对于高频总线服务的运营商,用户和监管者来说,总线聚集是一种众所周知的现象。公交车的运行通常受连续公交车之间时间间隔(车距)差异的影响。这种可变性的结果是,公交车倾向于分成两个或更多的束,这严重影响了服务质量和运营效率。本文的目的是使用来自圣地亚哥(智利)的高频服务和加蒂诺(加拿大)的通用航线服务的大量数据,分析与该现象相关的因素。数据从公交GPS和AFC系统获取,并进行处理以获得公交之间的车距。我们使用一周的数据来开发模型,以解释公交车集中的连续性和离散性指标随与操作相关的变量,与需求结构相关的变量以及与基础设施相关的变量的变化。导致公交车辆聚集的一些因素包括:靠近路线终点的车站,高调度频率,不定期的公交车调度车道,不均匀的车队,高需求和高需求变化。考虑到潜在的公交车聚束问题,该结果对于设计质量指标以测量公交车运行中的聚束,以及对于公交路线的设计和运行非常有用。

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