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Travel Time Estimation of Single Segment Based on Freeway Toll Data

机译:基于高速公路通行费数据的单路段出行时间估计

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Travel time is one of the most important indexes to describe freeway traffic condition, and the spatial and temporal variation of traffic condition can support operational decision making for administrators and trip planning for travelers. The closed toll system of freeway in China contains large amount of travel information (e.g. vehicle type, entry/exit station, entry/exit time), and the toll data can be used to estimate the route travel time directly (i.e. exit time minus entry time). Compared to the route travel time, single segment (i.e. the mainline between two adjacent toll stations) travel time represents the spatial variation of traffic condition more accurately. With short time interval (e.g. 15 minutes), single segment travel time is also good at describing the temporal variation of traffic condition. However, single segment travel time estimation is always unreliable when only using the adjacent toll stations' data due to the insufficient data with finer resolution. This study proposed a method to solve this problem by using toll information from all vehicles that pass through the single segment. A case study on Huning Freeway, which is the busiest freeway in Jiangsu province, is used to validate the method. 74,684 toll data records in four hours are used after quality control and data filtering. The results demonstrate the spatial and temporal variation of traffic conditions in 15 minutes time interval for the 274 km long freeway and the location and duration of congestion is precisely identified. Biased estimation results are discussed and improvement is proposed. The method will contribute to a better understanding of freeway traffic condition variations without additional monitoring facilities.
机译:出行时间是描述高速公路交通状况的最重要指标之一,交通状况的时空变化可以支持管理员的业务决策和旅行者的出行计划。中国高速公路的封闭收费系统包含大量的出行信息(例如车辆类型,出入站,出入时间),而通行费数据可用于直接估算路线出行时间(即出站时间减去出站时间)时间)。与路线行驶时间相比,单个路段(即两个相邻收费站之间的干线)行驶时间更准确地代表了交通状况的空间变化。在较短的时间间隔(例如15分钟)内,单段行驶时间也可以很好地描述交通状况的时间变化。但是,仅使用相邻收费站的数据时,单段行驶时间估计总是不可靠的,这是因为数据的分辨率较差。这项研究提出了一种通过使用来自所有通过单个路段的车辆的通行费信息来解决此问题的方法。以江苏省最繁忙的高速公路沪宁高速公路为例,对该方法进行了验证。经过质量控制和数据过滤后,将在四个小时内使用74,684个收费数据记录。结果表明,这条274公里长的高速公路在15分钟的时间间隔内交通状况的时空变化,可以准确地识别出拥堵的位置和持续时间。讨论了有偏估计结果,并提出了改进建议。该方法将有助于更好地了解高速公路交通状况的变化,而无需其他监控设施。

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