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A New Approach to Determine Traffic Peak Periods to Utilize in Transportation Planning

机译：一种确定交通峰期利用运输规划的新方法

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摘要

Detection of the traffic peak periods for a city has many advantages not only in terms of the traffic operation but also in urban transportation planning. In the planning, future travel demand is analyzed for peak and off-peak periods separately and transportation networks are designed based on these analyses. However, the traffic peak periods may shift in time because of changes in people’s activities. Therefore, the detection and update of these periods periodically provide to improve urban transportation planning. The aim of this research is to present a new approach to determine traffic peak periods in order to utilize for use in transportation planning. In order to achieve this goal, the inductive loop detector data are obtained for a city and cleaned. Regular traffic flow patterns (without days that include unexpected incidents) of the whole city are produced, and peak periods are determined with these data. The Facebook Prophet software, which is a forecasting procedure, is presented as a new approach to determine traffic peak periods based on changepoint detection. In order to compare the results, experts’ opinion, which is the conventional method, and the k-medoids clustering methods are applied. In conclusion, it is seen that the suggested new approach facilitates so much the accurate determination of traffic peak periods for urban transportation planning.
机译：检测城市的流量高峰期不仅在交通运营方面的优势，而且在城市交通规划方面具有许多优点。在规划中，将来的旅行需求分别分析峰值和非高峰期，并根据这些分析设计了运输网络。然而，由于人们活动的变化，流量高峰期可能会及时转换。因此，定期检测和更新这些时期，以改善城市运输规划。该研究的目的是提出一种新方法来确定交通峰期，以便利用在运输计划中使用。为了实现这一目标，为城市获得感应回路检测器数据并清洁。产生整个城市的常规交通流量模式（毫无包括的包括意外事件），并使用这些数据确定峰值周期。作为预测程序的Facebook先知软件被呈现为基于ChangePoint检测确定流量高峰期的新方法。为了比较结果，应用专家的意见，即常规方法和K-yemoids聚类方法。总之，看来，建议的新方法促进了城市交通规划的准确确定交通峰期。

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