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A rapid method for evaluating the variables affecting traffic flow in a touristic road, Iran
Environmental Systems Research Pub Date : 2019-12-01 , DOI: 10.1186/s40068-019-0162-0
Neda Kardani-Yazd , Nadia Kardani-Yazd , Mohammad Reza Mansouri Daneshvar

BackgroundThis study aimed to evaluate variables that influence traffic flow and its contribution to touristic transportation in a touristic road, Iran. The traffic flow data were extracted from the hour-by-hour data in 2018 from a local traffic control center in addition to three daily indices, including climatic comfort indicator, temperature inversion indicator, and temporal indicator of local calendar events, which were obtained from databases and equations. The data time series were arranged into diurnal, weekly, and monthly scales to apply in correlation tests.ResultsResults revealed that a rate of 18–25% of total transportation (about 3,500,000–5,000,000 vehicles from total 19,828,619 vehicles) was assumed as a touristic portion of the traffic flow in the study area. The relationships between independent variables and traffic flow data exposed the effective and considerable role of the local climate on the traffic flow at above 98% of confidence level, without a strong association between calendar effect and traffic flow. Statistical results in all temporal cycles revealed the significant positive and negative effects of the local climatic comfort index and temperature inversion index on the traffic flow, respectively.ConclusionsThe finding of this study described that the traffic flow and touristic transportation in the study area are more affected by the local climatic comfort and temperature inversion indices, but are less affected by the local calendar holidays and occasional vacations. Hence, the decision-makers in the study area sternly need a fundamental climatic calendar for management, tourism transportation, and traffic flow instead of the current local calendar.

中文翻译:

一种评估影响伊朗旅游道路交通流量的变量的快速方法

背景本研究旨在评估影响伊朗旅游公路交通流量及其对旅游交通的贡献的变量。交通流量数据是从当地交通控制中心2018年的逐小时数据中提取的,此外还有气候舒适度指标、逆温指标和当地日历事件的时间指标三个每日指标,这些指标来自于数据库和方程。数据时间序列被安排成日、周和月尺度以应用于相关性测试。 结果结果显示,总交通量(约 3,500,000-5,000,000 辆汽车,19,828,619 辆汽车)的比例为旅游部分研究区域内的交通流量。自变量与交通流量数据之间的关系在 98% 以上的置信水平下揭示了当地气候对交通流量的有效和相当大的作用,而日历效应与交通流量之间没有强关联。所有时间周期的统计结果分别揭示了当地气候舒适指数和逆温指数对交通流量的显着正负影响。结论本研究结果表明研究区的交通流量和旅游交通受到的影响更大受当地气候舒适度和逆温指数影响,但受当地日历假期和偶尔假期的影响较小。因此,研究区的决策者迫切需要一个基本的气候管理日历,
更新日期:2019-12-01
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