环岛通行能力实证模型的建立——以匈牙利为例

IF 0.4 Q4 TRANSPORTATION SCIENCE & TECHNOLOGY
Haitham Al Hasanat, Juhasz Janos
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引用次数: 0

摘要

环形交叉路口在世界范围内被广泛使用,因为它们比传统的交叉路口有很多优点。环岛所能处理的容量是确保特定地点交通畅通的重要因素。因此,开发了各种模型来描述不同地点或国家的交通状况和驾驶员行为。但是,如果没有适当校准模型以确保准确估计能力,现有模型就不能直接应用于其他国家。本研究选取匈牙利的5个环形交叉路口,建立通用容量模型,并与国际模型进行比较。首先,从每个环岛入口的视频记录中获得所有套入口和循环数据。这些数据被用来为每个入口建立一个模型,然后分别为每个回旋处建立一个模型。最后,将所有16个条目的所有数据集用于建立通用容量模型(GM)。通用容量模型(GM)与公路容量手册(HCM) 2016、Brilon-Bondzio和Brilon-Wu模型进行了比较。通用容量模型(GM)的最大容量为1390 pcu/h,略高于HCM 2016模型的最大容量1380 pcu/h。生成的通用容量模型(GM)与HCM 2016、Brilon-Bondzio和Brilon-Wu模型的百分比差异分别为+0.71%、+12.4%和+10.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DEVELOPMENT OF ROUNDABOUTS EMPIRICAL CAPACITY MODEL – CASE STUDY OF HUNGARY
Roundabouts are commonly used worldwide because they offer several advantages over traditional intersections. The capacity that a roundabout can handle is an important factor in ensuring smooth traffic flow at a particular location. Therefore, various models have been developed to describe traffic conditions and driver behaviour at different sites or countries. However, existing models cannot be directly applied to other countries without proper calibration of the models to ensure an accurate estimation of capacity. In this study, five roundabouts in Hungary were selected to develop a general capacity model and compare it with international models. First, all sets of entry and circulating data were obtained from video recordings of each roundabout entry. These data were used to develop a model for each entry and then for each roundabout separately. Finally, all the data sets from all sixteen entries were used to develop a general capacity model (GM). The general capacity model (GM) was compared with the Highway Capacity Manual (HCM) 2016, the Brilon-Bondzio, and the Brilon-Wu models. The maximum capacity of the general capacity model (GM) was 1390 pcu/h, slightly higher than the maximum capacity of the HCM 2016 model of 1380 pcu/h. The percentage differences between the generated general capacity model (GM), HCM 2016, Brilon-Bondzio, and Brilon-Wu models were +0.71%, +12.4%, and +10.7%, respectively.
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来源期刊
CiteScore
1.20
自引率
0.00%
发文量
52
审稿时长
20 weeks
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