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首页> 外文期刊>Networks & Spatial Economics >A Model for Locating Park-and-Ride Facilities on Urban Networks Based on Maximizing Flow Capture: A Case Study of Isfahan, Iran
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A Model for Locating Park-and-Ride Facilities on Urban Networks Based on Maximizing Flow Capture: A Case Study of Isfahan, Iran

机译:基于最大流量捕获的城市网络上停车和乘车设施定位模型:以伊朗伊斯法罕为例

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摘要

Traffic congestion is one of the main problems in large cities for which several approaches have been proposed. Park-and-ride is one of the best approaches that can remove traffic from the traffic network. Park-and-ride facilities are an important part of urban mass transit systems, effectively extending the service area and attracting commuters and other people who may not otherwise have used mass transit. However, its efficiency depends on its location in the urban network. In this research, we focus on travel time of shortest paths instead of the distance criterion for computing network traffic and develop a model for finding the best location(s) for siting park-and-ride systems so as to minimize the network traffic. The model is formulated based on population points, potential sites for park-and-ride establishment, and several Central Business District (CBDs). Then we present a Genetic algorithm that has been proved to be efficient in solving large size problems. Finally, the proposed model is used to locate park-and-ride facilities in the city of Isfahan, Iran.
机译:在已经提出了几种方法的大城市中,交通拥堵是主要问题之一。停车驾驶是可以从交通网络中删除交通的最佳方法之一。停车和骑行设施是城市公共交通系统的重要组成部分,有效地扩展了服务范围并吸引了通勤者和其他可能没有使用公共交通的人们。但是,其效率取决于其在城市网络中的位置。在这项研究中,我们专注于最短路径的旅行时间,而不是用于计算网络流量的距离标准,并开发了一种模型,该模型可以找到最佳选址的选址乘骑系统,以最大程度地减少网络流量。该模型是根据人口点,建立停车和骑行的潜在地点以及几个中央商务区(CBD)制定的。然后,我们提出了一种遗传算法,该算法已被证明可有效解决大型问题。最后,提出的模型用于定位伊朗伊斯法罕市的停车和乘车设施。

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