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Integrating Geographic Information Systems into Transit Ridership Forecast Models

机译:将地理信息系统集成到过境乘车率预测模型中

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Researchers have produced sophisticated modal split and transit demand models, including forecasts that are sensitive to the level of service. However, little effort has been made to integrate these models into corridor studies and route alignment analyses since (a) re-routing is itself an extremely complex modeling task, and (b) the results of the demand models are presented in tabular form with no facility to visualize spatial patterns and relationships that, if recognized, would aid in the routing tasks. GIS tools can be used, together with the demand models, to identify both clusters of city blocks that house families with certain socio-economic characteristics and potential trip destinations conducive to transit use. In other words, GIS tools can be used to better measure some of the factors that are needed by transit demand models. The results of these models can be displayed graphically, enabling analysts to target places needing improved service, evaluate route re-alignment alternatives, and operate more efficient and effective bus lines. This paper examines how a particular class of model used by transit agencies for estimating ridership can be integrated with GIS tools in order to facilitate such analyses. It also explores the effects of visualization of routes, demographics, and employment data on the process of designing route alignments with better targeting of high transit ridership areas. This paper is part of a research project sponsored by the Region One University Transportation Center, at MIT.
机译:研究人员已经生成了复杂的模式拆分和运输需求模型,包括对服务水平敏感的预测。但是,由于(a)重新路由本身是一项极其复杂的建模任务,并且(b)需求模型的结果以表格形式呈现,但没有做出任何努力,因此未将这些模型集成到走廊研究和路线对齐分析中可视化空间模式和关系的功能,如果被识别,将有助于路由任务。可以将GIS工具与需求模型一起使用,以识别容纳具有一定社会经济特征的家庭的城市街区群,以及有助于公交使用的潜在出行目的地。换句话说,可以使用GIS工具更好地度量公交需求模型所需的某些因素。这些模型的结果可以图形方式显示,从而使分析人员可以将目标对准需要改善服务的地点,评估路线重新调整的备选方案,并运行更高效的公交线路。本文研究了运输机构用来估算乘车人数的特定类别的模型如何与GIS工具集成在一起,以便于进行此类分析。它还探讨了路线,人口统计和就业数据可视化对路线对齐设计过程的影响,更好地针对了高乘车出行区域。该论文是麻省理工学院地区一大学交通中心赞助的一项研究项目的一部分。

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