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The Origin–Destination Matrix Development

机译:起源-目的地矩阵的发展

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Transport studies are conducted for a better understanding of the actual mobility and for developing transport forecasting models to predict the future transport demand and the changes in travel patterns. Transport planning involves the decision-making process for potential improvements to a community’ s roadway infrastructure. The first transport models used to analyze globally the transport system requirements while nowadays models were rethought as a demand – supply interaction reflecting the correlation between transport and socio-economic development. The transport forecasting methodology use a four stage structure consisting of: trip generation, trip distribution, modal split, traffic assignment. In the second stage of the model, the generated trips for each zone are distributed to all other zones based on the choice of destination. The trip pattern is represented by means of an origin-destination (O-D) matrix. The Growth Factor Model and the Gravity Model are two methods to distribute trips among destinations. The two methods for developing the O-D Matrix are presented and criticized in this paper, showing the similarities and differences between them and highlighting the implications for rigorous determination of future transport demand. A case study is done to emphasize the differences between these models and their implications in carrying out transport studies.
机译:进行运输研究以更好地了解实际的机动性并开发运输预测模型以预测未来的运输需求和出行方式的变化。运输计划涉及决策过程,以潜在改善社区的道路基础设施。第一种运输模型用于全球范围内分析运输系统的需求,而如今,这些模型已被重新考虑为一种需求-供应相互作用,反映了运输与社会经济发展之间的关系。运输预测方法采用四个阶段的结构,包括:行程生成,行程分配,模式拆分,交通分配。在模型的第二阶段,根据目的地的选择,将每个区域生成的行程分配到所有其他区域。行程模式通过起点-终点(O-D)矩阵表示。增长因子模型和重力模型是在目的地之间分配行程的两种方法。本文介绍并批评了开发O-D矩阵的两种方法,显示了它们之间的异同,并强调了严格确定未来运输需求的意义。进行了案例研究,以强调这些模型之间的差异及其在进行运输研究中的含义。

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