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Validation of Activity-based Travel Demand Model using Smart-card Data in Seoul, South Korea

机译:在韩国首尔使用智能卡数据验证基于活动的旅行需求模型

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This study aims to validate an activity-based travel demand model, FEATHERS, using smart-card data which is collected in Seoul, South Korea, and to discuss some limits and challenges in the prediction of public traffic demands. To achieve the goal, global/local trip pattern indices and a hot-spot analysis were applied for the validation test as a comparison method in this study. Using those methods, the public traffic demands predicted by the simulation in the study area were evaluated comparing with ones in the smart-card data. As a result, FEATHERS Seoul shows the enough performance in predicting the global pattern of the public traffic demands, but a low performance in a local pattern, particularly in some areas with a mixture land-use type and/or a frequent public transit. This is because the current model does not handle such a complicate type of land-use and also a multi-modal trip in the simulation process. In conclusion, this study addressed the limits of the current model through the validation test using smart-card data and suggested some solution to the improvement in the specific models As a future work, we will apply smart-card data for the validation of the models operated in FS, such as a location choice model and a trip mode choice model.
机译:这项研究旨在使用从韩国首尔收集的智能卡数据验证基于活动的出行需求模型FEATHERS,并讨论预测公共交通需求时的一些局限性和挑战。为了实现这一目标,在本研究中,将全球/本地出行方式指数和热点分析作为验证方法进行了验证测试。使用这些方法,通过模拟预测的研究区域中的公共交通需求与智能卡数据中的需求进行了评估。结果,首尔FEATHERS在预测全球公共交通需求的模式方面表现出足够的表现,但在本地模式下却表现不佳,尤其是在土地使用类型混合和/或公共交通频繁的某些地区。这是因为当前模型在模拟过程中无法处理如此复杂的土地利用类型,也无法处理多模式旅行。总之,本研究通过使用智能卡数据的验证测试解决了当前模型的局限性,并提出了一些改进特定模型的解决方案。作为未来的工作,我们将应用智能卡数据进行模型验证在FS中运行,例如位置选择模型和行程模式选择模型。

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