基于活动的微模拟模型的时间可转移性:在智利的应用

Víctor Allendes , Juan Antonio Carrasco , Eric J. Miller , James Vaughan
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引用次数: 0

摘要

发展中国家的城市交通政策大多使用传统的基于出行的模型来复制和预测不同城市背景下的个人出行。考虑到它们的集体性,与主要在全球北方使用的基于活动的模型,特别是基于微模拟的模型相比,它们在更分散的规模上应用时受到限制,在拉丁美洲的应用很少。此外,迫切需要增加经验证据来理解模型的时间可转移性,这涉及到它们基于当前收集的数据估计来预测未来旅行行为的能力。本文报告了智利一个基于活动的模式的可复制性和时间可转移性。目标是了解在这些环境中应用这些模型以实现政策有用性的挑战。本文分两个阶段研究了TASHA (Travel Activity Scheduler Household Agent)模型的适用性:对基准年的活动和行程的复制和预测,以及先前估计参数对未来一年的时间可转移性。该模型使用了来自智利一个中型城市的传统旅游调查的基于旅行的信息。这个练习提供了有价值的证据,证明了关于基于活动的模型(如TASHA)的优点的几个论点的原理。首先,该研究表明,尽管数据和环境有限,该模型仍有能力捕捉当前和未来的行为。其次,该模型支持对旅行之外的活动进行分析,从而对旅行行为进行更深入的评估。最后,也是更重要的是,对活动的关注,如结束时间,带来了纳入比传统上在运输方面研究的更广泛的政策的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temporal transferability of a microsimulation activity-based model: An application in Chile
Urban transport policies in the Global South mostly use traditional trip-based models to replicate and predict individuals' travel in different urban contexts. Given their aggregate nature, they are limited when applied at a more disaggregated scale, contrasting with activity-based models, especially microsimulation-based models, which have been used mainly in the Global North, with few applications in Latin America. In addition, there is a critical need to add empirical evidence to understand the models' temporal transferability, which involves their capability to predict future travel behavior based on estimations with data collected in the present. This paper reports on the replicability and temporal transferability of an activity-based model in Chile. The objective is to understand the challenges of applying these models in these contexts for policy usefulness. The applicability of the model TASHA (Travel Activity Scheduler Household Agent) is studied in two stages: replication and prediction of activities and trips for a base year and temporal transferability of previously estimated parameters to a future year. The model uses trip-based information from conventional travel surveys in a mid-size Chilean city. The exercise provides valuable proof of the principle of several arguments about the advantages of activity-based models such as TASHA. First, the study shows the model's ability to capture current and future behaviour despite data and context limitations. Second, the model supports the analysis of activities in addition to trips, providing a more in-depth assessment of travel behaviour. Finally, and more importantly, the focus on activities, such as end times, brings the opportunity to incorporate a broader range of policies than those traditionally studied in transport.
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