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A household-level activity pattern generation model with an application for Southern California

机译：家庭层面的活动模式生成模型及其在南加州的应用

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This paper develops and estimates a multiple discrete continuous extreme value model of household activity generation that jointly predicts the activity participation decisions of all individuals in a household by activity purpose and the precise combination of individuals participating. The model is estimated on a sample obtained from the post census regional household travel survey conducted by the South California Association of Governments in the year 2000. A host of household, individual, and residential neighborhood accessibility measures are used as explanatory variables. The results reveal that, in addition to household and individual demographics, the built environment of the home zone also impacts the activity participation levels and durations of households. A validation exercise is undertaken to evaluate the ability of the proposed model to predict participation levels and durations. In addition to providing richness in behavioral detail, the model can be easily embedded in an activity-based microsimulation framework and is computationally efficient as it obviates the need for several hierarchical sub-models typically used in extant activity-based systems to generate activity patterns.
机译：本文开发并估算了家庭活动产生的多个离散的连续极值模型，该模型可以通过活动目的和参与个体的精确组合共同预测一个家庭中所有个体的参与决策。该模型是根据2000年由南加州政府协会进行的人口普查后区域家庭旅行调查得出的样本估算的。许多家庭，个人和居民区可及性度量均用作解释变量。结果显示，除了家庭和个人人口统计信息外，家庭区域的建成环境还影响活动参与水平和家庭持续时间。进行了一项验证练习，以评估所提出模型预测参与水平和持续时间的能力。除了提供丰富的行为细节外，该模型还可以轻松地嵌入基于活动的微观仿真框架中，并且由于无需使用通常用于现有基于活动的系统中生成活动模式的几个层次子模型，因此具有较高的计算效率。

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