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Modeling and forecasting daily non-work/school activity patterns in an activity-based model using skeleton schedule constraints

机译：使用骨架时间表约束在基于活动的模型中建模和预测日常非工作/学校活动模式

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摘要

A dynamic, gap-based activity scheduling model is developed for predicting out-of-home non-work/school (NWS) episodes over a day. In the developed model, work/school, and night sleep are assumed to be pre-determined, thereby providing a daily "skeleton schedule". NWS episodes are then simultaneously generated and scheduled in the available gaps as a joint activity type and destination choice, followed by a continuous time expenditure choice. The model is built on a subset of the Transportation Tomorrow Survey (TTS) collected in the Greater Toronto and Hamilton Area (GTHA) in 2001. The developed model is validated on another sample from the TTS 2001 and is also applied to forecast individuals' schedules for the years 2006 and 2011, for which observed TTS data are also available. This study, which is rarely conducted in the literature, examines the model's capability to replicate the base year schedule and predict the activity patterns of the future years, which is the ultimate purpose of any travel demand model. Simulation outcomes of the three years follow similar trends to each other. Replication of the base year's schedule is more accurate than the future years; however, there are no significant changes in the accuracy of the outcomes of the model's application on all the three years.
机译：开发了一种动态的，基于缺口的活动计划模型，用于预测一天中的户外非工作/学校（NWS）发作。在开发的模型中，假定工作/学校和夜间睡眠是预先确定的，从而提供每日的“骨骼时间表”。然后，同时生成NWS情节并将其安排在可用间隙中，作为联合活动类型和目的地选择，然后进行连续的时间支出选择。该模型以2001年在大多伦多地区和汉密尔顿地区（GTHA）收集的运输明天调查（TTS）的子集为基础。开发的模型在2001年TTS的另一个样本中得到了验证，并且还用于预测个人的日程安排还提供了2006年和2011年的TTS观测数据。这项研究很少在文献中进行，研究了该模型复制基准年时间表和预测未来年份活动模式的能力，这是任何旅行需求模型的最终目的。三年的模拟结果遵循相似的趋势。复制基准年的时间表比未来几年更为准确；但是，在过去三年中，该模型应用结果的准确性没有明显变化。

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