Abstract This paper is motivated by the increasing recognition that modeling activity-travel demand for a single day of the week, as is done in virtually all travel forecasting models, may be inadequate in capturing underlying processes that govern activity-travel scheduling behavior. The considerable variability in daily travel suggests that there are important complementary relationships and competing tradeoffs involved in scheduling and allocating time to various activities across days of the week. Both limited survey data availability and methodological challenges in modeling week-long activity-travel schedules have precluded the development of multi-day activity-travel demand models. With passive and technology-based data collection methods increasingly in vogue, the collection of multi-day travel data may become increasingly commonplace in the years ahead. This paper addresses the methodological challenge associated with modeling multi-day activity-travel demand by formulating a multivariate multiple discrete-continuous probit (MDCP) model system. The comprehensive framework ties together two MDCP model components, one corresponding to weekday time allocation and the other to weekend activity-time allocation. By tying the two MDCP components together, the model system also captures relationships in activity-time allocation between weekdays on the one hand and weekend days on the other. Model estimation on a week-long travel diary data set from the United Kingdom shows that there are significant inter-relationships between weekdays and weekend days in activity-travel scheduling behavior. The model system presented in this paper may serve as a higher-level multi-day activity scheduler in conjunction with existing daily activity-based travel models.

中文翻译：

---

了解工作日和周末的活动参与度：多元多元离散连续建模方法

摘要本文的动机是，人们越来越认识到，像在几乎所有旅行预测模型中所做的那样，对一周中一天的活动-旅行需求进行建模可能不足以捕获控制活动-旅行计划行为的基础流程。每天旅行的变化很大，这表明在安排和分配时间到一周中的各种活动中存在重要的互补关系和竞争性的权衡。在为期一周的活动旅行时间表建模中，有限的调查数据可用性和方法上的挑战都阻碍了多日活动旅行需求模型的开发。随着被动和基于技术的数据收集方法越来越流行，在未来几年，收集多日旅行数据可能会变得越来越普遍。本文通过制定多元多元离散连续连续概率（MDCP）模型系统，解决了与为多日活动/旅行需求建模相关的方法挑战。全面框架将两个MDCP模型组件联系在一起，一个对应于工作日时间分配，另一个对应于周末活动时间分配。通过将两个MDCP组件捆绑在一起，模型系统还可以捕获一方面工作日与另一方面工作日之间的活动时间分配关系。来自英国的为期一周的旅行日记数据集的模型估计表明，工作旅行的日程安排行为在工作日和周末之间存在显着的相互关系。