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Existing activity-based modeling predominantly focus on out-of-home activities in order to un- derstand transport demand. In this research, we extend the state of practice in activity-based modelling by determining both in- and out-of-home activities in a single scheduling framework. This approach has two main benefits: Firstly, it can capture the trade-offs between in-home and out-of-home activities. Secondly, in-home time-use patterns can be used to model high resolution energy demand. Our work builds on an existing optimisation framework, which treats individuals as maximising their total utility from completed activities and incorporates multiple scheduling decisions simultaneously. The approach is tested on a set of detailed daily schedules extracted from the 2016-2020 UK Time Use Survey data. The results show that the model is able to generate peoples’ daily activity schedules based on their individual preferences and constraints.
Mario Paolone, Sidi-Rachid Cherkaoui, Elena Vagnoni, Francesco Gerini, Martin Seydoux