A simulator designed to generate realistic Activities of Daily Living (ADLs) to model urban-scale utility consumption (water, electricity, and gas) and an Agentic AI architecture using Large Language Models (LLMs) to generate 24-hour activity schedules are proposed.
Activity-based models have emerged over the past four decades and have demonstrated a stronger capacity than traditional four-step models to capture the sequence of an individual’s daily activities, associated trips, and travel behavior. However, the state of the art shows that demand generation in activity-based model...
N. Nguyen, Joerg Schweizer, Cristian Poliziani et al.· SUMO Conference Proceedings· 0 citations
In existing agent-based simulations of multimodal urban mobility, agents, representing humans, choose their travel modes either using discrete choice or machine learning models fitted on structured travel survey data, or with rules explicitly written by the domain experts. Such approaches fix a priori the agents'possib...
Decarbonising the building sector is central to meeting climate targets, yet existing models rarely capture the interaction between system-level transformation dynamics and heterogeneous individual investment decisions. This work presents AgentHomeID, an agent-based model of building stock evolution in which owner beha...
Helen Ganal, Sarah Becker, S. Holzhauer et al.· 0 citations
This study presents BuildOcc, an open-source Python platform that grounds large language model agents in the ATUS, a nationally representative diary dataset covering 16,684 respondents, and provides the building energy community with a reusable, openly available implementation of the occupant behavioral layer.
Digital Twins have become a central tool for Smart City planning and management, enabling simulation and analysis of complex urban systems such as mobility and energy infrastructures. However, most existing implementations primarily focus on physical and operational layers, relying on static rules or aggregate models t...
E. Masciari, Enea Vincenzo Napolitano· IEEE Access· 0 citations
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