Climate change is a critical threat to human well-being and sustainable development. The I-CHANGE project aims to address this by engaging citizens and encouraging sustainable activity–travel behaviors and lifestyles that reduce energy use and carbon emissions. Researchers from project partner UHasselt (Belgium) have recently published a scientific paper about the enrichment of activity-travel schedules with in-home activities.
Activity-Based Travel Demand Models (ABMs) are key tools in this effort, as they simulate individuals’ daily activity–travel patterns, estimate their environmental impacts, and explore policies to promote sustainable living.
However, conventional ABMs overlook in-home activities, which are essential parts of daily routines. This study introduces a method to predict the types and durations of in-home activities within ABM-generated schedules, using statistical techniques. Tested with data from 6.3 million people in Belgium, the method achieved significant accuracy improvements, including a 68% increase in predicting time spent on in-home activities after calibration.
The results highlight the method’s ability to enhance ABMs for broader applications, such as evaluating energy use, carbon emissions, and telecommuting policies.