Pougala_STRC2022 TRANSP-OR TALK Pougala, Janody Hillel, Tim Bierlaire, Michel Parameter estimation for activity-based models 2022 STRC 2022 Monte Veritá, Ascona, Switzerland May 19, 2022 Activity-based models (ABM) have seen a significant increase in research focus in the past decade. Based on the fundamental assumption that travel demand is derived from the need to do activities and time and space constraints. ABM offer a more flexible and behaviorally centered alternative to traditional trip-based approaches. Econometric – or utility-based – activity-based models postulate that the process of activity generation and scheduling can be modelled as discrete choices. Individuals derive a utility from performing activities, and they schedule them as to maximize the total utility. In this paper, we estimate the parameters of the optimization-based activity-based model developed by Pougala et al (2021), by defining a discrete choice model where the choices for each individual are full daily schedules, each associated with a utility. The maximum likelihood estimators of the parameters (e.g. scheduling penalties, desired start times and durations, constants…) are evaluated on a choice set of daily schedules sampled using the Metropolis-Hastings algorithm, derived for sample of individuals from the 2015 Swiss Mobility and Transport Microcensus. Results show that the proposed methodology significantly improves the calibration of econometric activity-based models.