  Activity-based models appeared as an answer to the limitations of the
traditional trip-based and tour-based four-stage models. The fundamental
assumption of activity-based models is that travel demand is originated from
people performing their daily activities. This is why they include a consistent
representation of time, of the persons and households, time-dependent routing,
and microsimulation of travel demand and traffic. In spite of their potential
to simulate traffic demand management policies, their practical application is
still limited. One of the main reasons is that these models require a huge
amount of very detailed input data hard to get with surveys. However, the
pervasive use of mobile devices has brought a valuable new source of data. The
work presented here has a twofold objective: first, to demonstrate the
capability of mobile phone records to feed activity-based transport models,
and, second, to assert the advantages of using activity-based models to
estimate the effects of traffic demand management policies. Activity diaries
for the metropolitan area of Barcelona are reconstructed from mobile phone
records. This information is then employed as input for building a transport
MATSim model of the city. The model calibration and validation process proves
the quality of the activity diaries obtained. The possible impacts of a cordon
toll policy applied to two different areas of the city and at different times
of the day is then studied. Our results show the way in which the modal share
is modified in each of the considered scenario. The possibility of evaluating
the effects of the policy at both aggregated and traveller level, together with
the ability of the model to capture policy impacts beyond the cordon toll area
confirm the advantages of activity-based models for the evaluation of traffic
demand management policies.

Physics and Society;Social and Information Networks