  Mobility as a Service (MaaS), as an emerging concept, is quickly evolving and
at the same time irreversibly reshaping travellers behaviour by facilitating
their accessibility to different transport modes using shared economy concepts.
Managing the complex multimodal and intermodal system of quickly emerging MaaS,
requires a holistic modelling framework of transport network incorporating all
the influential aspects and means involved. In this paper, we mathematically
formulate a novel MaaS-based activity travel pattern (ATP) generator to
facilitate ridesharing in a system in which drivers and passengers interact by
sharing their full activity diary. The proposed formulation extends the
definition of MaaS beyond an intermodal trip planner, by incorporating an
inclusive set of travel attributes including the choices of activity, activity
sequence, departure time, and mode, and the transitions among the modes in ATPs
of all participants. Furthermore, this paper introduces a dynamic
rideshare-oriented MaaS model in which the conventional rideshare modelling
structure is synchronised with the proposed MaaS-based ATP generator in a
unified structure. These models explicitly bridge the gaps in the missed-out
connection between ATPs planning and rideshare models in the current
literature. At last, numerical examples are provided to demonstrate the
significant impacts of the MaaS-based planning on the ridesharing systems
performance.
