Mandatory Tour Scheduling#

The mandatory tour scheduling model selects a tour departure and duration period (and therefore a start and end period as well) for each mandatory tour. The primary drivers in the model are accessibility-based parameters such as the mode choice logsum for the departure/arrival hour combination, demographics, and time pattern characteristics such as the time windows available from previously scheduled tours. This model uses person :ref:time_windows.

Note

For prototype_mtc, the modeled time periods for all submodels are hourly from 3 am to 3 am the next day, and any times before 5 am are shifted to time period 5, and any times after 11 pm are shifted to time period 23.

If tour_departure_and_duration_segments.csv is included in the configs, then the model will use these representative start and end time periods when calculating mode choice logsums instead of the specific start and end combinations for each alternative to reduce runtime. This feature, know as representative logsums, takes advantage of the fact that the mode choice logsum, say, from 6 am to 2 pm is very similar to the logsum from 6 am to 3 pm, and 6 am to 4 pm, and so using just 6 am to 3 pm (with the idea that 3 pm is the “representative time period”) for these alternatives is sufficient for tour scheduling. By reusing the 6 am to 3 pm mode choice logsum, ActivitySim saves significant runtime.

The main interface to the mandatory tour purpose scheduling model is the mandatory_tour_scheduling function. This function is registered as an Inject step in the example Pipeline

Structure#

  • Configuration File: mandatory_tour_scheduling.yaml

  • Core Table: tours

  • Result Field: start,end,duration

  • Skim Keys: TAZ,workplace_taz,school_taz,start,end

This model generates only True or False outcomes, and is structured as a binary logit model.

Examples#

Implementation#

activitysim.abm.models.mandatory_scheduling.mandatory_tour_scheduling(state: State, tours: DataFrame, persons_merged: DataFrame, tdd_alts: DataFrame) None#

This model predicts the departure time and duration of each activity for mandatory tours