Mandatory Tour Frequency#

The individual mandatory tour frequency model predicts the number of work and school tours taken by each person with a mandatory DAP. The primary drivers of mandatory tour frequency are demographics, accessibility-based parameters such as drive time to work, and household automobile ownership. It also creates mandatory tours in the data pipeline.

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

Structure#

  • Configuration File: mandatory_tour_frequency.yaml

  • Core Table: persons

  • Result Field: mandatory_tour_frequency

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

Configuration#

settings activitysim.abm.models.mandatory_tour_frequency.MandatoryTourFrequencySettings#

Bases: LogitComponentSettings

Settings for the mandatory_tour_frequency component.

Fields:
Validators:

  • nests_are_for_nl » NESTS

field COEFFICIENTS: Path | None = None#

Coefficients filename.

This is a CSV file giving named parameters for use in the utility expression. If it is not provided, then it is assumed that all model coefficients are given explicitly in the SPEC as numerical values instead of named parameters. This is perfectly acceptable for use with ActivitySim for typical simulation applications, but may be problematic if used with “estimation mode”.

field CONSTANTS: dict[str, Any] = {}#

Named constants usable in the utility expressions.

field LOGIT_TYPE: Literal['MNL', 'NL'] = 'MNL'#

Logit model mathematical form.

  • “MNL”

    Multinomial logit model.

  • “NL”

    Nested multinomial logit model.

field NESTS: LogitNestSpec | None = None#

Nesting structure for a nested logit model.

The nesting structure is specified heirarchically from the top, so the value of this field should be the “root” level nest of the nested logit tree, which should contain references to lower level nests and/or the actual alternatives.

For example, this YAML defines a simple nesting structure for four alternatives (DRIVE, WALK, WALK_TO_TRANSIT, DRIVE_TO_TRANSIT) with the two transit alternatives grouped together in a nest:

NESTS:
  name: root
  coefficient: coef_nest_root
  alternatives:
    - DRIVE
    - WALK
    - name: TRANSIT
      coefficient: coef_nest_transit
      alternatives:
      - WALK_TO_TRANSIT
      - DRIVE_TO_TRANSIT
Validated by:

  • nests_are_for_nl

field SPEC: Path [Required]#

Utility specification filename.

This is sometimes alternatively called the utility expressions calculator (UEC). It is a CSV file giving all the functions for the terms of a linear-in-parameters utility expression.

field annotate_persons: PreprocessorSettings | None = None#
field preprocessor: PreprocessorSettings | None = None#

Setting for the preprocessor.

field sharrow_skip: bool = False#

Skip sharrow when evaluating this component.

field source_file_paths: list[Path] = None#

A list of source files from which these settings were loaded.

This value should not be set by the user within the YAML settings files, instead it is populated as those files are loaded. It is primarily provided for debugging purposes, and does not actually affect the operation of any model.

validator nests_are_for_nl  »  NESTS#

Checks that nests are provided if (and only if) LOGIT_TYPE is NL.

Examples#

Implementation#

activitysim.abm.models.mandatory_tour_frequency.mandatory_tour_frequency(state: State, persons_merged: DataFrame, model_settings: Optional[MandatoryTourFrequencySettings] = None, model_settings_file_name: str = 'mandatory_tour_frequency.yaml', trace_label: str = 'mandatory_tour_frequency') → None#

This model predicts the frequency of making mandatory trips (see the alternatives above) - these trips include work and school in some combination.