Joint Tour Destination#

The joint tour destination choice model operate similarly to the usual work and school location choice model, selecting the primary destination for travel tours. The only procedural difference between the models is that the usual work and school location choice model selects the usual location of an activity whether or not the activity is undertaken during the travel day, while the joint tour destination choice model selects the location for an activity which has already been generated.

The tour’s primary destination is the location of the activity that is assumed to provide the greatest impetus for engaging in the travel tour. In the household survey, the primary destination was not asked, but rather inferred from the pattern of stops in a closed loop in the respondents’ travel diaries. The inference was made by weighing multiple criteria including a defined hierarchy of purposes, the duration of activities, and the distance from the tour origin. The model operates in the reverse direction, designating the primary purpose and destination and then adding intermediate stops based on spatial, temporal, and modal characteristics of the inbound and outbound journeys to the primary destination.

The joint tour destination choice model is made up of three model steps:

  • sample - selects a sample of alternative locations for the next model step. This selects X locations from the full set of model zones using a simple utility.

  • logsums - starts with the table created above and calculates and adds the mode choice logsum expression for each alternative location.

  • simulate - starts with the table created above and chooses a final location, this time with the mode choice logsum included.

Joint tour location choice for multiple_zone_systems models uses presampling by default.

The main interface to the model is the joint_tour_destination function. This function is registered as an Inject step in the example Pipeline. See writing_logsums for how to write logsums for estimation.

Structure#

  • Configuration File: joint_tour_destination.yaml

  • Core Table: tours

  • Result Field: destination

  • Skims Keys: TAZ, alt_dest, MD time period

Configuration#

settings activitysim.abm.models.joint_tour_destination.TourLocationComponentSettings#

Bases: LocationComponentSettings

Config:

  • extra: str = forbid

Fields:

  • ALT_DEST_COL_NAME (str)

  • CHOOSER_FILTER_COLUMN_NAME (str | None)

  • CHOOSER_ID_COLUMN (str)

  • CHOOSER_ORIG_COL_NAME (str)

  • CHOOSER_SEGMENT_COLUMN_NAME (str | None)

  • CHOOSER_TABLE_NAME (str | None)

  • COEFFICIENTS (Path | None)

  • CONSTANTS (dict[str, Any])

  • DEST_CHOICE_COLUMN_NAME (str | None)

  • DEST_CHOICE_LOGSUM_COLUMN_NAME (str | None)

  • DEST_CHOICE_SAMPLE_TABLE_NAME (str | None)

  • ESTIMATION_SAMPLE_SIZE (int)

  • IN_PERIOD (int | dict[str, int] | None)

  • LOGSUM_PREPROCESSOR (str)

  • LOGSUM_SETTINGS (Path)

  • LOGSUM_TOUR_PURPOSE (str | dict[str, str] | None)

  • MODELED_SIZE_TABLE (str | None)

  • MODEL_SELECTOR (str | None)

  • MODE_CHOICE_LOGSUM_COLUMN_NAME (str | None)

  • ORIG_ZONE_ID (str | None)

  • OUT_PERIOD (int | dict[str, int] | None)

  • SAMPLE_SIZE (int)

  • SAMPLE_SPEC (Path)

  • SAVED_SHADOW_PRICE_TABLE_NAME (str | None)

  • SEGMENTS (list[str] | None)

  • SEGMENT_IDS (dict[str, int] | dict[str, str] | dict[str, bool] | None)

  • SHADOW_PRICE_TABLE (str | None)

  • SIMULATE_CHOOSER_COLUMNS (list[str] | None)

  • SIZE_TERM_SELECTOR (str | None)

  • SPEC (Path)

  • annotate_households (PreprocessorSettings | None)

  • annotate_persons (PreprocessorSettings | None)

  • annotate_tours (PreprocessorSettings | None)

  • compute_settings (ComputeSettings)

  • explicit_chunk (float)

  • source_file_paths (list[Path])

Validators:

  • update_sharrow_skip » all fields

field ALT_DEST_COL_NAME: str [Required]#
Validated by:

  • update_sharrow_skip

field CHOOSER_FILTER_COLUMN_NAME: str | None = None#
Validated by:

  • update_sharrow_skip

field CHOOSER_ID_COLUMN: str = 'person_id'#
Validated by:

  • update_sharrow_skip

field CHOOSER_ORIG_COL_NAME: str [Required]#
Validated by:

  • update_sharrow_skip

field CHOOSER_SEGMENT_COLUMN_NAME: str | None = None#
Validated by:

  • update_sharrow_skip

field CHOOSER_TABLE_NAME: str | None = None#
Validated by:

  • update_sharrow_skip

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”.

Validated by:

  • update_sharrow_skip

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

Named constants usable in the utility expressions.

Validated by:

  • update_sharrow_skip

field DEST_CHOICE_COLUMN_NAME: str | None = None#
Validated by:

  • update_sharrow_skip

field DEST_CHOICE_LOGSUM_COLUMN_NAME: str | None = None#

Column name for logsum calculated across all sampled destinations.

Validated by:

  • update_sharrow_skip

field DEST_CHOICE_SAMPLE_TABLE_NAME: str | None = None#
Validated by:

  • update_sharrow_skip

field ESTIMATION_SAMPLE_SIZE: int = 0#

The number of alternatives to sample for estimation mode. If zero, then all alternatives are used. Truth alternative will be included in the sample. Larch does not yet support sampling alternatives for estimation, but this setting is still helpful for estimation mode runtime.

Validated by:

  • update_sharrow_skip

field IN_PERIOD: int | dict[str, int] | None = None#
Validated by:

  • update_sharrow_skip

field LOGSUM_PREPROCESSOR: str = 'preprocessor'#
Validated by:

  • update_sharrow_skip

field LOGSUM_SETTINGS: Path [Required]#

Settings for the logsum computation.

Validated by:

  • update_sharrow_skip

field LOGSUM_TOUR_PURPOSE: str | dict[str, str] | None = None#
Validated by:

  • update_sharrow_skip

field MODELED_SIZE_TABLE: str | None = None#
Validated by:

  • update_sharrow_skip

field MODEL_SELECTOR: str | None = None#
Validated by:

  • update_sharrow_skip

field MODE_CHOICE_LOGSUM_COLUMN_NAME: str | None = None#

Column name for logsum calculated across all sampled modes to selected destination.

Validated by:

  • update_sharrow_skip

field ORIG_ZONE_ID: str | None = None#

This setting appears to do nothing…

Validated by:

  • update_sharrow_skip

field OUT_PERIOD: int | dict[str, int] | None = None#
Validated by:

  • update_sharrow_skip

field SAMPLE_SIZE: int [Required]#

This many candidate alternatives will be sampled for each choice.

Validated by:

  • update_sharrow_skip

field SAMPLE_SPEC: Path [Required]#

The utility spec giving expressions to use in alternative sampling.

Validated by:

  • update_sharrow_skip

field SAVED_SHADOW_PRICE_TABLE_NAME: str | None = None#
Validated by:

  • update_sharrow_skip

field SEGMENTS: list[str] | None = None#
Validated by:

  • update_sharrow_skip

field SEGMENT_IDS: dict[str, int] | dict[str, str] | dict[str, bool] | None = None#
Validated by:

  • update_sharrow_skip

field SHADOW_PRICE_TABLE: str | None = None#
Validated by:

  • update_sharrow_skip

field SIMULATE_CHOOSER_COLUMNS: list[str] | None = None#
Validated by:

  • update_sharrow_skip

field SIZE_TERM_SELECTOR: str | None = None#
Validated by:

  • update_sharrow_skip

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.

Validated by:

  • update_sharrow_skip

field annotate_households: PreprocessorSettings | None = None#
Validated by:

  • update_sharrow_skip

field annotate_persons: PreprocessorSettings | None = None#
Validated by:

  • update_sharrow_skip

field annotate_tours: PreprocessorSettings | None = None#
Validated by:

  • update_sharrow_skip

field compute_settings: ComputeSettings = ComputeSettings(sharrow_skip=False, fastmath=True, use_bottleneck=None, use_numexpr=None, use_numba=None, drop_unused_columns=True, protect_columns=[])#

Sharrow settings for this component.

Validated by:

  • update_sharrow_skip

field explicit_chunk: float = 0#

If > 0, use this chunk size instead of adaptive chunking. If less than 1, use this fraction of the total number of rows.

Validated by:

  • update_sharrow_skip

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.

Validated by:

  • update_sharrow_skip

validator update_sharrow_skip  »  all fields#

Examples#

Implementation#

activitysim.abm.models.joint_tour_destination.joint_tour_destination(state: State, tours: DataFrame, persons_merged: DataFrame, network_los: Network_LOS, model_settings: TourLocationComponentSettings | None = None, model_settings_file_name: str = 'joint_tour_destination.yaml', trace_label: str = 'joint_tour_destination') → None#

Given the tour generation from the above, each tour needs to have a destination, so in this case tours are the choosers (with the associated person that’s making the tour)

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