Joint Tour Scheduling#
The joint tour scheduling model selects a tour departure and duration period (and therefore a start and end period as well) for each joint tour. This model uses person time_windows. The primary drivers in the models are accessibility-based parameters such as the auto travel time for the departure/arrival hour combination, demographics, and time pattern characteristics such as the time windows available from previously scheduled tours. The joint tour scheduling model does not use mode choice logsums.
The main interface to the joint tour purpose scheduling model is the joint_tour_scheduling function. This function is registered as an Inject step in the example Pipeline.
Structure#
Configuration File:
joint_tour_scheduling.yaml
Core Table:
tours
Result Field:
start, end, duration
Skims Keys:
TAZ, destination, MD time period, MD time period
Configuration#
- settings activitysim.abm.models.joint_tour_scheduling.TourSchedulingSettings#
Bases:
LogitComponentSettings
- Config:
extra: str = forbid
- Fields:
ALTS_PREPROCESSOR (PreprocessorSettings | dict[str, PreprocessorSettings])
COEFFICIENTS (Path | None)
CONSTANTS (dict[str, Any])
DESTINATION_FOR_TOUR_PURPOSE (str | dict[str, str] | None)
LOGIT_TYPE (Literal['MNL', 'NL'])
LOGSUM_PREPROCESSOR (str)
LOGSUM_SETTINGS (Path | None)
NESTS (LogitNestSpec | None)
SIMULATE_CHOOSER_COLUMNS (list[str] | None)
SPEC (Path | None)
SPEC_SEGMENTS (dict[str, LogitComponentSettings])
TOUR_SPEC_SEGMENTS (dict[str, str])
compute_settings (ComputeSettings)
explicit_chunk (float)
preprocessor (PreprocessorSettings | None)
source_file_paths (list[Path])
- Validators:
update_sharrow_skip
»all fields
- field ALTS_PREPROCESSOR: PreprocessorSettings | dict[str, PreprocessorSettings] = {}#
If the alternatives preprocessor is a single PreprocessorSettings object, it is assumed to be an unsegmented preprocessor. Otherwise, the dict keys give the segements.
- 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 DESTINATION_FOR_TOUR_PURPOSE: str | dict[str, str] | None = None#
- Validated by:
update_sharrow_skip
- field LOGIT_TYPE: Literal['MNL', 'NL'] = 'MNL'#
Logit model mathematical form.
- “MNL”
Multinomial logit model.
- “NL”
Nested multinomial logit model.
- Validated by:
update_sharrow_skip
- 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:
update_sharrow_skip
- field SPEC: Path | None = None#
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. If SPEC_SEGMENTS is given, then this unsegmented SPEC should be omitted.
- Validated by:
update_sharrow_skip
- field SPEC_SEGMENTS: dict[str, LogitComponentSettings] = {}#
- 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 preprocessor: PreprocessorSettings | None = None#
Setting for the preprocessor.
- 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
- classmethod nests_are_for_nl(nests, values)#
Checks that nests are provided if (and only if) LOGIT_TYPE is NL.
- validator update_sharrow_skip » all fields#
Examples#
Implementation#
- activitysim.abm.models.joint_tour_scheduling.joint_tour_scheduling(state: State, tours: DataFrame, persons_merged: DataFrame, tdd_alts: DataFrame, model_settings: TourSchedulingSettings | None = None, model_settings_file_name: str = 'joint_tour_scheduling.yaml', trace_label: str = 'joint_tour_scheduling') None #
This model predicts the departure time and duration of each joint tour