Park-and-ride lot choice and capacity#1001
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Required to maintain backwards compatibility in tour indexes in SANDAG models
jpn--
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February 26, 2026 19:37
dhensle
marked this pull request as ready for review
March 19, 2026 17:14
This was referenced Apr 2, 2026
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@copilot resolve the merge conflicts in this pull request |
jpn--
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Jun 24, 2026
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Mostly good. That several agencies have collaborated and tested this already gives some extra confidence. Only a couple minor bugs/concerns to address.
| persons = state.get_dataframe("persons") | ||
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| # don't know a-priori how many park-and-ride tours there are at the start of the model run | ||
| # giving the buffer a size equal to the number of persons should be sufficient |
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This is probably fine most of the time, but in the outside chance that the number of PnR tours does exceed the number of persons, the model is going to crash hard later, probably just after line 159 where pad will become negative.
| synced_choices = synced_choices.sort_index() | ||
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| # now append any additional rows need to get size back to original length | ||
| pad = len(self.shared_pnr_choice) - len(synced_choices) |
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We should intercept here if pad is negative, maybe crash gracefully explaining that the number of PnR tours was unexpectedly greater than the number of persons, instead of crashing with an arcane "negative dimensions are not allowed" error from deep in this code. (see initialization comment below)
| .astype(int) | ||
| ) | ||
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| elif self.model_settings.RESAMPLE_STRATEGY == "random": |
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There's no testing of RESAMPLE_STRATEGY == "random"
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| # count the total number of pnr choices being resimulated | ||
| pnr_counts = ( | ||
| current_sample.pnr_zone_id.value_counts() |
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I tried making a simple test for "random" but it failed here, current_sample seems to be a pd.Series.
The correct code might be:
pnr_counts = (
tours_in_cap_zones.loc[current_sample.index, "pnr_zone_id"]
.value_counts()
.reindex(self.shared_pnr_occupancy_df.index)
.fillna(0)
.astype(int)
)
| ---------- | ||
| choices : pandas.Series | ||
| zone id of location choice indexed by person_id | ||
| segment_ids : pandas.Series |
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This function does not take segment_ids
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Pull request overview
Implements explicit Park-and-Ride (PnR) lot choice and capacity-constrained iteration with tour mode choice, and extends skimming/logsum/matrix-writing infrastructure so PnR auto/transit legs can be modeled and reported without relying on expensive precomputed PnR skim sets.
Changes:
- Added a new
park_and_ride_lot_choicemodel plusParkAndRideCapacityhelper to iterate tour mode choice until PnR lots are within capacity. - Extended skim plumbing (
flow,logsums, tour scheduling logsums) to support origin→lot and lot→destination skims and optional inclusion of PnR in logsum computation. - Updated trip matrix writing to support table-specific origin/destination columns (enabling PnR leg matrix outputs) and added tests for both PnR iteration and matrix writing behavior.
Reviewed changes
Copilot reviewed 19 out of 19 changed files in this pull request and generated 7 comments.
Show a summary per file
| File | Description |
|---|---|
| activitysim/core/util.py | Keeps pnr_lot_dest_col_name columns when dropping unused chooser columns. |
| activitysim/core/steps/output.py | Adjusts data dictionary text formatting width calculation. |
| activitysim/core/mp_tasks.py | Allocates shared multiprocessing buffers for PnR capacity iteration when configured. |
| activitysim/core/flow.py | Adds support for PnR lot destination column and additional PnR skim relationships. |
| activitysim/core/configuration/logit.py | Adds settings flags for at-work PnR and optional PnR inclusion in logsums. |
| activitysim/abm/test/test_misc/test_tour_mode_choice_simulate.py | New integration-style tests for tour mode choice with/without PnR iteration. |
| activitysim/abm/test/test_misc/test_park_and_ride_models.py | New unit tests for PnR lot choice filtering, utilities, and capacity synchronization logic. |
| activitysim/abm/tables/disaggregate_accessibility.py | Updates nearest accessibility zone helper signature to accept model settings. |
| activitysim/abm/models/util/vectorize_tour_scheduling.py | Integrates optional PnR lot choice into tour scheduling logsum computation and centralizes skim setup. |
| activitysim/abm/models/util/test/test_write_matrices.py | New tests validating matrix writing with custom OD columns for PnR legs. |
| activitysim/abm/models/util/school_escort_tours_trips.py | Tightens integer casting to explicit int64 dtype. |
| activitysim/abm/models/util/park_and_ride_capacity.py | New multiprocessing-aware PnR capacity accounting and chooser resampling logic. |
| activitysim/abm/models/util/logsums.py | Adds shared setup_skims helper and optional PnR lot choice during logsum creation. |
| activitysim/abm/models/trip_matrices.py | Supports per-table origin/destination columns and accumulating repeated table names into a single matrix. |
| activitysim/abm/models/tour_mode_choice.py | Adds iterative PnR capacity-constrained tour mode choice and reuses shared skim setup. |
| activitysim/abm/models/park_and_ride_lot_choice.py | New PnR lot choice model implementation and settings schema. |
| activitysim/abm/models/disaggregate_accessibility.py | Adds NEAREST_ZONE_SKIM configuration for nearest-zone selection behavior. |
| activitysim/abm/models/atwork_subtour_mode_choice.py | Adds optional at-work subtour PnR lot choice integration and shared skim setup. |
| activitysim/abm/models/init.py | Registers the new park_and_ride_lot_choice model module. |
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| with open(state.get_output_file_path(txt_format), "w") as output_file: | ||
| # get max schema column widths from omnibus table | ||
| col_width = {c: schema_df[c].str.len().max() + 2 for c in schema_df} | ||
| col_width = {c: int(schema_df[c].str.len().max()) + 2 for c in schema_df} |
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| def return_no_choices(state, choosers: pd.DataFrame, original_index=None) -> pd.Series: | ||
| logger.debug( | ||
| "No choosers with transit accessible destinations found. Returning -1 as park-and-ride lot choice." | ||
| ) | ||
| # need to drop rng channel that we created before trn_accessible_choosers | ||
| state.get_rn_generator().drop_channel("pnr_lot_choice") | ||
| index = choosers.index if original_index is None else original_index | ||
| return pd.Series(data=-1, index=index) |
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| if "pnr_zone_id" in subtours_merged.columns: | ||
| if model_settings.run_atwork_pnr_lot_choice: | ||
| subtours_merged["pnr_zone_id"] = run_park_and_ride_lot_choice( | ||
| state, | ||
| choosers=subtours_merged.copy(), | ||
| land_use=state.get_dataframe("land_use"), | ||
| network_los=network_los, | ||
| model_settings=None, | ||
| choosers_dest_col_name="destination", | ||
| choosers_origin_col_name="workplace_zone_id", | ||
| estimator=None, | ||
| pnr_capacity_cls=None, | ||
| trace_label=tracing.extend_trace_label(trace_label, "pnr_lot_choice"), | ||
| ) | ||
| else: | ||
| subtours_merged["pnr_zone_id"].fillna(-1, inplace=True) | ||
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| # now append any additional rows need to get size back to original length | ||
| pad = len(self.shared_pnr_choice) - len(synced_choices) | ||
| new_arr_values = np.concatenate( | ||
| [ | ||
| synced_choices["pnr_zone_id"].to_numpy(np.int64), | ||
| np.zeros(pad, dtype=np.int64), | ||
| ] | ||
| ) |
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| def find_nearest_accessibility_zone( | ||
| state: workflow.State, choosers, accessibility_df, method="skims" | ||
| state: workflow.State, model_settings, choosers, accessibility_df, method="skims" | ||
| ): |
| model_settings_file_name: str = "park_and_ride_lot_choice.yaml", | ||
| pnr_capacity_cls: ParkAndRideCapacity | None = None, | ||
| trace_label: str = "park_and_ride_lot_choice", | ||
| ) -> None: |
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| if model_settings is None: | ||
| model_settings = ParkAndRideLotChoiceSettings.read_settings_file( | ||
| state.filesystem, | ||
| "park_and_ride_lot_choice.yaml", | ||
| ) | ||
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Code changes for #965