Dev/merge to master

.gitignore

@@ -5,6 +5,7 @@ run_private*.py
 data/README*
 data/demand/*
 !data/demand/example_demand
+!data/demand/sumo_example
 !data/demand/example_parcel_demand
 data/fleetctrl/initial_vehicle_distribution/*
 data/fleetctrl/elastic_pricing/*
@@ -20,8 +21,10 @@ data/networks/*
 data/networks/example_network/ff/*
 data/networks/example_network/ch_graph/*
 data/networks/example_network/base/*.graph
-data/pubtrans/*
-!data/pubtrans/route_193
+!data/networks/sumo_example
+data/pt/*
+!data/pt/route_193
+!data/pt/example_network
 data/vehicles/*
 !data/vehicles/default_vehtype.csv
 !data/vehicles/low_range_vehtype.csv
@@ -35,11 +38,15 @@ data/zones/*
 # study directories except for example and example case studies
 studies/*
 !studies/example_study
+!studies/fleetpy_sumo_coupling
+studies/fleetpy_sumo_coupling/results/*
 studies/example_study/results/*
 studies/example_study/git_info.txt
+!studies/module_tests
 !studies/module_tests/*
 studies/module_tests/results/*
 studies/module_tests/git_info.txt
+studies/module_tests/benchmark_comparison.csv
 !studies/module_tests/results/benchmark.csv
 !studies/manhattan_case_study
 studies/manhattan_case_study/results/*
@@ -54,15 +61,18 @@ studies/munich_case_study/git_info.txt
 *zip
 
 # system dependent C++ Router files
-src/routing/cpp_router/*.pyd
-src/routing/cpp_router/build/*
-src/routing/cpp_router/PyNetwork.cpp
-src/routing/extractors/cache/*
+src/routing/road/cpp_router/*.pyd
+src/routing/road/cpp_router/build/*
+src/routing/road/cpp_router/PyNetwork.cpp
+src/routing/road/extractors/cache/*
+
+src/routing/pt/cpp_raptor_router/PyPTRouter.cpp
+src/routing/pt/cpp_raptor_router/build/*
 
 # IDE-related files
 *.idea
 .vscode/*
-src/routing/cpp_router/.vs/*
+src/routing/road/cpp_router/.vs/*
 
 # Byte-compiled / optimized / DLL files
 __pycache__/
@@ -195,3 +205,10 @@ dmypy.json
 # Pyre type checker
 .pyre/
 
+# other
+CLAUDE.md
+# MacOS
+.DS_Store
+
+# GTFS preprocessing file
+!src/preprocessing/pt/PTRouterGTFSPreperation.ipynb

README.md

@@ -66,10 +66,17 @@ conda activate fleetpy
 
 ### 2️⃣ Install C++ Router (Recommended)
 
-For improved routing efficiency, compile the C++ router:
+For improved road network routing efficiency, compile the C++ road router:
 
 ```bash
-cd FleetPy/src/routing/cpp_router
+cd FleetPy/src/routing/road/cpp_router
+python setup.py build_ext --inplace
+```
+
+To enable public transport routing, compile the C++ RAPTOR router:
+
+```bash
+cd FleetPy/src/routing/pt/cpp_raptor_router
 python setup.py build_ext --inplace
 ```
 

changelog.md

@@ -2,6 +2,142 @@
 
 All notable changes to this project will be documented in this file.
 
+## [1.1.0] - 2025-12-18
+
+Key update:
+1. Refactored routing file structure: road-related routing modules are moved to the `road` subdirectory, and PT-related routing modules are moved to the `pt` subdirectory.
+2. Introduced a C++ routing module based on the RAPTOR algorithm for querying the fastest PT travel plans between two stations.
+3. Introduced the PTControl module to simulate PT operator behavior, such as recording offer information and dynamically updating GTFS files.
+4. Introduced three PTBroker strategy variants to simulate different levels of MaaS–DRT coordination for intermodal requests: Plan-As-You-Go (PTBrokerPAYG), Estimation-based Integration (PTBrokerEI), and Collaborative Coordination (PTBroker).
+5. Introduced subrequest ID coding rules for intermodal scenarios, using unique integers to classify legs and `{parent_rid}_{subtrip_id}` to define new subrequest IDs.
+6. Socket-based coupling to MATSim/Eqasim where FleetPy models the DRT operator
+7. Coupling to SUMO: Vehicles move in a microscopic SUMO simulation
+8. Travellers can start and end anywhere on an edge
+
+### Added
+- cpp_raptor_router: C++ implementation of the PT router based on the RAPTOR algorithm
+
+- RaptorRouterCpp: Python entry point for the PT router, responsible for activating the cpp_raptor_router instance and regularizing PT requests
+
+- PTControlBase & PTControlBasic: Modules to simulate PT operator behavior, such as recording offer information and dynamically updating GTFS files
+
+- PTOffer: Class for recording PT offer information
+
+- IntermodalOffer: Class for recording offer information for intermodal requests
+
+- BasicIntermodalRequest: Class to simulate travel behavior of travelers with intermodal requests
+
+- example_100_intermodal.csv: Intermodal demand based on example_100.csv, containing 25 monomodal, 25 first-mile, 25 last-mile, and 25 first-last-mile requests
+
+- example_100_intermodal_lmwt30.csv: Variant of the intermodal demand file with a 30-second last-mile wait time constraint
+
+- example_gtfs: Public transport design based on example_network
+
+- PTBrokerBasic: Base class providing shared infrastructure for intermodal request handling across all PTBroker variants (FM, LM, FLM sub-request creation, offer assembly, booking confirmation)
+
+- PTBroker (Collaborative Coordination): Simulates a future scenario with tight MaaS–DRT integration. DRT provides a predicted FM dropoff time; PT feeds back the user's expected station waiting time, which MaaS uses to dynamically adjust the DRT dropoff deadline, giving DRT more pooling flexibility while guaranteeing PT connection. LM DRT wait time can also be constrained to minimize destination wait.
+
+- PTBrokerEI (Estimation-based Integration): Simulates current MaaS platforms with limited real-time DRT communication. FM dropoff time is estimated using `broker_maas_detour_time_factor` rather than obtained from an actual DRT offer. A conservative factor ensures PT is caught but increases travel time; an optimistic factor risks missing PT.
+
+- PTBrokerPAYG (Plan-As-You-Go): Simulates the absence of a MaaS platform. Each leg is planned only after the previous one completes (FM DRT → PT → LM DRT). Trips may be interrupted if a subsequent leg is unavailable.
+
+- intermodal_evaluation: Evaluation methods designed for intermodal scenarios
+
+- example_study & module_tests: Added intermodal scenario example experiments
+
+- globals: Added `RQ_MODAL_STATE`, `RQ_SUB_TRIP_ID`, and `PAYG_TRIP_STATE` enums for intermodal sub-request classification; added global variable names for PT (`G_PT_*`), intermodal offers (`G_IM_*`), and broker configuration (`G_BROKER_*`, including `G_BROKER_MAAS_DETOUR_TIME_FACTOR`, `G_BROKER_TRANSFER_SEARCH_METHOD`, `G_BROKER_ALWAYS_QUERY_PT`, `G_IM_LM_WAIT_TIME`)
+
+- init_modules: Added initialization code for PTControl and PTBroker modules
+
+- FleetSimulationBase: Added code to load PTControl and PTBroker modules
+
+- PlanRequest: Added `set_new_dropoff_time_constraint` method to update the passenger's latest drop-off time constraint
+
+- Demand: Added `create_sub_requests` method to establish sub-requests for corresponding legs of intermodal requests
+
+- RequestBase: Added `modal state` attribute (default: monomodal) and `get_modal_state` method
+
+- PTRouterGTFSPreperation: Jupyter notebook for cleaning and formatting raw GTFS data for RaptorRouterCpp
+
+- globals.py: REJECTION_REASON enum (OUT_OF_OPERATING_AREA, NO_VEHICLE_AVAILABLE, OUT_OF_SERVICE_TIME, INVALID_RQ) and G_OFFER_REJECTION_REASON for structured rejection output
+
+- globals.py: G_OP_MIN_RQ_DISTANCE parameter — operator can set a minimum direct travel distance for a request to be accepted; adds TRAVEL_DISTANCE to REJECTION_REASON
+
+- MATSimIterationForecast: New forecast module that uses requests from the last MATSim/Eqasim iteration to forecast future demand
+
+- create_historical_network_scaling.py: New preprocessing script to calculate dynamic scaling of network edges using historical trip durations
+
+- match_nodes_to_zones.py: New preprocessing script to match network nodes to zone systems
+
+- max_coverage.py: New preprocessing script to solve a max coverage problem (e.g. for zone or stop creation)
+
+- AlonsoMoraRepositioning: Now also loads a zone system when given (to check operating area)
+
+- PTBroker: Automatic cancellation mechanism when FM AMoD arrives too late for the PT connection
+
+- SUMOFleetPyServer: FleetPy server for SUMO traci-based coupling; manages vehicle insertion, demand handling, and travel time updates during a microscopic SUMO simulation
+
+- SUMOcontrolledSim: Simulation class for SUMO-controlled runs
+
+- NetworkBasicWithStoreOnlineMatrixCpp: New routing module that computes travel time matrices online during simulation (required for SUMO coupling with dynamic travel times)
+
+- network_from_sumo.py: Preprocessing script to convert a SUMO network to FleetPy format
+
+- demand_from_sumo.py: Preprocessing script to convert SUMO demand to FleetPy format
+
+- studies/fleetpy_sumo_coupling: Full example study for SUMO coupling including run script, scenario configs, and sumo_example network/demand
+
+- data/networks/sumo_example: Example road network for the SUMO coupling example study
+
+- MATSimSocket: Socket-based communication module for MATSim/Eqasim coupling; can be started with console arguments; performs network conversion (checking available modes per link) and network hash comparison across iterations
+
+- MATSimSimulationClass: Simulation class for MATSim/Eqasim-coupled runs; supports starting from a later iteration and cleans up travel time files/logs from the previous iteration at the start of each new run
+
+- misc.py (MATSimEqasim): Utility functions for the MATSim/Eqasim coupling
+
+- data/vehicles/single_user_vehtype.csv: Vehicle type file for single-user (non-pooled) scenarios
+
+- example_200_pos.csv: Demand file for testing position-based (arbitrary edge position) requests
+
+- module_tests: Added sc_config_rq_pos.csv scenario for position-based request module tests; updated benchmark_comparison.csv and results/benchmark.csv
+
+### Changed
+- BrokerBase & BrokerBasic: `collect_offers` method now accepts an input variable `sim_time` (int, default: None)
+
+- ImmediateDecisionsSimulation: Added `sim_time` input variable when calling `self.broker.collect_offers`
+
+- RequestBase: Updated `create_SubTripRequest` method to create intermodal sub-requests
+
+- insertion: `insertion_with_heuristics` and `reservation_insertion_with_heuristics` methods added `excluded_vid` input (list of vehicle IDs that should not be considered for assignment)
+
+- RollingHorizon: `return_immediate_reservation_offer` method added `excluded_vid` input
+
+- PoolingIRSOnly: `user_request` method added optional `max_wait_time` parameter (used for LM leg of intermodal requests); tracks `flm_excluded_vid` to exclude the FM vehicle from LM assignment in FLM requests
+
+- Vehicles: `assign_vehicle_plan` method now uses `rid_struct` to obtain request information
+
+- FleetSimulationBase: Modified public transportation module loading code; modified `evaluate` method to use `G_EVAL_METHOD` to specify standard result evaluation (default: standard_evaluation)
+
+- gitignore: Ignored specific C++ Router files
+
+- data/pubtrans/ renamed to data/pt/ and src/preprocessing/pubtrans/ renamed to src/preprocessing/pt/: standardized fixed-line transport service naming throughout the repository
+
+- MATSimSimulationClass: automatic evaluation of simulation results is now run at the end of each iteration
+
+- evaluation/temporal.py: `run_complete_temporal_evaluation` now saves per-operator evaluation results to a `temporal_eval.json` file in the output directory and returns the evaluation dictionary
+
+### Deprecated
+- globals: Traveler modal state global variables are no longer used (G_RQ_STATE_MONOMODAL, G_RQ_STATE_FIRSTMILE, G_RQ_STATE_LASTMILE, G_RQ_STATE_FIRSTLASTMILE)
+
+### Removed
+- globals: Traveler modal state global variable names
+
+### Fixed
+- RollingHorizon: Correctly retrieve `vid` and `veh_obj` in `user_cancels_request` method
+
+- FleetSimulationBase: In `update_sim_state_fleets`, ensured `rid_struct` is the actual key of the dictionary returned by `veh_obj.update_veh_state`
+
+
 
 ## [1.0.0] - 2025-04-DD
 

data/demand/example_demand/matched/example_network/example_100_intermodal.csv

@@ -0,0 +1,101 @@
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