Skip to main content

Convert GTFS blocks to trip-to-trip transfers

Project description

gtfs-blocks-to-transfers

Converts GTFS blocks, defined by setting trip.block_id into a series of trip-to-trip transfers (GTFS specification). Uses configurable heuristics to predict whether two trips are connected as in-seat transfers or as vehicle continuations only. This tool also validates predefined trip-to-trip transfers in transfers.txt.

Usage: ./convert.py <input feed> <directory for output>

Install

The easiest way to install the tool is to clone this repository, then run pip install -e .

If that doesn't work, try to run python3 manual_install.py.

Publishing

Package publishing is automated via GitHub Actions. Bump the version in pyproject.toml and merge to master to trigger publication to PyPI.

How it works

Throughout this tool, sets of service days are used to relate trips. They are defined in service_days.py, and are represented as a bitmap per service_id, with bit n set to 1 if that service operates on the nth day since the beginning of the feed. The term trip's service days refers to the service days for trip.service_id. If the first departure of a trip is after 24:00:00, the service days are stored as-if the trip began the next day between 00:00:00 and 23:59:59.

For each block defined in the feed, convert_blocks.py finds the most likely continuations for each trip, starting the search after the final arrival time of the trip. The program searches for a matching continuation for all of the trip's service days, greedily selecting continuation trips in order of wait time. Some days may remain unmatched if a configurable threshold is exceeded (config.TripToTripTransfers.max_wait_time). classify_transfers.py uses heuristics to assign transfer_type=4 (in-seat transfer) or transfer_type=5 to each continuation.

Generated transfers are combined with predefined transfers from transfers.txt in simplify_graph.py. If necessary, this step will split trips such that for any given from_trip_id, each of the potential to_trip_id, will operate on a disjoint set of service days. For example bus 50 could continue to bus 15 on Monday through Thursday, but continue to bus 20 on Fridays. Both generated and predefined transfers are validated to ensure they are unambiguous and conform to the specification.

simplify_export.py converts the continuation graph back to a series of transfers, resuing the feed's existing trip_ids and service_ids when an exact match can be found, or creating new entities if required. This step will preserve trip-to-trip transfers that don't represent vehicle continuations (e.g. transfer_type=2 used to estimate walk time between two vehicles).

Heuristics

An in-seat transfer is likely if:

  • Riders only need to wait a short time between trips.
  • The next trip begins at the same stop as the preceding trip ended, or the two stops are very close to each other.
  • The next trip goes a different destination than the preceding trip, or the two trips serve a loop route.

Riders probably won't be able to, or want to, to stay on board if:

  • The wait time aboard the bus is quite long.
  • The next trip is very similar to the preceding trip, but in reverse. We assess similarity by comparing the sequence of stop locations of the two trips using a modified Hausdorff metric.

You can adjust thresholds or entirely disable a heuristic in blocks_to_transfers/config.py. Configuration can also be provided as a JSON string with the --config argument.

Special continuations

Precise rules can also be added to enable or disable in-seat transfers for particular stops and routes within a feed.

A rule is a JSON object consisting of three parts:

  • match: A list of selectors.
  • op: The action to take on matching predicted continuations.
    • modify: Change the transfer_type.
    • More operations are planned in the future.
  • transfer_type: Only for modify operations. The new transfer_type to assign,
    • 4: in-seat transfer
    • 5: vehicle continuation only
    • (Transit's internal use) 104: in-seat transfer for trip planner only

The following selectors are supported:

  • All selectors will match any trip-to-trip transfers.
    • Example: {"all": true}
    • This selector may not be combined with any other selector.
  • Through selectors will match either the from_trip or the to_trip.
    • Example: {"through": {"route": "1", "stop": "Terminus Longueuil"}}
    • You can specify a route (route short name), a stop (stop name), or both.
    • This selector may not be combined with any other selector.
  • From selectors will match on the from_trip.
    • Example: {"from": {"route": "20", "last_stop": "Osachoff / White"}}
    • You can specify a route, a last_stop, or both.
  • To selectors will match on the to_trip.
    • Example: {"to": {"route": "5T", "first_stop": "Stewart Creek"}}
    • You can specify a route, a first_stop, or both.
  • From and to selectors can be combined to match a particular continuation between two trips].
    • Example: {"from": {"route": "124", "last_stop": "3rd / Pine"}, "to": {"route": "26", "first_stop": "3rd / Pine"}}

When a transfer matches multiple rules, the last rule wins. For transfers predicted from blocks, special continuation rules override all heuristics except max_wait_time. Rules never apply to predefined transfers specified using transfers.txt.

For example, to enable in-seat transfers only for routes 20 and 99 the following configuration can be set:

{
    "SpecialContinuations": [
        {
            "match": [
                {"all": true}
            ],
            "op": "modify",
            "transfer_type": 5
        },
        {
            "match": [
                {"through": {"route": "20"}},
                {"through": {"route": "99"}}
            ],
            "op": "modify"
            "transfer_type": 4
        }
    ]
} 

Advanced

  • simplify_linear.py: You probably don't want to enable this option, unless your system happens to have the same constraints described in this section. If enabled, trips will be split so that each trip has at most one incoming continuation, and at most one outgoing continuation. Where cycles exist (e.g. an automated people mover that serves trip 1 -> trip 2 -> trip 1 every day until the end of the feed), back edges are removed. Trips that decouple into multiple vehicles, or that are formed through the coupling of multiple vehicles are preserved as is.
  • Test cases can be found in the tests/ directory.
  • This program will run much faster using PyPy, a jitted interpreter for Python.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gtfs_blocks_to_transfers-1.8.2.tar.gz (23.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

gtfs_blocks_to_transfers-1.8.2-py3-none-any.whl (26.2 kB view details)

Uploaded Python 3

File details

Details for the file gtfs_blocks_to_transfers-1.8.2.tar.gz.

File metadata

  • Download URL: gtfs_blocks_to_transfers-1.8.2.tar.gz
  • Upload date:
  • Size: 23.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for gtfs_blocks_to_transfers-1.8.2.tar.gz
Algorithm Hash digest
SHA256 5b2d802953c614fece2f9fb4712524d41f741546da566e7a6088dc4f8a94df44
MD5 45ae77276fd8b863f0bb8a0e748c2505
BLAKE2b-256 ef0795a31f2678fccaf69e58aabf0f8a77de70bca88a2c08f75feaa9635d8876

See more details on using hashes here.

File details

Details for the file gtfs_blocks_to_transfers-1.8.2-py3-none-any.whl.

File metadata

File hashes

Hashes for gtfs_blocks_to_transfers-1.8.2-py3-none-any.whl
Algorithm Hash digest
SHA256 e8a0cf2d39454577937403a095a3c4509f83204b588b50ea7fa82abca8dd4f5d
MD5 54e4fd043bdaa705bcccdae1c38ea4fb
BLAKE2b-256 f308ee4fb573fba6e76e8da6590651f3763df9b8fe8215753215a4c37004ae38

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page