dr-pod/data-dive-mtd-gtfs-rt

CUMTD GTFS-Realtime archive (Apr 23 – Apr 29 2026)

A timestamped public archive of the Champaign-Urbana Mass Transit District (CUMTD / MTD) GTFS-Realtime feeds, captured from the public endpoints at https://gtfs-rt.mtd.org. To my knowledge no continuous public archive of CUMTD's real-time feeds exists; the live feeds overwrite themselves.

Window: 2026-04-23 ~05:30 UTC → 2026-04-29 23:42 UTC (~6.76 days).

Feeds archived

feed	endpoint	poll interval
vehicle_positions	/vehicle-positions	5 s
trip_updates	/trip-updates	5 s
service_alerts	/service-alerts	300 s

MTD's empirical refresh rate is ~2 s on the position/trip feeds; 5-second polling captures essentially every refresh while leaving slack for jitter.

Layout

{feed}/YYYY-MM-DD/HH.pb.gz       # concatenated length-prefixed protobufs
{feed}/YYYY-MM-DD/HH.index.jsonl # one record per poll

The .pb.gz is a gzip-wrapped stream of <uint32 BE length><protobuf bytes> records, ordered by poll time. The sidecar .index.jsonl has one JSON record per poll, lining up 1:1 with records in the .pb.gz. Each index record:

{"ts": "2026-04-25T18:00:00+00:00",
 "feed_ts": 1714068000,
 "http_status": 200,
 "entity_count": 43,
 "bytes": 4998,
 "err": null}

Decoding

import gzip, struct
from google.transit import gtfs_realtime_pb2

with gzip.open("vehicle_positions/2026-04-25/18.pb.gz", "rb") as f:
    while True:
        head = f.read(4)
        if not head: break
        n, = struct.unpack(">I", head)
        msg = gtfs_realtime_pb2.FeedMessage()
        msg.ParseFromString(f.read(n))
        # iterate msg.entity

Provenance & license

• Source: CUMTD public feeds (no authentication, polite User-Agent).
• Archived by Darsh Poddar, UIUC undergrad, as part of an academic research project on UIUC class-release pedestrian surges and bus delays at signalized intersections. Code: https://github.com/drPod/data-dive
• License: CC-BY 4.0. Acknowledge CUMTD when republishing derived data.

Citation

Darsh Poddar (2026). CUMTD GTFS-Realtime archive (Apr 23 – Apr 29 2026).
Hugging Face. dr-pod/data-dive-mtd-gtfs-rt.

Notable fields in vehicle_positions

Beyond the standard GTFS-RT position/trip/vehicle fields, CUMTD populates two fields that are valuable for delay and crowding analysis:

field	values observed	use
occupancy_status	EMPTY, MANY_SEATS_AVAILABLE, FEW_SEATS_AVAILABLE	Passenger-load proxy (strongest single feature for delay prediction in the literature). Present on every entity.
congestion_level	RUNNING_SMOOTHLY (others possible)	Road-traffic signal.

These are present across the full archive window (Apr 23–29 2026).

MTD attribution

This dataset uses data from the Champaign-Urbana Mass Transit District (CUMTD / MTD). Per the MTD API Terms of Use, any use of MTD data must include the following identification:

Data provided by the Champaign-Urbana Mass Transit District (CUMTD). For more information, visit mtd.dev.