SurvCancel / README.md
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metadata
license: cc-by-nc-sa-4.0
language:
  - en
pretty_name: SurvCancel
tags:
  - survival-analysis
  - dynamic-survival-analysis
  - transportation
  - demand-responsive-transit
  - ride-pooling
  - time-series
  - jsonl
configs:
  - config_name: default
    data_files:
      - split: train
        path: train-*.jsonl

SurvCancel

SurvCancel is an anonymized longitudinal dataset for dynamic passenger cancellation prediction in on-demand ride-sharing systems. Each JSONL record is one focal order with static trip attributes, a terminal outcome, and an ordered sequence of pre-pickup system snapshots. Snapshots are sampled every 10 seconds and include the focal order state, surrounding active orders, available vehicles, and the matched vehicle when present.

This release is intentionally flat: the four public region shards are exposed as one Hugging Face train split. Benchmark train/validation/test partitions are constructed by the accompanying code at the order level.

Release Statistics

The release contains 173,037 focal orders and 7,944,171 temporal snapshots.

Region shard Days Orders Snapshots Pre-match cancel Matched Post-match cancel Completed
R1 38 60,548 2,717,147 26,511 34,037 10,987 23,050
R2 72 6,518 240,075 310 6,208 872 5,336
R3 72 42,106 2,099,571 13,404 28,702 7,667 21,035
R4 72 63,865 2,887,378 10,449 53,416 10,651 42,765
Total -- 173,037 7,944,171 50,674 122,363 30,177 92,186

Files

  • train-R1.jsonl, train-R2.jsonl, train-R3.jsonl, train-R4.jsonl: public region shards
  • sample/sample_records.jsonl: small sample for smoke tests
  • SCHEMA.md: field-level schema

Loading With datasets

from datasets import load_dataset

dataset = load_dataset(
    "survcancel-anonymous/SurvCancel",
    split="train",
    streaming=True,
)

Load one region directly:

from datasets import load_dataset

r1 = load_dataset(
    "json",
    data_files="hf://datasets/survcancel-anonymous/SurvCancel/train-R1.jsonl",
    split="train",
    streaming=True,
)

Anonymization

Identifiers are replaced with salted HMAC-SHA256 surrogate strings:

  • order_id -> ord_*
  • vehicle_id and matched_vehicle_id -> veh_*
  • region_id -> reg_*

The same original identifier in the same namespace maps to the same surrogate. The private salt and source-to-surrogate mappings are not released. Coordinates are standardized planar coordinates, not raw latitude/longitude.

Intended Use

This dataset is intended for academic and non-commercial research on survival analysis, dynamic event prediction, demand-responsive transportation, ride-pooling, and cancellation or pickup time-to-event modeling.

License

This dataset is released under the Creative Commons Attribution-NonCommercial- ShareAlike 4.0 International License (CC BY-NC-SA 4.0).