Data cluster

Thailand Taxi Complaints and Safety Data.

DLT 1584 complaint data, DLT GPS complaint channels, public-safety context, and passenger-protection caveats.

3 sources Updated 2026-05-11 Download JSON

Best use for travel intelligence

For travel decisions, taxi complaint data helps with trust, expectations, and complaint-channel guidance rather than live service monitoring.

What this changes for travelers

  • 1584 complaint stats: Historical complaint volume and issue-type context for public transport, including taxi-related categories.
  • Complaint channels: How travelers can escalate refusal, overcharge, unsafe driving, or service mismatch issues.
  • Trust scoring: A trend layer for risk and expectation setting, not an operational realtime quality feed.
  • DLT GPS app: A passenger-facing route to report issues where regulated vehicle context matters.

Best sources to start with

  • Best official complaint dataset: DLT 1584 complaint statistics and public annual-report context for complaint type and vehicle-category trends.
  • Best public complaint channels: DLT hotline 1584, DLT GPS, web complaint service, and public complaint guidance.
  • Best travel use: Trust and expectation setting for taxi, motorcycle-taxi, and ride-hailing pages.
  • Best developer starting point: Store period, vehicle type, complaint issue, count, channel, source URL, and the distinction between historical data and live complaint intake.
Official / agency sources

1 of 3 sources look official or agency-backed.

API/feed candidates

1 sources expose API, feed, CKAN/DataStore, JSON, XML, or similar machine-readable access.

Near-real-time signals

1 sources have live, hourly, event-driven, warning, or frequent update language.

Developer note

Keep historical complaint tables separate from operational complaint intake; public data is for trend analysis, not personal-case resolution.

Last checked and source confidence

Last checked: 2026-05-11.

Source confidence: This cluster is strongest when several sources describe the same traveler problem from different angles: official context, machine-readable feeds, and slower fallback documentation.