Data cluster

Thailand Road Accident Data.

Road crashes, deaths, injuries, police road-safety dashboards, and transport-risk context for route and destination safety pages.

4 sources Updated 2026-05-11 Download JSON

Best use for travel intelligence

For travel decisions, road-accident data is often the most actionable public safety layer in Thailand because it changes whether a drive, scooter plan, or holiday route still looks wise.

What this changes for travelers

  • Driving and scooter caution: Improves decisions about self-drive, motorcycles, long transfers, and holiday travel windows.
  • Route realism: Helps travelers see when a route is riskier than a generic city safety page suggests.
  • Major-accident pressure: Adds real operational context that often matters more than slower crime statistics.

Best sources to start with

  • Best current public dashboard: ThaiRSC road accident center for deaths, injuries, province-level context, and risk points.
  • Best police road-safety source: PRS Open Data police road accidents for police road-safety summary context and risk analysis.
  • Best official transport baseline: MOT road accident datasets for published batch datasets and broader route-risk context.
  • Best developer starting point: Separate crash events or daily summaries from general crime tables, and keep cause, location, deaths, injuries, and major-accident flags visible.
Official / agency sources

2 of 4 sources look official or agency-backed.

API/feed candidates

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

Near-real-time signals

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

Developer note

Keep crash totals, injuries, deaths, road names, and risk points separate from police crime tables because road risk is a different product with a stronger realtime signal.

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.