Road Accident Risk Factors for Schools in Rural Thailand, 2020

Ratchanee Joomjee's study investigates accident likelihood on school routes in Thailand's Ubon Ratchathani Province from April to December 2020. The research employed the Haddon Matrix, Fault Tree Analysis, and Analytic Hierarchy Process (FTA-AHP) techniques. Findings identified human error, environmental factors like speeding, and vehicle equipment issues as the highest risk factors.

Use Cases

• Prioritizing road safety interventions based on identified high-risk factors like human error and speeding.
• Modeling accident probability near schools using fault tree analysis and analytic hierarchy process techniques.
• Informing infrastructure and policy design for student safety based on environmental and vehicle-related risk factors.

Strengths

• Study employs multiple established research tools: Haddon Matrix, Fault Tree Analysis (FTA), and Analytic Hierarchy Process (AHP).
• Research conducted over a defined period (April to December 2020) in a specific geographic area (Ubon Ratchathani Province, Thailand).
• Identifies three concrete, high-level risk factor categories: human error, environmental factors, and vehicle/equipment issues.

Limitations

• Row count and column-level documentation are absent; field semantics must be inferred after download.
• Data may reflect geographic and temporal bias inherent to a single-province study conducted in 2020.
• Last update date is unknown; freshness unverified.

Provenance

Source

Ratchanee Joomjee via paperswithcode

Collection Method

Cross-sectional study employing Haddon Matrix, Fault Tree Analysis, and Analytic Hierarchy Process (FTA-AHP).

Time Range

April to December 2020

Geography

Ubon Ratchathani Province, Thailand