UNITAR produces rigorous research and publications that advance understanding of road safety challenges and inform evidence-based interventions worldwide. Through systematic reviews, meta-analyses, and innovative applications of artificial intelligence and machine learning, these publications examine critical issues such as drink-driving among youth, behavioral trends, contributing factors, and the effectiveness of prevention strategies.
By linking insights to the UN Sustainable Development Goals, the Decade of Action for Road Safety 2021–2030, and the UN Decade of Sustainable Transport 2026-2035, the research provides actionable guidance for policymakers, government officials, educators, and practitioners seeking to improve road safety outcomes globally.
Understanding the Impacts of Drink-Driving for Youth
Understanding the Impacts of Drink-Driving for Youth: Contributing Factors, Behavioral Trends, Public Sentiments, and Preventative Interventions
Authors: Ali Asgary, Zahra Movahedi Nia, Iman Nezami, Peyman Naeemi, and Sharuka Promodya Thirimanne
Download Full Publication
Abstract
This groundbreaking study introduces an AI-based prototype tool using Large Language Models with Retrieval-Augmented Generation to deliver intervention content through real-world stories and documentaries, representing a novel application of artificial intelligence in road safety education.
It employs a unique mixed-methods approach combining meta-analysis, systematic review, and advanced machine learning techniques to comprehensively examine drink-driving among youth aged 15-25. The research synthesizes scientific literature while pioneering the use of social media analytics to understand public discourse and behavioral patterns related to driving under the influence (DUI).
The research underscores the importance of standardized, evidence-based approaches to address drink-driving among youth. It highlights that combining multiple intervention strategies, maintaining long-term engagement, and integrating innovative technologies can significantly improve outcomes. This publication serves as a reference for road safety researchers, policymakers, practitioners, and academics contributing to global initiatives aligned with the UN Sustainable Development Goals and the Decade of Action for Road Safety 2021–2030.
Publication Details:
- ISBN 978-2-9701428-1-2 (electronic version)
- ISBN 978-2-9701428-2-9 (print version)
- Year: 2025
- Partnership: UNITAR and York University
Download Full Publication
Assessing Attitudinal Change Towards Drinking and Driving - Coming Soon!
This upcoming publication explores applications of generative AI, virtual reality, and machine learning in assessing attitudinal and behavioural change related to drink-driving interventions. The research demonstrates how these technologies can customize assessment tools, create experiential learning environments, and predict intervention outcomes. Building on this technological foundation, the publication synthesizes nine major psychological theories, including theories of attitude formation, behavioural change, and integrative frameworks, to develop a comprehensive assessment toolkit. The framework addresses five attitude dimensions: risk perception, controllability beliefs, social normality, justifiability rationalizations, and negativity toward alternatives. By combining emerging technologies with established theoretical approaches, this resource offers practical, validated tools for measuring intervention effectiveness across diverse populations and cultural contexts.