Using Machine Learning In Road Safety Research

Road traffic fatalities remain a critical global challenge, with young people being disproportionately affected. Drink-driving, or Driving Under the Influence (DUI), is a major contributor to these preventable tragedies, accounting for 5% to 35% of all road fatalities worldwide.

As the global community works toward the goals of the UN Decade of Action for Road Safety 2021-2030 , the need for innovative, evidence-based, and effective interventions has never been more urgent. With the objective of informing the design and implementation of targeted interventions , UNITAR and York University are releasing the study "Understanding the Impacts of Drink-Driving for Youth: Contributing Factors, Behavioural Trends, Public Sentiments, and Preventative Interventions".

This publication employs a unique mixed-methods approach, combining a large-scale meta-analysis of scientific literature with machine learning (AI) techniques to strengthen the evidence base for road safety practice. Grounded in a comprehensive systematic review conducted under PRISMA guidelines, this study synthesizes global research on contributing factors, behavioural patterns, and the effectiveness of interventions aimed at reducing drink-driving among youth.

This research uses Large Language Models (LLMs) to analyse public discourse, examining extensive datasets from social media platforms such as Reddit and YouTube with Sentiment Analysis (SA) and Topic Modelling (TM) to capture public attitudes and perceptions beyond traditional surveys. Building on these insights, the study introduces a prototype Drink-Driving Impact Awareness AI Tool, which leverages a Retrieval-Augmented Generation (RAG) architecture to provide users with meaningful insights into the real-world consequences of drink-driving, with a particular focus on youth.

This publication aims to be a resource for professionals working in the road safety field, especially those responsible for designing and implementing policies and interventions targeting youth. By harnessing the power of new technologies to better understand and address persistent challenges, this publication seeks to serve as a useful resource and a contribution to our collective efforts to achieve the targets of the Decade of Action for Road Safety.

Link to Download Full Publication Here

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