Agile Solutions for Challenging Times

The IRTAD 2026 conference highlighted a major shift in road safety practice, driven by advances in AI, connected vehicle data, and international collaboration. From explainable machine learning models delivering significant gains in fatality reduction to critical insights on data bias and ethical governance, the field is moving beyond prediction toward transparent, proactive systems. At the same time, new evidence on under-reporting, inequality, and policy effectiveness is reshaping how countries design and evaluate road safety strategies globally.

The 2026 IRTAD Conference in Athens brought together 141 research papers under the theme "Better Road Safety Data for Better Safety Performance. The role of international road safety data in local best practice," a clear message emerged: the road safety community is fundamentally shifting from reactive collision analysis toward proactive risk assessment. This transformation, evident across presentations from Agilysis colleagues and international partners, represents both the field's greatest opportunity and its most complex challenge.

The Agilysis team of Nathan Harpham, Drishti Khatri, Dan Campsall, and Richard Owen have spent the last few weeks reviewing the new road safety casualty reduction targets with the aim of seeing how close we may get based on previous performance. The results are in some ways promising, but still fall way short of the requirement. Read on to learn more about the targets, prior performance, our modelling methodology, and how policy changes can help make rapid progress.