The various rapid advances in computer systems and new algorithms have applications in all aspects of transport, and road safety could not be an exception. Artificial Intelligence (AI)-based modelling has become more accessible and approachable, and road safety experts have been acquiring new knowledge on how to enhance road safety in the examined networks using increasingly sophisticated algorithms. Simultaneously, data collection is becoming more affordable, seamless, voluminous and multifaceted, departing from traditional, rare road safety indicators, such as crashes and casualties, to an array of surrogate safety measures with high recording frequency, such as harsh events, Time-To-Collision or a wealth of driver behavior data. The aim of the present chapter is to provide an overview of current progress. Specifically, aspects of AI for (i) modelling road user behavior, (ii) modelling network-level performance and (iii) conducting in-depth crash analysis are discussed. Promising research directions to be explored in the imminent future are presented as well, in the form of high-impact feature engineering, crash and injury causality analyses and ethical AI applications.
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