Artificial Intelligence for Intelligent Road Communication: Systems and Strategies in Cameroon

Road safety in Cameroon remains a major concern, with thousands of deaths and significant economic losses recorded annually. Traditional road communication strategies have shown limited effectiveness, revealing a gap between the messages disseminated and their appropriation by road users. In this context, artificial intelligence (AI) emerges as a strategic resource to rethink prevention and traffic regulation. Intelligent Transport Systems (ITS) and digital tools such as navigation applications, smart sensors, and connected vehicles provide new opportunities for interactive, predictive, and adaptive communication. The study adopts an empirico-inductive methodology based on observation, documentary analysis, and international comparison. The theoretical framework combines Shannon and Weaver’s mathematical theory of communication, Habermas’s theory of communicative action, Crozier and Friedberg’s sociology of regulation, and ITS approaches. The analysis highlights both media and non-media strategies, while demonstrating the concrete contributions of AI to traffic fluidity, accident reduction, and road governance. It concludes with the challenges and prospects of implementing intelligent road communication adapted to the Cameroonian context.