PROACTIVE FATIGUE PREDICTION AND HEALTH MONITORING SYSTEMS FOR ROAD FREIGHT TRANSPORT IN THE EUROPEAN UNION: TOWARD A PREVENTIVE SAFETY FRAMEWORK

Abstract

Poor health conditions and driver fatigue continue to be a major contributor to road traffic accidents in the transport and logistics industries across the European Union (EU). Despite great technological and regulatory advancements in driver systems and safety technologies, most approaches towards management of fatigue among professional drivers remain reactive, rather than proactive, with physiological and behavioral indicators being the basis of detecting fatigue. This paper proposes a preventive framework for the management of fatigue, where fatigue risk factors are identified by integrating wearable sensors, predictive analytics, and health monitoring systems. A detailed literature review illustrates gaps in the current systems of fatigue management, laying emphasis on the need for progressive, real-time health data, and prediction models based on machine learning. The proposed system presents a combination of driver scheduling information, environmental data, and physiological monitoring information to predict the probability of fatigue and offer adaptive interventions. This paper also discusses policy implications for EU transport regulations, driver privacy, and management of data, suggesting its implementation using a multi-stakeholder approach. This paper highlights the potential of proactive management of fatigue towards reduction of road accidents and enhancement of occupational and logistics well-being in EU. Findings indicate that proactive monitoring plays a key role in improving early risk detection, improving well-being of drivers, and reducing accident rates, thus promoting safer and sustainable logistics operations.