DECART: Planning for Decarbonising Transport Sector with Predictive Analytics - An Irish Case Study

This article explores assessing the impact of the decarbonisation of the transport sector using an evidence-based approach incorporating data analysis and advanced machine learning (ML) modelling. We investigate the radical behavioural and societal changes needed for the decarbonisation of the transport sector in Ireland. We perform a study through our system DECArbonisation in Road Transport (DECART), a suite of statistical and time series ML models for facilitating policy making, monitoring and advising governments, companies and organisations in the transport sector. Based on data analysis and through scenario-modelling approaches, we present alternatives to policy and decision makers to achieve goals in mitigation of carbon emissions in road transport. The models depict how changes in mobility patterns in road transport affect CO2 emissions. Through insights obtained from the models, we infer that renewable energy in Ireland has the potential for meeting the growing electricity needs of electric vehicles. Experimentation is conducted on real-world datasets such as traffic, motor registrations, and data from renewable sources such as wind farms, for building efficient ML models. The models are validated in terms of accuracy, based on their potential to capture hidden insights from real-world events and domain knowledge.