Reducing port city congestion through data analysis, simulation, and artificial intelligence to improve the well-being of citizens

Abstract

Abstract Many port cities suffer from congestion and greenhouse gas (GHG) and other emissions. City governments and port authorities seek ways to reduce the negative impacts on quality of life, health, climate, and the local economy. Congestion across the United States, United Kingdom and Germany alone cost close to $461 billion in 2017 or $975 per capita. Artificial intelligence and machine learning can help to understand and predict traffic volumes and enable simulation of alternative solutions to smooth flows and reduce congestion. This article reflects on optimising the utilisation of road transport infrastructure to reduce GHG emissions in the Valencia port city environment. This real-life study case shows that data, data sharing and AI systems can contribute to reducing congestion and with that GHG emissions and other negative impacts for port cities.