Data Technology Triad: A Model towards Integrated Autonomous Transportation (IAT) Networks

The Data Technology Triad, encompassing the Internet of Things, Blockchain technology, and Artificial Intelligence, has the potential to transform Integrated Autonomous Transportation Networks. In this study, the authors apply the Triadic Model and the Triple S holistic approach (which focuses on synthetic, systemic, and synergic perspectives) to create a model for optimizing freight systems. The authors use the Multi-Agent Transport Simulation (MATSim) platform to examine the performance of integrated (freight_i) and non-integrated (freight_n) freight systems under urban traffic conditions. The simulation consists of 80% commuter and 20% freight agents who travel in a terrestrial-only network. The results highlight the efficiency and adaptability of integrated systems. More significantly, they show that the synergy of Internet of Things data collection, Blockchain-enabled security, and AI-driven optimization can produce important gains in the number of kilometers traveled and reduced travel times. The findings also validate the triad’s potential to improve operational efficiency, security, and interoperability within urban transportation networks.