The concept of Smart Cities aims to create more sustainable, efficient, and greener urban environments through the use of technology, specifically the Internet of Things (IoT). This aligns with the United Nations’ 2030 Agenda for Sustainable Development, specifically Goal 11 which focuses on making cities inclusive, safe, resilient, and sustainable. Smart cities rely heavily on information and communication technologies (ICT) and transportation systems are a key area in which they are evolving quickly and steadily through the use of the IoT. This has led to the development of new concepts such as cooperative ITS (C-ITS) and autonomous vehicles (AV). Smart cities and mobility can be thought of as complex, dynamic, distributed systems in which entities have intelligence and autonomy, and exhibit cooperative, collaborative, and competitive interactions. Therefore, the domains of smart cities and smart mobility provide a natural laboratory for testing AI theories, methods, tools, and applications in a cross-fertilization approach that benefits both the application domains and AI.
LIACC has vast experience and a long history in applying AI in traffic and transportation, which allowed the Laboratory to easily pursue research and innovation in smart cities and mobility as well. More specifically, multiagent systems are the main methodology to model, design, and test intelligent solutions in smart cities and mobility.
Different applications to which LIACC has contributed include intelligent traffic control, public transit and multimodal transportation, demand modelling, road safety, autonomous driving and platoon coordination, urban vehicle accessibility regulations, road pricing and incentives design, electric mobility, sustainable households and intelligent waste collection. Additionally, LIACC has contributed to the implementation of methodologies and tools, including middleware for transportation simulators interoperability, artificial societies synthetisation, and disruption management.