Topics of interest

The AITS Thematic Track welcomes and encourages contributions reporting on original research, work under development and experiments of different AI techniques, such as, supervised/unsupervised learning approaches (e.g. neural networks for classification problems), biologically inspired approaches, evolutionary algorithms, knowledge-based and expert systems, case-based reasoning, fuzzy logics, intelligent agents and multi-agent systems, support vector regression, data mining and other pattern-recognition and optimization techniques, as well as concepts such as ambient intelligence and ubiquitous computing, service-oriented architectures, and ontology, to address specific issues in contemporary transportation, which would include (but are not limited to):

• different modes of transport and their interactions (air, road, rail and water transports);
• intelligent and real-time traffic management and control;
• design, operation, timetabling and real-time control of logistics systems and freight transport;
• transport policy, planning, design and management;
• environmental issues, road pricing, security and safety;
• transport systems operation;
• application and management of new technologies in transport;
• travel demand analysis, prediction and transport marketing;
• advanced traveller information systems and services;
• ubiquitous transport technologies and ambient intelligence;
• pedestrian and crowd simulation and analysis;
• urban planning toward sustainable mobility;
• service oriented architectures for vehicle-to-vehicle and vehicle-to-infrastructure communications;
• assessment and evaluation of intelligent transportation technologies; 
• human factors in intelligent vehicles;
• autonomous driving;
• artificial transportation systems and simulation;
• serious games and gamification in transportation;
• behaviour modelling and social simulation of transportation systems;
• electric mobility and its relationship with smart grids and the electricity market;
• computer vision in autonomous driving;
• surveillance and monitoring systems for transportation and pedestrians;
• data-driven preventive maintenance policies;
• anomalous trajectory mining and fraud detection;
• smart architectures for vehicle-to-vehicle/vehicle-to-infrastructure communications;
• automatic assessment and/or evaluation on the transport reliability (planning, control and other related policies);
• intelligent transportation infrastructure management and maintenance;
• legal and ethical issues in intelligent transportation systems and smart mobility.