The 8th AITS Track at EPIA Conferences aims to promote a debate on current developments and advancements of AI techniques in a rather practical perspective. It will gather both the AI community and transportation practitioners to discuss how cutting-edge AI technologies can be effectively applied to improve the performance of transportation systems and mobility in general on a sustainable basis, according to three important dimensions, namely economic, environmental, and social. This forum also aims to generate new ideas towards building innovative applications of AI technologies into smarter, greener and safer transportation systems, stimulating contributions that emphasise on how theory and practice are effectively coupled to solve real-life problems in contemporary transportation, naturally including all sorts of mobility systems. Indeed, today’s transportation systems are being devised on a more intelligent basis, and the concept of Intelligent Transportation Systems (ITS) has become already a reality among us. More recently, ITS have evolved into the basis giving support to the development of the so-called Smart Mobility solutions, within the framework of Smart Cities, in which social issues increase the complexity of transportation systems and bring about new performance measures such as equity, security, while sustainability is strongly emphasised. This thematic track on AI in Transportation Systems is also organised and promoted by the technical activity subcommittee on Artificial Transportation Systems and Simulation, a TAC of the IEEE ITS Society.

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.

PAPER SUBMISSION

Submissions must follow the guidelines specified on the EPIA 2020 Conference Website (http://www.appia.pt/epia2021/).

All accepted papers will be published by Springer in a volume of Springer’s Lecture Notes in Artificial Intelligence (LNAI) corresponding to the proceedings of the 20th EPIA Conference on Artificial Intelligence, EPIA 2021.

Submissions must be original and not published elsewhere. Papers should not exceed twelve (12) pages for full papers or six (6) pages for short papers and must adhere to the formatting instructions of the conference. Each submission will be peer reviewed by at least three members of the Program Committee. The reviewing process is double blind, so authors should remove names and affiliations from the submitted papers and must take reasonable care to assure anonymity during the review process. References to own work may be included in the paper, as long as referred to in the third person. Acceptance will be based on the paper’s significance, technical quality, clarity, relevance and originality. All accepted papers must be presented orally at the conference by one of the authors and at least one author of each accepted paper must register for the conference.

All papers should be submitted in PDF format through the EPIA 2020 EasyChair submission page: https://easychair.org/conferences/?conf=epia2021

ORGANIZING COMMITTEE

Rosaldo Rossetti, University of Porto, Portugal (rossetti@fe.up.pt)
Alberto Fernandez, University Rey Juan Carlos, Spain (alberto.fernandez@urjc.es)