AITS – Artificial Intelligence in Transportation Systems

The Thematic Track on Artificial Intelligence in Transportation Systems (AITS) within EPIA Conferences aims to promote an interdisciplinary debate on current developments and advances of AI techniques in a rather practical perspective, focusing on transportation and mobility systems. This Thematic Track follows up the first edition of the AIASTS Thematic Track, held at EPIA’2007, the second edition of the AITUM Thematic Track, held at EPIA’2009, and the third edition of the AITS Thematic Track, held at EPIA’2011. This event will act as a unique platform gathering the AI community, transportation engineers and practitioners, as well as social scientists to discuss how cutting-edge AI technologies can be effectively developed and applied to improve transportation performance towards sustainable mobility settings. This forum is thus an opportunity for the technical and scientific community to present progresses made so far, and as a means to generate new ideas towards building innovative applications of AI technologies into more efficient transportation systems.

As from this 4th Edition of the AITS Thematic Track, the event will be promoted by the Artificial Transportation Systems and Simulation (ATSS) Technical Activity Sub-committee of IEEE Intelligent Transportations Systems Society. The EPIA Conference Series has been ranked by the Computing Research & Education initiative as a “CORE B” Conference, whose proceedings are published by Springer in their LNAI Series and traditionally indexed by Thomson Reuters’ ISI Web of Knowledge.

Scope of AITS Thematic Track

As in many multidisciplinary knowledge fields, much advance in AI is fostered through challenges imposed by issues that scientists address when applying theory to solve practical problems. Thus, the AITS Thematic Track serves as a working platform to discuss current developments and advances of AI techniques in a rather practical perspective. It will stimulate a debate emphasising on how theory and practice are effectively coupled to tackle problems in the specific domain of transportation.

Besides its economical, social, and environmental importance, transportation is a very challenging domain, especially due to its inherent complexity. It is formed up by geographically and functionally distributed heterogeneous elements, both artificial and human, with different decision-making abilities, collective or individual goals, making its dynamics rather uncertain. Also, mobility plays a major role towards citizen’s quality of life. With resources even scarcer and the imposition of uncountable constraints to mobility, contemporary transportation has experienced a great revolution and has become highly evolving. This means that a rational use of transportation infrastructures and the way they interact with the environment must be managed on a sustainable basis.

Within the last two decades, this scenario has witnessed the advent of the concept of Intelligent Transportation Systems (ITS). Rather than increasing service capacity, one underlying approach of ITS-based solutions is to ensure productivity and mobility by making better use of existing transportation infrastructure, featuring them with smarter, greener, safer, and more efficient technologies. Indeed, much advance verified in this field is due to AI that is a key ingredient to ITS. The relationship between these two areas is certainly mutually beneficial, suggesting a wide range of cross-fertilisation opportunities and potential synergisms between the AI community that devises theory and transport practitioners that use it. Therefore, contemporary transportation systems are a natural ground to conceive, develop, test and apply AI techniques.

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 neural networks, 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 optimisation 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 transport);
- intelligent and real-time traffic management and control;
- design, operations, time-tabling and management of logistic systems and freight transport;
- transport policy, planning, design and management;
- environmental issues, road pricing, security and safety;
- transport system operations;
- application and management of new technologies in transport;
- travel demand analysis, prediction and transport marketing;
- traveller information systems and services;
- ubiquitous transport technologies and ambient intelligence;
- pedestrian and crowd modelling, simulation and analysis;
- urban planning towards 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;
- surveillance and monitoring systems for transportation and pedestrians.

Paper Submission and Publication

Contributions must be original and not published elsewhere. Papers should strictly adhere to formatting instructions of the conference, and can be of two types: regular (full-length) papers should not exceed twelve (12) pages in length, whereas short papers should not exceed six (6) pages. Each submission will be reviewed by at least three members of the International Programme Committee of the AITS Thematic Track. This process will follow a blind-review approach, so we kindly ask authors to take reasonable care not to indirectly disclose their identity, removing their names from the manuscript and any reference that might explicitly identify them.
The best papers will be included in a volume of the Lecture Notes in Artificial Intelligence (LNAI) Series, to be published by Springer (proceedings indexed by the Thomson ISI Web of Knowledge). All other accepted papers will be published in the local proceedings. Publication of accepted papers is subject to at least one co-author registering for the conference and presenting the paper during the AITS session at the Conference.

Organizing Committee

Rosaldo Rossetti, LIACC/DEI – University of Porto, Portugal (rossetti@fe.up.pt)
Matteo Vasirani, École Polytechnique Fédérale de Lausanne, Switzerland (matteo.vasirani@epfl.ch)
Cristina Olaverri Monreal, Technische Universität München, Germany (olaverri@lfe.mw.tum.de)

Program Committee

- Adriana Giret, U.P. Valencia, Spain
- Agachai Sumalee, The Hong Kong Polytechnic University, Hong Kong
- Alberto Fernandez, Rey Juan Carlos University, Spain
- Ana Almeida, Polytechnic Institute of Porto, Portugal
- Ana Bazzan, UFRGS, Brazil
- António Castro, University of Porto, Portugal
- Carlos Lisboa Bento, University of Coimbra, Portugal
- Constantinos Antoniou, National Technical University of Athens, Greece
- Danny Weyns, Katholieke Universiteit Leuven, Belgium
- Eduardo Camponogara, UFSC, Brazil
- Elisabete Arsénio, LNEC, Portugal
- Fausto Vieira, Instituto de Telecomunicações/FCUP, Portugal
- Federico Barber, U.P. Valencia, Spain
- Fei-Yue Wang, Chinese Academy of Sciences,  China
- Francisco Pereira, SMART/MIT, Singapore
- Geert Wets, University of Hasselt, Belgium
- Giuseppe Vizzari, University of Milan-Bicocca, Italy
- Harry Timmermans, Eindhoven University of Technology, The Netherlands
- Hilmi Berk Celikoglu, Technical University of Istanbul, Turkey
- Hussein Dia, AECOM, Australia
- Javier Sanchez Medina, Universidad de Las Palmas de Gran Canaria, Spain
- Jeffrey Miller, University of Anchorage, USA
- Jorge Lopes, BRISA S.A., Portugal
- José Manuel Menendez, Universidad Politécnica de Madrid, Spain
- José Telhada, University of Minho, Portugal
- Jürgen Sauer, University of Oldenburg, Germany
- Luís Nunes, ISCTE, Portugal
- Luís Paulo Reis, University of Minho, Portugal
- Maite López Sánchez, University of Barcelona, Spain
- Michael Rovatsos, University of Edinburgh, UK
- Miguel A. Salido, U.P. Valencia, Spain
- Paulo Leitão, Instituto Politécnico de Bragança, Portugal
- Ronghui Liu, ITS/University of Leeds, UK
- Sascha Ossowski, Rey Juan Carlos University, Spain
- Shuming Tang, Chinese Academy of Sciences, China
- Thomas Strang, DLR, Germany

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