Artificial Intelligence in Transportation Systems
The Thematic Track on Artificial Intelligence in Transportation Systems (AITS@EPIA2015) 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 Workshop, held at EPIA2007, the second edition of the AITUM Thematic Track, held at EPIA2009, the third edition of the AITS Thematic Track, held at EPIA2011, and AITS Track held at EPIA2013. It will serve as a unique platform gathering the AI community, transportation and other social sciences’ practitioners to discuss how cutting-edge AI technologies can be effectively developed and applied to improve transportation performance towards sustainable mobility systems. This forum is 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 smarter, greener and safer transportation systems, stimulating contributions that emphasize on how theory and practice are effectively coupled to solve real-life problems in contemporary transportation. The EPIA conference has been ranked by the Computing Research & Education initiative as a “CORE B” Conference, whose proceedings are published by Springer in their LNAI Series.
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
- intelligent and real-time traffic management and control;
- design, operation, time-tabling and management 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;
- 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;
- surveillance and monitoring systems for transportation and pedestrians.
Scope of the 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.
Paper submission
Submissions must be original and not published elsewhere. Papers should not exceed twelve (12) pages in length 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.
Paper Publication
All accepted papers will be published by Springer in a volume of the LNAI-Lecture Notes in Artificial Intelligence series (indexed by the Thomson ISI Web of Knowledge). The number of pages of the accepted contributions has the following limits:
- Full Regular Papers: Contributions accepted as full papers should contain from 10 to 12 pages in its final version, according to the LNAI series formatting instructions. Extraordinarily, other two additional pages could be considered with a supplementary fee.
- Short Papers: Contributions accepted as short papers should contain from 4 to 6 pages in its final version, according to the LNAI series formatting instructions.
All accepted papers must be presented orally the conference by one of the authors and at least one author of each accepted paper must register for the conference.
Important dates
Deadline for paper submission: March 23, 2015
Notification of paper acceptance: 27, April, 2015
Camera-ready papers due: 1, June, 2015
Conference dates: September 8-11, 2015
Track Chairs
Rui Gomes
University of Coimbra, Coimbra, Portugal
Email: ruig (at) dei.uc.pt
Rosaldo Rossetti
University of Porto, Porto, Portugal
Email: rossetti (at) fe.up.pt
Program Committee
Achille Fonzone, Edinburgh Napier University, UK
Agachai Sumalee, Hong Kong Polytechnic University, Hong Kong
Alberto Fernandez, Universidad Rey Juan Carlos, Spain
Ana Almeida, Instituto Polit\’ecnico do Porto, Portugal
Ana L. C. Bazzan, Universidade Federal do Rio Grande do Sul, Brazil
Constantinos Antoniou, National Technical University of Athens, Greece
Cristina Olaverri-Monreal, AIT Austrian Institute of Technology GmbH, Austria
Eduardo Camponogara, Universidade Federal de Santa Catarina, Brazil
Giovanna Di Marzo Serugendo, University of Geneva, Switzerland
Gonçcalo Correia, Delft University of Technology, The Netherlands
Harry Timmermans, Eindhoven University of Technology, The Netherlands
Hussein Dia, Swinburne University of Technology, Australia
José Telhada, Universidade do Minho, Portugal
Kai Nagel, Technische Universität Berlin, Germany
Luís Moreira Matias, NEC Europe Ltd, Germany
Luís Nunes, ISCTE Instituto Universit\’ario de Lisboa, Portugal
Oded Cats, Delft University of Technology, The Netherlands
Sascha Ossowski, Universidad Rey Juan Carlos, Spain
Shuming Tang, Institute of Automation, Chinese Academy of Sciences, China
Tânia Fontes, Faculdade de Engenharia da Universidade do Porto, Portugal