Important dates

Paper submission:
15.Jul.2007
Author notification:
10.Aug.2007
Camera-ready copies:
10.Sep.2007
Conference dates:
3-7.Dec.2007
 
AIASTS Print E-mail

Workshop on AI Applications for Sustainable Transportation Systems

The AIASTS’07 workshop aims to promote an interdisciplinary debate on current developments and advances of AI techniques in a rather practical perspective, focusing on transportation and mobility. It will act as a unique platform gathering both the AI community, transportation and other social sciences’ practitioners to discuss how cutting-edge AI technologies can be effectively applied to improve transportation performance towards sustainable systems. This forum is an opportunity to present progresses made so far, and a means 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.

Topics of Interest

The workshop 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, to address specific issues in contemporary transportation, which would include (but are not limited to): 

- different modes of transport (road, rail, air, maritime, cycling, ...) and their interactions;
- intelligent and real-time traffic management and control;
- design, operation, and management of logistics systems and freight transport;
- transportation policy, planning, design and management;
- environmental impacts, road pricing issues, security and safety;
- transportation systems operation;
- artificial transport systems and simulation;
- application and management of new technologies in transportation;
- travel demand analysis, prediction and transportation marketing;
- traveller information systems and services;
- assessment and evaluation of intelligent transportation technologies.

Scope

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 AIASTS workshop 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 infrastructure and the way it interacts 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 synergism 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.

Organising Committee

Rosaldo Rossetti, University of Porto, Portugal ( This email address is being protected from spam bots, you need Javascript enabled to view it )

José Telhada, University of Minho, Portugal ( This email address is being protected from spam bots, you need Javascript enabled to view it )

Ronghui Liu, University of Leeds, UK ( This email address is being protected from spam bots, you need Javascript enabled to view it )

Elisabete Arsénio, National Laboratory of Civil Engineering, Portugal ( This email address is being protected from spam bots, you need Javascript enabled to view it )

Program Committee

Agachai Sumalee, Hong Kong Polytechnic University, Hong Kong
Álvaro Seco, University of Coimbra, Portugal
Ana Bazzan, UFRGS, Brazil
Elisabete Arsénio, LNEC, Portugal
Eugénio Oliveira, University of Porto, Portugal
Fei-Yue Wang, University of Arizona, USA
Franziska Klügl, University of Würzburg, Germany
Giovanna Serugendo, Birkbeck College, University of London, UK
Giuseppe Vizzari, University of Milan-Bicocca, Italy
Harry Timmermans, Eindhoven University of Technology, The Netherlands
Hussein Dia, University of Quensland, Australia
João Pavão Martins, Technical University of Lisbon, Portugal
José Telhada, University of Minho, Portugal
Luís Nunes, ISCTE, Portugal
Luís Paulo Reis, University of Porto, Portugal
Maria Sameiro Carvalho, University of Minho, Portugal
Ronghui Liu, University of Leeds, UK
Rosaldo Rossetti, University of Porto, Portugal
Sascha Ossowski, Universidad Rey Juan Carlos, Spain
Shuming Tang, Chinese Academy of Sciences, China

(to be completed)

 
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