Autonomic Road Transport Support Systems

1. Front Matter

   Pages i-vi

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2. Autonomic Road Transport Support Systems: An Introduction

   • Thomas Leo McCluskey, Apostolos Kotsialos, Jörg P. Müller, Franziska Klügl, Omer F. Rana, René Schumann

   Pages 1-11

3. A Game Theory Model for Self-adapting Traffic Flows with Autonomous Navigation

   • László Z. Varga

   Pages 13-28

4. Self-management in Urban Traffic Control: An Automated Planning Perspective

   • Falilat Jimoh, Thomas Leo McCluskey

   Pages 29-46

5. An Experimental Review of Reinforcement Learning Algorithms for Adaptive Traffic Signal Control

   • Patrick Mannion, Jim Duggan, Enda Howley

   Pages 47-66

6. A Multiagent Approach to Modeling Autonomic Road Transport Support Systems

   • Maksims Fiosins, Bernhard Friedrich, Jana Görmer, Dirk Mattfeld, Jörg P. Müller, Hugues Tchouankem

   Pages 67-85

7. A Self-Optimization Traffic Model by Multilevel Formalism

   • Todor Stoilov, Krasimira Stoilova

   Pages 87-111

8. An Organic Computing Approach to Resilient Traffic Management

   • Matthias Sommer, Sven Tomforde, Jörg Hähner

   Pages 113-130

9. Autonomic Systems Design for ITS Applications: Modelling and Route Guidance

   • Apostolos Kotsialos, Adam Poole

   Pages 131-145

10. Simulation Testbed for Autonomic Demand-Responsive Mobility Systems

    • Michal Čertický, Michal Jakob, Radek Píbil

    Pages 147-164

11. Multi-Agent Traffic Simulation for Development and Validation of Autonomic Car-to-Car Systems

    • Martin Schaefer, Jiří Vokřínek, Daniele Pinotti, Fabio Tango

    Pages 165-180

12. Performance Maintenance of ARTS Systems

    • René Schumann

    Pages 181-195

13. Learning-Based Control Algorithm for Ramp Metering

    • Martin Gregurić, Edouard Ivanjko, Sadko Mandžuka

    Pages 197-213

14. An Autonomic Methodology for Embedding Self-tuning Competence in Online Traffic Control Systems

    • Anastasios Kouvelas, Diamantis Manolis, Elias Kosmatopoulos, Ioannis Papamichail, Markos Papageorgiou

    Pages 215-232

15. Electric Vehicles in Road Transport and Electric Power Networks

    • Charalampos Marmaras, Erotokritos Xydas, Liana M. Cipcigan, Omer Rana, Franziska Klügl

    Pages 233-252

16. Traffic Signal Control with Autonomic Features

    • Iisakki Kosonen, Xiaoliang Ma

    Pages 253-267

17. TIMIPLAN: A Tool for Transportation Tasks

    • Javier García, Álvaro Torralba, José E. Florez, Daniel Borrajo, Carlos Linares López, Ángel García-Olaya

    Pages 269-285

18. Applying the PAUSETA Protocol in Traffic Management Plans

    • Miguel Prades-Farrón, Luis A. García, Vicente R. Tomás

    Pages 287-302

19. Back Matter

    Pages 303-304

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The work on Autonomic Road Transport Support (ARTS) presented here aims at meeting the challenge of engineering autonomic behavior in Intelligent Transportation Systems (ITS) by fusing research from the disciplines of traffic engineering and autonomic computing. Ideas and techniques from leading edge artificial intelligence research have been adapted for ITS over the last 30 years. Examples include adaptive control embedded in real time traffic control systems, heuristic algorithms (e.g. in SAT-NAV systems), image processing and computer vision (e.g. in automated surveillance interpretation). Autonomic computing which is inspired from the biological example of the body’s autonomic nervous system is a more recent development. It allows for a more efficient management of heterogeneous distributed computing systems. In the area of computing, autonomic systems are endowed with a number of properties that are generally referred to as self-X properties, including self-configuration, self-healing, self-optimization, self-protection and more generally self-management. Some isolated examples of autonomic properties such as self-adaptation have found their way into ITS technology and have already proved beneficial.   This edited volume provides a comprehensive introduction to Autonomic Road Transport Support (ARTS) and describes the development of ARTS systems. It starts out with the visions, opportunities and challenges, then presents the foundations of ARTS and the platforms and methods used and it closes with experiences from real-world applications and prototypes of emerging applications. This makes it suitable for researchers and practitioners in the fields of autonomic computing, traffic and transport management and engineering, AI, and software engineering. Graduate students will benefit from state-of-the-art description, the study of novel methods and the case studies provided.

• Intelligent Transportation Systems Architecture
• artificial intelligence
• autonomic computing
• traffic control
• traffic simulation
• traffic surveillance

• University of Huddersfield, School of Computing and Engineering, Huddersfield, United Kingdom

  Thomas Leo McCluskey

• School of Engineering and Computing Scie, Durham University, Co Durham, United Kingdom

  Apostolos Kotsialos

• Department of Informatics, TU Clausthal, Clausthal-Zellerfeld, Germany

  Jörg P. Müller

• Örebro University, School of Science and Technology, Sweden

  Franziska Klügl

• School of Computer Science and Informati, Cardiff University, Cardiff, United Kingdom

  Omer Rana

• Institute of Information Systems, HES-SO Valais-Wallis, Sierre, Switzerland

  René Schumann

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