Multi-Agent Systems for Traffic and Transportation Engineering

Ana Bazzan received her PhD in 1997 from the University of Karlsruhe (Germany), and an MSc. in Computer Science from the Institute of Informatics at the University of Rio Grande do Sul (UFRGS) in Porto Alegre (Brazil). From 1997 to 1998, she had a postdoc research associate position in the Multi-Agent Systems Laboratory at the University of Massachusetts in Amherst, under the supervision of Prof. Victor Lesser. In 1999 she joined the Institute for Informatics at UFRGS as a Professor and got tenure 3 years later. During 2006 and 2007 she had a fellowship from the Alexander von Humboldt Foundation at the University of W�rzburg (Germany). She is affiliated with the research groups on Artificial Intelligence and Multi-Agent Systems at UFRGS. Her research interests include: Game-Theoretic Paradigms for Coordination of Agents, Multiagent Learning, Coordination and Cooperation in MAS, Agent-Based Simulation, RoboCup Rescue, and Traffic Simulation and Control. Other professional activities: associate editor of the journal Advances in Complex Systems, chair of program committee for the 17th Braz. Symp. on Artificial Intelligence (2004), and co-organizer of workshop series on Agents in Traffic and Transportation. Franziska Kl�gl is Universitetslektor at the �rebro University since September 2008. She is also responsible for Scenario-based Modelling at the Research Centre for Modelling and Simulation at the Campus Alfred Nobel in Karlskoga. She received her PhD in Computer Science from the University of W�rzburg (2000). From 2000 to 2008 she worked as an Assistant Professor at the University of W�rzburg and headed there the Multi-Agent Simulation group. She is co-organizer of the workshop series on �Agents in Traffic and Transportation� and was involved in the organization of several scientific events like PC Chair of the European Workshop of Multi-Agent Systems (2008). Her research interests are in the area of methodologies, applications and tools for multi-agent simulation ranging from learning and adaptive agents to visual programming for modelling multi-agent models. The main application areas of her research are all forms of traffic simulation.

Our increasing societal demand for mobility now challenges researchers to devise more efficient traffic and transportation systems. Multi-Agent Systems for Traffic and Transportation Engineering provides a unique compendium of research covering topics such as transportation system designs, control devices, and techniques to optimize existing networks. Presenting a collection of approaches to issues in traffic and transportation, this authoritative reference offers a compilation of chapters with innovative methods and systems written by leading international researchers.

Activity-travel patterns Autonomous intersection control Complex traffic simulation Collaborative driving Evacuation dynamics Microscopic traffic modeling Pedestrian dynamics Public transport systems Route information sharing Traffic congestion management Traffic flow