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This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
The problem of energy-aware traffic management in urban environment is addressed. Such traffic management aims at reducing vehicle stops, accelerations, energy consumption, and ultimately congestion. The eco-management in urban traffic networks may be divided in two broad categories: vehicle-side control and infrastructure-side control. Both control domains can feature isolated or coordinated characteristics, depending on the type of information used in the optimization.The vehicle-side traffic management influences each single vehicle according to its own characteristics and position. Isolated vehicle control aims primarily at optimizing the powertrain and/or the driving profile of the vehicles, possibly using information about the road characteristics, but without communicating with the other agents of the traffic network. Coordinated vehicle control makes use of communication among vehicles and with the infrastructure in order to achieve larger benefits in terms of energy consumption and traffic fluidity.The infrastructure-side management, on the other hand, influences traffic lights and road side panels in order to improve the performance of the traffic as a whole. Isolated infrastructure control regulates essentially the traffic lights at a single signalized intersection, or the speed limits in a single stretch of road, without taking into account the interactions with the neighboring junctions and/or road sections. Coordinated infrastructure control overcomes this limitation by using information about traffic conditions in other road sections to alleviate congestion.The contributions of this work to the energy-aware traffic management may be summarized as follows.Firstly, a solution for the coordinated vehicle control has been proposed, in which communication with the infrastructure is exploited to reduce energy consumption. In particular, the traffic lights timings are assumed to be communicated to the vehicle and known, and the vehicle is suggested an optimal speed to drive through a sequence of signalized intersections without stopping, while following a minimum-energy trajectory. The proposed strategy, independently applied to each vehicle, has been tested in a microscopic traffic simulator in order to assess the impact on the traffic performance. The analysis has demonstrated that the energy consumption and the number of stops can be drastically reduced without affecting the travel time.Then, a solution for the isolated infrastructure control has been proposed. A macroscopic urban traffic model has been introduced, and the variable speed limits have been used as actuation to improve traffic performance. In particular, the analysis has been carried out at saturated traffic conditions, with given and fixed traffic lights scheduling. The optimization aims at reducing the energy consumption in trade-off with the average travel time of the vehicles in the considered road section. Experiments have demonstrated that there exists an optimal speed limit that improves traffic performance and reduces the length of the queue at the traffic light.Lastly, a solution for the coordinated infrastructure control has been proposed. Traffic lights coordination on arterials has been proved to be effective in terms of traffic delay reduction. Our analysis has demonstrated that an optimization problem can be cast to take into account also energetic aspects. Extensive experiments in a microscopic traffic simulator have showed that a correlation exists between traffic progression and traffic performance indexes, such as energy consumption, travel time, idling time, and number of stops. The proposed control strategy has showed that a significant reduction of energy consumption can be achieved, almost completely eliminating number of stops and idling time, without affecting the travel time.
The problems of urban traffic in the industrially developed countries have been at the top of the priority list for a long time. While making a critical contribution to the economic well being of those countries, transportation systems in general and highway traffic in particular, also have detrimental effects which are evident in excessive congestion, high rates of accidents and severe pollution problems. Scientists from different disciplines have played an important role in the development and refinement of the tools needed for the planning, analysis, and control of urban traffic networks. In the past several years, there were particularly rapid advances in two areas that affect urban traffic: 1. Modeling of traffic flows in urban networks and the prediction of the resulting equilibrium conditions; 2. Technology for communication with the driver and the ability to guide him, by providing him with useful, relevant and updated information, to his desired destination.
This book describes how control of distributed systems can be advanced by an integration of control, communication, and computation. The global control objectives are met by judicious combinations of local and nonlocal observations taking advantage of various forms of communication exchanges between distributed controllers. Control architectures are considered according to increasing degrees of cooperation of local controllers: fully distributed or decentralized control, control with communication between controllers, coordination control, and multilevel control. The book covers also topics bridging computer science, communication, and control, like communication for control of networks, average consensus for distributed systems, and modeling and verification of discrete and of hybrid systems. Examples and case studies are introduced in the first part of the text and developed throughout the book. They include: control of underwater vehicles, automated-guided vehicles on a container terminal, control of a printer as a complex machine, and control of an electric power system. The book is composed of short essays each within eight pages, including suggestions and references for further research and reading. By reading the essays collected in the book Coordination Control of Distributed Systems, graduate students and post-docs will be introduced to the research frontiers in control of decentralized and of distributed systems. Control theorists and practitioners with backgrounds in electrical, mechanical, civil and aerospace engineering will find in the book information and inspiration to transfer to their fields of interest the state-of-art in coordination control.