12,276 research outputs found
Federated Robust Embedded Systems: Concepts and Challenges
The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements.
While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development.
During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs
An agent-based approach to assess drivers’ interaction with pre-trip information systems.
This article reports on the practical use of a multi-agent microsimulation framework to address the issue of assessing drivers’
responses to pretrip information systems. The population of drivers is represented as a community of autonomous agents,
and travel demand results from the decision-making deliberation performed by each individual of the population as regards
route and departure time. A simple simulation scenario was devised, where pretrip information was made available to users
on an individual basis so that its effects at the aggregate level could be observed. The simulation results show that the
overall performance of the system is very likely affected by exogenous information, and these results are ascribed to demand
formation and network topology. The expressiveness offered by cognitive approaches based on predicate logics, such as the
one used in this research, appears to be a promising approximation to fostering more complex behavior modelling, allowing
us to represent many of the mental aspects involved in the deliberation process
Wireless vehicular communications for automatic incident detection and recovery
Incident detection is the process by which an incident is brought to the attention of traffic operators in order to design and activate a response plan. To minimize the detection time is crucial to mitigate the incident severity for victims as well to reduce the risk of secondary crashes. Automated incident information dissemination and traffic conditions is useful to alert in-route drivers to decide alternative routes on unexpected traffic congestion and may be also used for the incident recovery process, namely to optimize the response plan including the “nearest” rescue teams, thereby shortening their response times.
Wireless vehicular communications, notably the emergent IEEE 802.11p protocol, is the enabling technology providing timely, dependable and secure properties that are essential for the devised target application. However, there are still some open issues with vehicular communications that require further research efforts.
This paper presents an overview of the state of the art in wireless vehicular communications and describes the field operational tests proposed within the scope of the upcoming FP7 project ICSI - Intelligent Cooperative Sensing for Improved traffic efficiency
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Challenges in Complex Systems Science
FuturICT foundations are social science, complex systems science, and ICT.
The main concerns and challenges in the science of complex systems in the
context of FuturICT are laid out in this paper with special emphasis on the
Complex Systems route to Social Sciences. This include complex systems having:
many heterogeneous interacting parts; multiple scales; complicated transition
laws; unexpected or unpredicted emergence; sensitive dependence on initial
conditions; path-dependent dynamics; networked hierarchical connectivities;
interaction of autonomous agents; self-organisation; non-equilibrium dynamics;
combinatorial explosion; adaptivity to changing environments; co-evolving
subsystems; ill-defined boundaries; and multilevel dynamics. In this context,
science is seen as the process of abstracting the dynamics of systems from
data. This presents many challenges including: data gathering by large-scale
experiment, participatory sensing and social computation, managing huge
distributed dynamic and heterogeneous databases; moving from data to dynamical
models, going beyond correlations to cause-effect relationships, understanding
the relationship between simple and comprehensive models with appropriate
choices of variables, ensemble modeling and data assimilation, modeling systems
of systems of systems with many levels between micro and macro; and formulating
new approaches to prediction, forecasting, and risk, especially in systems that
can reflect on and change their behaviour in response to predictions, and
systems whose apparently predictable behaviour is disrupted by apparently
unpredictable rare or extreme events. These challenges are part of the FuturICT
agenda
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