2,240 research outputs found
Exploring Driving Behavior for Autonomous Vehicles Based on Gramian Angular Field Vision Transformer
Effective classification of autonomous vehicle (AV) driving behavior emerges
as a critical area for diagnosing AV operation faults, enhancing autonomous
driving algorithms, and reducing accident rates. This paper presents the
Gramian Angular Field Vision Transformer (GAF-ViT) model, designed to analyze
AV driving behavior. The proposed GAF-ViT model consists of three key
components: GAF Transformer Module, Channel Attention Module, and Multi-Channel
ViT Module. These modules collectively convert representative sequences of
multivariate behavior into multi-channel images and employ image recognition
techniques for behavior classification. A channel attention mechanism is
applied to multi-channel images to discern the impact of various driving
behavior features. Experimental evaluation on the Waymo Open Dataset of
trajectories demonstrates that the proposed model achieves state-of-the-art
performance. Furthermore, an ablation study effectively substantiates the
efficacy of individual modules within the model
Distributed workload control for federated service discovery
The diffusion of the internet paradigm in each aspect of human life continuously fosters the widespread of new technologies and related services. In the Future Internet scenario, where 5G telecommunication facilities will interact with the internet of things world, analyzing in real time big amounts of data to feed a potential infinite set of services belonging to different administrative domains, the role of a federated service discovery will become crucial. In this paper the authors propose a distributed workload control algorithm to handle efficiently the service discovery requests, with the aim of minimizing the overall latencies experienced by the requesting user agents. The authors propose an algorithm based on the Wardrop equilibrium, which is a gametheoretical concept, applied to the federated service discovery domain. The proposed solution has been implemented and its performance has been assessed adopting different network topologies and metrics. An open source simulation environment has been created allowing other researchers to test the proposed solution
Mathematics and the Internet: A Source of Enormous Confusion and Great Potential
Graph theory models the Internet mathematically, and a number of plausible mathematically intersecting network models for the Internet have been developed and studied. Simultaneously, Internet researchers have developed methodology to use real data to validate, or invalidate, proposed Internet models. The authors look at these parallel developments, particularly as they apply to scale-free network models of the preferential attachment type
On resilient control of dynamical flow networks
Resilience has become a key aspect in the design of contemporary
infrastructure networks. This comes as a result of ever-increasing loads,
limited physical capacity, and fast-growing levels of interconnectedness and
complexity due to the recent technological advancements. The problem has
motivated a considerable amount of research within the last few years,
particularly focused on the dynamical aspects of network flows, complementing
more classical static network flow optimization approaches. In this tutorial
paper, a class of single-commodity first-order models of dynamical flow
networks is considered. A few results recently appeared in the literature and
dealing with stability and robustness of dynamical flow networks are gathered
and originally presented in a unified framework. In particular, (differential)
stability properties of monotone dynamical flow networks are treated in some
detail, and the notion of margin of resilience is introduced as a quantitative
measure of their robustness. While emphasizing methodological aspects --
including structural properties, such as monotonicity, that enable tractability
and scalability -- over the specific applications, connections to
well-established road traffic flow models are made.Comment: accepted for publication in Annual Reviews in Control, 201
On imitation dynamics in potential population games
Imitation dynamics for population games are studied and their asymptotic
properties analyzed. In the considered class of imitation dynamics - that
encompass the replicator equation as well as other models previously considered
in evolutionary biology - players have no global information about the game
structure, and all they know is their own current utility and the one of fellow
players contacted through pairwise interactions. For potential population
games, global asymptotic stability of the set of Nash equilibria of the
sub-game restricted to the support of the initial population configuration is
proved. These results strengthen (from local to global asymptotic stability)
existing ones and generalize them to a broader class of dynamics. The developed
techniques highlight a certain structure of the problem and suggest possible
generalizations from the fully mixed population case to imitation dynamics
whereby agents interact on complex communication networks.Comment: 7 pages, 3 figures. Accepted at CDC 201
TEchMA2020: 3rd International Conference on Technologies for the Wellbeing and Sustainable Manufacturing Solutions: book of abstracts
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