46,743 research outputs found
A Learning-based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles
Vehicle to Vehicle (V2V) communication has a great potential to improve
reaction accuracy of different driver assistance systems in critical driving
situations. Cooperative Adaptive Cruise Control (CACC), which is an automated
application, provides drivers with extra benefits such as traffic throughput
maximization and collision avoidance. CACC systems must be designed in a way
that are sufficiently robust against all special maneuvers such as cutting-into
the CACC platoons by interfering vehicles or hard braking by leading cars. To
address this problem, a Neural- Network (NN)-based cut-in detection and
trajectory prediction scheme is proposed in the first part of this paper. Next,
a probabilistic framework is developed in which the cut-in probability is
calculated based on the output of the mentioned cut-in prediction block.
Finally, a specific Stochastic Model Predictive Controller (SMPC) is designed
which incorporates this cut-in probability to enhance its reaction against the
detected dangerous cut-in maneuver. The overall system is implemented and its
performance is evaluated using realistic driving scenarios from Safety Pilot
Model Deployment (SPMD).Comment: 10 pages, Submitted as a journal paper at T-I
Exact ZF Analysis and Computer-Algebra-Aided Evaluation in Rank-1 LoS Rician Fading
We study zero-forcing detection (ZF) for multiple-input/multiple-output
(MIMO) spatial multiplexing under transmit-correlated Rician fading for an N_R
X N_T channel matrix with rank-1 line-of-sight (LoS) component. By using matrix
transformations and multivariate statistics, our exact analysis yields the
signal-to-noise ratio moment generating function (m.g.f.) as an infinite series
of gamma distribution m.g.f.'s and analogous series for ZF performance
measures, e.g., outage probability and ergodic capacity. However, their
numerical convergence is inherently problematic with increasing Rician
K-factor, N_R , and N_T. We circumvent this limitation as follows. First, we
derive differential equations satisfied by the performance measures with a
novel automated approach employing a computer-algebra tool which implements
Groebner basis computation and creative telescoping. These differential
equations are then solved with the holonomic gradient method (HGM) from initial
conditions computed with the infinite series. We demonstrate that HGM yields
more reliable performance evaluation than by infinite series alone and more
expeditious than by simulation, for realistic values of K , and even for N_R
and N_T relevant to large MIMO systems. We envision extending the proposed
approaches for exact analysis and reliable evaluation to more general Rician
fading and other transceiver methods.Comment: Accepted for publication by the IEEE Transactions on Wireless
Communications, on April 7th, 2016; this is the final revision before
publicatio
Model-Based Security Testing
Security testing aims at validating software system requirements related to
security properties like confidentiality, integrity, authentication,
authorization, availability, and non-repudiation. Although security testing
techniques are available for many years, there has been little approaches that
allow for specification of test cases at a higher level of abstraction, for
enabling guidance on test identification and specification as well as for
automated test generation.
Model-based security testing (MBST) is a relatively new field and especially
dedicated to the systematic and efficient specification and documentation of
security test objectives, security test cases and test suites, as well as to
their automated or semi-automated generation. In particular, the combination of
security modelling and test generation approaches is still a challenge in
research and of high interest for industrial applications. MBST includes e.g.
security functional testing, model-based fuzzing, risk- and threat-oriented
testing, and the usage of security test patterns. This paper provides a survey
on MBST techniques and the related models as well as samples of new methods and
tools that are under development in the European ITEA2-project DIAMONDS.Comment: In Proceedings MBT 2012, arXiv:1202.582
Now or never: negotiating efficiently with unknown counterparts
We define a new protocol rule, Now or Never (NoN), for bilateral negotiation processes which allows self-motivated competitive agents to efficiently carry out multi-variable negotiations with remote untrusted parties, where privacy is a major concern and agents know nothing about their opponent. By building on the geometric concepts of convexity and convex hull, NoN ensures a continuous progress of the negotiation, thus neutralising malicious or inefficient opponents. In par- ticular, NoN allows an agent to derive in a finite number of steps, and independently of the behaviour of the opponent, that there is no hope to find an agreement. To be able to make such an inference, the interested agent may rely on herself only, still keeping the highest freedom in the choice of her strategy.
We also propose an actual NoN-compliant strategy for an automated agent and evaluate the computational feasibility of the overall approach on instances of practical size
- …