1,483 research outputs found
A Survey on Fault Tolerance Techniques for Wireless Vehicular Networks
Future intelligent transportation systems (ITS) hold the promise of supporting the operation of safety-critical applications, such as cooperative self-driving cars. For that purpose, the communications among vehicles and with the road-side infrastructure will need to fulfil the strict real-time guarantees and challenging dependability requirements. These safety requisites are particularly important in wireless vehicular networks, where road traffic presents several threats to human life. This paper presents a systematic survey on fault tolerance techniques in the area of vehicular communications. The work provides a literature review of publications in journals and conferences proceedings, available through a set of different search databases (IEEE Xplore, Web of Science, Scopus and ScienceDirect). A systematic method, based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) Statement was conducted in order to identify the relevant papers for this survey. After that, the selected articles were analysed and categorised according to the type of redundancy, corresponding to three main groups (temporal, spatial and information redundancy). Finally, a comparison of the core features among the different solutions is presented, together with a brief discussion regarding the main drawbacks of the existing solutions, as well as the necessary steps to provide an integrated fault-tolerant approach to the future vehicular communications systems
In-vehicle communication networks : a literature survey
The increasing use of electronic systems in automobiles instead of mechanical and hydraulic parts brings about advantages by decreasing their weight and cost and providing more safety and comfort. There are many electronic systems in modern automobiles like antilock braking system (ABS) and electronic brakeforce distribution (EBD), electronic stability program (ESP) and adaptive cruise control (ACC). Such systems assist the driver by providing better control, more comfort and safety. In addition, future x-by-wire applications aim to replace existing braking, steering and driving systems. The developments in automotive electronics reveal the need for dependable, efficient, high-speed and low cost in-vehicle communication. This report presents the summary of a literature survey on in-vehicle communication networks. Different in-vehicle system domains and their requirements are described and main invehicle communication networks that have been used in automobiles or are likely to be used in the near future are discussed and compared with key references
6G White Paper on Machine Learning in Wireless Communication Networks
The focus of this white paper is on machine learning (ML) in wireless
communications. 6G wireless communication networks will be the backbone of the
digital transformation of societies by providing ubiquitous, reliable, and
near-instant wireless connectivity for humans and machines. Recent advances in
ML research has led enable a wide range of novel technologies such as
self-driving vehicles and voice assistants. Such innovation is possible as a
result of the availability of advanced ML models, large datasets, and high
computational power. On the other hand, the ever-increasing demand for
connectivity will require a lot of innovation in 6G wireless networks, and ML
tools will play a major role in solving problems in the wireless domain. In
this paper, we provide an overview of the vision of how ML will impact the
wireless communication systems. We first give an overview of the ML methods
that have the highest potential to be used in wireless networks. Then, we
discuss the problems that can be solved by using ML in various layers of the
network such as the physical layer, medium access layer, and application layer.
Zero-touch optimization of wireless networks using ML is another interesting
aspect that is discussed in this paper. Finally, at the end of each section,
important research questions that the section aims to answer are presented
Non-Terrestrial Networks in the 6G Era: Challenges and Opportunities
Many organizations recognize non-terrestrial networks (NTNs) as a key
component to provide cost-effective and high-capacity connectivity in future
6th generation (6G) wireless networks. Despite this premise, there are still
many questions to be answered for proper network design, including those
associated to latency and coverage constraints. In this paper, after reviewing
research activities on NTNs, we present the characteristics and enabling
technologies of NTNs in the 6G landscape and shed light on the challenges in
the field that are still open for future research. As a case study, we evaluate
the performance of an NTN scenario in which satellites use millimeter wave
(mmWave) frequencies to provide access connectivity to on-the-ground mobile
terminals as a function of different networking configurations.Comment: 8 pages, 4 figures, 2 tables, submitted for publication to the IEE
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
Preliminary study for the measurement of Biosignals in Driving Simulators
openThis preliminary study focuses on the goal of developing and testing a setup and method for non-invasive monitoring of individuals using biosensors in a professional driving simulator (VI-grade Compact Simulator).
This involves the synchronization and integration of hardware and software components.
To detect the emotional and cognitive state of the driver, it is crucial to identify which signals provide reliable information about their condition.
The objective of this study is to observe individuals in a controlled and repeatable environment designed to stimulate cognitive workload. This was achieved using a multimodal assessment method (iMotions), which includes eye tracking, galvanic skin response (GSR), electromyography (EMG), and respiration measurements, all conducted during two distinct controlled driving simulation scenarios.
Four healthy subjects (average age = 24, standard deviation = ±2) were monitored during the first scenario, a highway with repeated emergency maneuvers (slalom through cones and double lane change), and the second, five laps of the Paul Ricard circuit. All of this for a total duration of approximately 20 minutes. The participants were not aware that the scenarios were designed to provoke different reactions.
This experimental thesis aims to be the continuation and evolution of a testing phase previously conducted during an internship at iMotions, a company that develops multimodal streaming software and distributes commercial hardware. The hardware was supplied to the NAVLAB at the University of Padua, where the simulator is located.
The results obtained, at first analysis, appear to be consistent with the literature, suggesting that a multimodal approach to physiological signals may characterize emotional and cognitive states in driving scenarios.This preliminary study focuses on the goal of developing and testing a setup and method for non-invasive monitoring of individuals using biosensors in a professional driving simulator (VI-grade Compact Simulator).
This involves the synchronization and integration of hardware and software components.
To detect the emotional and cognitive state of the driver, it is crucial to identify which signals provide reliable information about their condition.
The objective of this study is to observe individuals in a controlled and repeatable environment designed to stimulate cognitive workload. This was achieved using a multimodal assessment method (iMotions), which includes eye tracking, galvanic skin response (GSR), electromyography (EMG), and respiration measurements, all conducted during two distinct controlled driving simulation scenarios.
Four healthy subjects (average age = 24, standard deviation = ±2) were monitored during the first scenario, a highway with repeated emergency maneuvers (slalom through cones and double lane change), and the second, five laps of the Paul Ricard circuit. All of this for a total duration of approximately 20 minutes. The participants were not aware that the scenarios were designed to provoke different reactions.
This experimental thesis aims to be the continuation and evolution of a testing phase previously conducted during an internship at iMotions, a company that develops multimodal streaming software and distributes commercial hardware. The hardware was supplied to the NAVLAB at the University of Padua, where the simulator is located.
The results obtained, at first analysis, appear to be consistent with the literature, suggesting that a multimodal approach to physiological signals may characterize emotional and cognitive states in driving scenarios
Distributed Hybrid Simulation of the Internet of Things and Smart Territories
This paper deals with the use of hybrid simulation to build and compose
heterogeneous simulation scenarios that can be proficiently exploited to model
and represent the Internet of Things (IoT). Hybrid simulation is a methodology
that combines multiple modalities of modeling/simulation. Complex scenarios are
decomposed into simpler ones, each one being simulated through a specific
simulation strategy. All these simulation building blocks are then synchronized
and coordinated. This simulation methodology is an ideal one to represent IoT
setups, which are usually very demanding, due to the heterogeneity of possible
scenarios arising from the massive deployment of an enormous amount of sensors
and devices. We present a use case concerned with the distributed simulation of
smart territories, a novel view of decentralized geographical spaces that,
thanks to the use of IoT, builds ICT services to manage resources in a way that
is sustainable and not harmful to the environment. Three different simulation
models are combined together, namely, an adaptive agent-based parallel and
distributed simulator, an OMNeT++ based discrete event simulator and a
script-language simulator based on MATLAB. Results from a performance analysis
confirm the viability of using hybrid simulation to model complex IoT
scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487
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