3 research outputs found
Quality of Assessment in Connected Vehicles
In recent years, there has been a huge interest in Machine-to-Machine connectivity under the umbrella of Internet of Things (IoT). With the UK Government looking to trial autonomous (driverless) cars this year, connected vehicles will play a key part in improving and managing existing road safety and congestion, leading to a new generation of intelligent transport systems. This is also well aligned to the current initiatives by the automotive industry to improve the driver’s experience on-board. However, the wireless channels most suitable for this application have not been standardized. In this paper, we review the wireless channels suitable for vehicle-2-vehicle (V2V) and Vehicle–to-x (V2x) connectivity. We further present preliminary analysis on the factors that impact the Quality of Service (QoS) of connected vehicles. We use the open access GEMV2 data to carry out Analysis of Variance (ANOVA) and Principal Component Analysis (PCA) on the link quality and found that both line of sight and non line of sight has a significant impact on the link quality. The work presented here will help in the development of connected vehicle network (CVN) prediction model and control for V2V and V2x connectivity. It will further contribute towards unfolding and testing key research questions in the context of connected vehicles which may otherwise be overlooked
Quality of Assessment in Connected Vehicles
In recent years, there has been a huge interest in Machine-to-Machine connectivity under the umbrella of Internet of Things (IoT). With the UK Government looking to trial autonomous (driverless) cars this year, connected vehicles will play a key part in improving and managing existing road safety and congestion, leading to a new generation of intelligent transport systems. This is also well aligned to the current initiatives by the automotive industry to improve the driver’s experience on-board. However, the wireless channels most suitable for this application have not been standardized. In this paper, we review the wireless channels suitable for vehicle-2-vehicle (V2V) and Vehicle–to-x (V2x) connectivity. We further present preliminary analysis on the factors that impact the Quality of Service (QoS) of connected vehicles. We use the open access GEMV2 data to carry out Analysis of Variance (ANOVA) and Principal Component Analysis (PCA) on the link quality and found that both line of sight and non line of sight has a significant impact on the link quality. The work presented here will help in the development of connected vehicle network (CVN) prediction model and control for V2V and V2x connectivity. It will further contribute towards unfolding and testing key research questions in the context of connected vehicles which may otherwise be overlooked
QoS Assessment and Modelling of Connected Vehicle Network within Internet of Vehicles
Connected vehicles have huge potential in improving
road safety and traffic congestion. The primary aim of this
paper is threefold: firstly to present an overview of network
models in connected vehicles; secondly to analyze the factors
that impact the Quality of Service (QoS) of connected vehicles
and thirdly to present initial modelling results on Link QoS. We
use the open access Geometry-based Efficient Propagation
Model (GEMV2
) data to carry out Analysis of Variance,
Principal Component Analysis and Classical Multi-Dimensional
scaling on the link quality for vehicle-2-vehicle (V2V) and
vehicle-2-infrastucture (V2i) data and found that both line of
sight and non-line of sight has a significant impact on the link
quality. We further carried out modelling using system
identification method of the connected vehicle network (CVN)
in terms of Link QoS based on the parameters identified by the
QoS assessment. We evaluated the CVN in terms of a step
response achieving steady-state within 80 seconds for V2V data
and 500 seconds for V2i data. The work presented here will
further help in the development of CVN prediction model and
control for V2V and vehicle-2-anything connectivity