1,702 research outputs found
A Taxonomy for Congestion Control Algorithms in Vehicular Ad Hoc Networks
One of the main criteria in Vehicular Ad hoc Networks (VANETs) that has
attracted the researchers' consideration is congestion control. Accordingly,
many algorithms have been proposed to alleviate the congestion problem,
although it is hard to find an appropriate algorithm for applications and
safety messages among them. Safety messages encompass beacons and event-driven
messages. Delay and reliability are essential requirements for event-driven
messages. In crowded networks where beacon messages are broadcasted at a high
number of frequencies by many vehicles, the Control Channel (CCH), which used
for beacons sending, will be easily congested. On the other hand, to guarantee
the reliability and timely delivery of event-driven messages, having a
congestion free control channel is a necessity. Thus, consideration of this
study is given to find a solution for the congestion problem in VANETs by
taking a comprehensive look at the existent congestion control algorithms. In
addition, the taxonomy for congestion control algorithms in VANETs is presented
based on three classes, namely, proactive, reactive and hybrid. Finally, we
have found the criteria in which fulfill prerequisite of a good congestion
control algorithm
Implementation and Evaluation of a Cooperative Vehicle-to-Pedestrian Safety Application
While the development of Vehicle-to-Vehicle (V2V) safety applications based
on Dedicated Short-Range Communications (DSRC) has been extensively undergoing
standardization for more than a decade, such applications are extremely missing
for Vulnerable Road Users (VRUs). Nonexistence of collaborative systems between
VRUs and vehicles was the main reason for this lack of attention. Recent
developments in Wi-Fi Direct and DSRC-enabled smartphones are changing this
perspective. Leveraging the existing V2V platforms, we propose a new framework
using a DSRC-enabled smartphone to extend safety benefits to VRUs. The
interoperability of applications between vehicles and portable DSRC enabled
devices is achieved through the SAE J2735 Personal Safety Message (PSM).
However, considering the fact that VRU movement dynamics, response times, and
crash scenarios are fundamentally different from vehicles, a specific framework
should be designed for VRU safety applications to study their performance. In
this article, we first propose an end-to-end Vehicle-to-Pedestrian (V2P)
framework to provide situational awareness and hazard detection based on the
most common and injury-prone crash scenarios. The details of our VRU safety
module, including target classification and collision detection algorithms, are
explained next. Furthermore, we propose and evaluate a mitigating solution for
congestion and power consumption issues in such systems. Finally, the whole
system is implemented and analyzed for realistic crash scenarios
iTETRIS: An Integrated Wireless and Traffic Platform for Real-Time Road Traffic Management Solutions
Wireless vehicular cooperative systems have been identified as an attractive solution to improve road traffic management, thereby contributing to the European goal of safer, cleaner, and more efficient and sustainable traffic solutions. V2V-V2I communication technologies can improve traffic management through real-time exchange of data among vehicles and with road infrastructure. It is also of great importance to investigate the adequate combination of V2V and V2I technologies to ensure the continuous and costefficient operation of traffic management solutions based on wireless vehicular cooperative solutions. However, to adequately design and optimize these communication protocols and analyze the potential of wireless vehicular cooperative systems to improve road traffic management, adequate testbeds and field operational tests need to be conducted.
Despite the potential of Field Operational Tests to get the first insights into the benefits and problems faced in the development of wireless vehicular cooperative systems, there is yet the need to evaluate in the long term and large dimension the true potential benefits of wireless vehicular cooperative systems to improve traffic efficiency. To this aim, iTETRIS is devoted to the development of advanced tools coupling traffic and wireless communication simulators
VANET Applications: Hot Use Cases
Current challenges of car manufacturers are to make roads safe, to achieve
free flowing traffic with few congestions, and to reduce pollution by an
effective fuel use. To reach these goals, many improvements are performed
in-car, but more and more approaches rely on connected cars with communication
capabilities between cars, with an infrastructure, or with IoT devices.
Monitoring and coordinating vehicles allow then to compute intelligent ways of
transportation. Connected cars have introduced a new way of thinking cars - not
only as a mean for a driver to go from A to B, but as smart cars - a user
extension like the smartphone today. In this report, we introduce concepts and
specific vocabulary in order to classify current innovations or ideas on the
emerging topic of smart car. We present a graphical categorization showing this
evolution in function of the societal evolution. Different perspectives are
adopted: a vehicle-centric view, a vehicle-network view, and a user-centric
view; described by simple and complex use-cases and illustrated by a list of
emerging and current projects from the academic and industrial worlds. We
identified an empty space in innovation between the user and his car:
paradoxically even if they are both in interaction, they are separated through
different application uses. Future challenge is to interlace social concerns of
the user within an intelligent and efficient driving
Street Smart in 5G : Vehicular Applications, Communication, and Computing
Recent advances in information technology have revolutionized the automotive industry, paving the way for next-generation smart vehicular mobility. Specifically, vehicles, roadside units, and other road users can collaborate to deliver novel services and applications that leverage, for example, big vehicular data and machine learning. Relatedly, fifth-generation cellular networks (5G) are being developed and deployed for low-latency, high-reliability, and high bandwidth communications. While 5G adjacent technologies such as edge computing allow for data offloading and computation at the edge of the network thus ensuring even lower latency and context-awareness. Overall, these developments provide a rich ecosystem for the evolution of vehicular applications, communications, and computing. Therefore in this work, we aim at providing a comprehensive overview of the state of research on vehicular computing in the emerging age of 5G and big data. In particular, this paper highlights several vehicular applications, investigates their requirements, details the enabling communication technologies and computing paradigms, and studies data analytics pipelines and the integration of these enabling technologies in response to application requirements.Peer reviewe
AICP: Augmented Informative Cooperative Perception
Connected vehicles, whether equipped with advanced driver-assistance systems or fully autonomous, require human driver supervision and are currently constrained to visual information in their line-of-sight. A cooperative perception system among vehicles increases their situational awareness by extending their perception range. Existing solutions focus on improving perspective transformation and fast information collection. However, such solutions fail to filter out large amounts of less relevant data and thus impose significant network and computation load. Moreover, presenting all this less relevant data can overwhelm the driver and thus actually hinder them. To address such issues, we present Augmented Informative Cooperative Perception (AICP), the first fast-filtering system which optimizes the informativeness of shared data at vehicles to improve the fused presentation. To this end, an informativeness maximization problem is presented for vehicles to select a subset of data to display to their drivers. Specifically, we propose (i) a dedicated system design with custom data structure and lightweight routing protocol for convenient data encapsulation, fast interpretation and transmission, and (ii) a comprehensive problem formulation and efficient fitness-based sorting algorithm to select the most valuable data to display at the application layer. We implement a proof-of-concept prototype of AICP with a bandwidth-hungry, latency-constrained real-life augmented reality application. The prototype adds only 12.6 milliseconds of latency to a current informativeness-unaware system. Next, we test the networking performance of AICP at scale and show that AICP effectively filters out less relevant packets and decreases the channel busy time.Peer reviewe
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