1,032 research outputs found
Performance Analysis of C-V2I-Based Automotive Collision Avoidance
One of the key applications envisioned for C-V2I (Cellular Vehicle-to-Infrastructure) networks pertains to safety on the road. Thanks to the exchange of Cooperative Awareness Messages (CAMs), vehicles and other road users (e.g., pedestrians) can advertise their position, heading and speed and sophisticated algorithms can detect potentially dangerous situations leading to a crash. In this paper, we focus on the safety application for automotive collision avoidance at intersections, and study the effectiveness of its deployment in a C-V2I-based infrastructure. In our study, we also account for the location of the server running the application as a factor in the system design. Our simulation-based results, derived in real-world scenarios, provide indication on the reliability of algorithms for car-to-car and car-to-pedestrian collision avoidance, both when a human driver is considered and when automated vehicles (with faster reaction times) populate the streets.This work was partially supported by TIM through the research contract “Multi-access Edge Computing”, and by the European Commission through the H2020 5GTRANSFORMER
project (Project ID 761536
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
Development and Performance Evaluation of Network Function Virtualization Services in 5G Multi-Access Edge Computing
L'abstract è presente nell'allegato / the abstract is in the attachmen
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
Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT
In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV).
The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets.
This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols.
The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety
Hardware-in-the-Loop and Road Testing of RLVW and GLOSA Connected Vehicle Applications
This paper presents an evaluation of two different Vehicle to Infrastructure
(V2I) applications, namely Red Light Violation Warning (RLVW) and Green Light
Optimized Speed Advisory (GLOSA). The evaluation method is to first develop and
use Hardware-in-the-Loop (HIL) simulator testing, followed by extension of the
HIL testing to road testing using an experimental connected vehicle. The HIL
simulator used in the testing is a state-of-the-art simulator that consists of
the same hardware like the road side unit and traffic cabinet as is used in
real intersections and allows testing of numerous different traffic and
intersection geometry and timing scenarios realistically. First, the RLVW V2I
algorithm is tested in the HIL simulator and then implemented in an
On-Board-Unit (OBU) in our experimental vehicle and tested at real world
intersections. This same approach of HIL testing followed by testing in real
intersections using our experimental vehicle is later extended to the GLOSA
application. The GLOSA application that is tested in this paper has both an
optimal speed advisory for passing at the green light and also includes a red
light violation warning system. The paper presents the HIL and experimental
vehicle evaluation systems, information about RLVW and GLOSA and HIL simulation
and road testing results and their interpretations
Development and Simulation-based Testing of a 5G-Connected Intersection AEB System
In Europe, 20% of road crashes occur at intersections. In recent years,
evolving communication technologies are making V2V and V2I faster and more
reliable; with such advancements, these crashes, as well as their economic
cost, can be partially reduced. In this work, we concentrate on straight path
intersection collisions. Connectivity-based algorithms relying on 5G technology
and smart sensors are presented and compared to a commercial radar AEB logic in
order to evaluate performances and effectiveness in collision avoidance or
mitigation. The aforementioned novel safety systems are tested in a blind
intersection and low adherence scenario. The first algorithm proposed is
obtained by incorporating connectivity information to the original control
scheme, while the second algorithm proposed is a novel control logic fully
capable of utilizing also adherence estimation provided by smart sensors. Test
results show an improvement in terms of safety for both the architecture and
high prospects for future developments
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