424 research outputs found
Synergizing Roadway Infrastructure Investment with Digital Infrastructure for Infrastructure-Based Connected Vehicle Applications: Review of Current Status and Future Directions
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The safety, mobility, environmental and economic benefits of Connected and Autonomous Vehicles (CAVs) are potentially dramatic. However, realization of these benefits largely hinges on the timely upgrading of the existing transportation system. CAVs must be enabled to send and receive data to and from other vehicles and drivers (V2V communication) and to and from infrastructure (V2I communication). Further, infrastructure and the transportation agencies that manage it must be able to collect, process, distribute and archive these data quickly, reliably, and securely. This paper focuses on current digital roadway infrastructure initiatives and highlights the importance of including digital infrastructure investment alongside more traditional infrastructure investment to keep up with the auto industry's push towards this real time communication and data processing capability. Agencies responsible for transportation infrastructure construction and management must collaborate, establishing national and international platforms to guide the planning, deployment and management of digital infrastructure in their jurisdictions. This will help create standardized interoperable national and international systems so that CAV technology is not deployed in a haphazard and uncoordinated manner
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Cooperative Eco-Driving at Signalized Intersections in a Partially Connected and Automated Vehicle Environment
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
A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles
Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy
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
Virtual and Real Data Populated Intersection Visualization and Testing Tool for V2X Application Development
The capability afforded by Vehicle-to-Vehicle communication improves
situational awareness and provides advantages for many of the traffic problems
caused by reduced visibility or No-Line-of-Sight situations, being useful for
both autonomous and non-autonomous driving. Additionally, with the traffic
light Signal Phase and Timing and Map Datainformation and other advisory
information provided with Vehicle-to-Infrastructure (V2I) communication,
outcomes which benefit the driver in the long run, such as reducing fuel
consumption with speed regulation or decreasing traffic congestion through
optimal speed advisories, providing red light violation warning messages and
intersection motion assist messages for collision-free intersection maneuvering
are all made possible. However, developing applications to obtain these
benefits requires an intensive development process within a lengthy testing
period. Understanding the intersection better is a large part of this
development process. Being able to see what information is broadcasted and how
this information translates into the real world would both benefit the
development of these highly useful applications and also ensure faster
evaluation, when presented visually, using an easy to use and interactive tool.
Moreover, recordings of this broadcasted information can be modified and used
for repeated testing. Modification of the data makes it flexible and allows us
to use it for a variety of testing scenarios at a virtually populated
intersection. Based on this premise, this paper presents and demonstrates
visualization tools to project SPaT, MAP and Basic Safety Message information
into easy to read real-world based graphs. Also, it provides information about
the modification of the real-world data to allow creation of a virtually
populated intersection, along with the capability to also inject virtual
vehicles at this intersection
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