V2V- and V2X-Communication data within a distributed computing platform for adaptive radio channel modelling

Pinzel, Florian; Holfeld, Jörg; Olunczek, Andrej; Balzer, Paul; Michler, Oliver

doi:10.1109/mtits.2019.8883347

Cited by 5 publications

(6 citation statements)

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“…The work in [7] presents the use of the IoT message protocol MQTT for transmitting accumulated and live V2X data from vehicles to a centralized big data platform. The usage of MQTT introduces a small overhead regarding network bandwidth and works on top of the standard TCP/IP protocol.…”

Section: Related Workmentioning

confidence: 99%

Vehicular Message Exchange in Cross-border Scenarios Using Public Cloud Infrastructure

Vilalta

Casellas

Sedar

et al. 2020

2020 IEEE 3rd 5G World Forum (5GWF)

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Cross-border scenarios are of extreme importance in current research work on 5G networks for connected vehicles. Network services and applications for connected vehicles, which are in specific cases expected to run on Mobile Edge Computing (MEC) infrastructure, might experience problems through country borders due to inter-domain. Given that crossborder scenarios typically imply a change of network operator, deployed MEC services need to work in such environments and, where applicable, different entities need to synchronize their input/output vehicular messages and work seamlessly in such a multi-operator context. One of most significant MEC services is vehicular message brokering. It consists on the controlled publishing and notification mechanisms to create awareness to all subscribed vehicles concerning their position as well as other significant events that may arise, such as hazardous events. This paper presents an architecture and method for vehicular message exchange, based on current Intelligent Transport Systems (ITS) standards, and proposes a novel hierarchical message brokering approach with the purpose of solving cross-domain scenarios, which can be applied not only in the aforementioned cross-border case but also in other scenarios where there is no single domain (i.e., with multiple vendors). Message Queuing Telemetry Transport (MQTT) servers are used in a hierarchical approach (locating a parent MQTT broker in a public cloud) in order to demonstrate the feasibility of using them for crossborder scenarios. Latency results are obtained in order to evaluate the performance penalty of the proposed solution.

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Section: Related Workmentioning

confidence: 99%

Vehicular Message Exchange in Cross-border Scenarios Using Public Cloud Infrastructure

Vilalta

Casellas

Sedar

et al. 2020

2020 IEEE 3rd 5G World Forum (5GWF)

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“…Green Light Optimized Speed Advisory (GLOSA) uses real-time traffic light timing data as well as information on the speed and position of individual cars to generate the ideal speed advisory for each vehicle approaching their next traffic light. In principle, GLOSA intends to minimize fuel consumption and emissions while enhancing traffic flow and safety by providing drivers with the statistics and information described above [8,9]. From the point of view of researchers, it is important to add maps that indicate the level of environmental pollution in residential areas and link them with an application that works on smartphones, integrated with GLOSA technology.…”

Section: Introductionmentioning

confidence: 99%

Controlling Traffic Congestion in a Residential Area via GLOSA Development

Jawad,

Nitulescu

2024

Applied Sciences

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The phenomenon of traffic congestion started in the second half of the twentieth century. This arose because of our society’s constant increase in demand for mobility. The excessive traffic of vehicles attempting to use the same infrastructure at the same time is what causes congestion. The consequences are well-known: delays, air pollution, reduced speed, and dissatisfaction (which may lead to risky maneuvers, reducing pedestrian and other driver safety). Our objective is to simulate the change in traffic patterns brought about by app users in residential areas (using navigational tools like Google Maps and Apple Maps), where the majority of navigational tools provide shortcuts that go through residential areas. In addition to discouraging navigation apps from directing drivers through residential areas during peak hours to mitigate pollution levels, by developing an algorithm based on the technology of Green Light Optimized Speed Advisory (GLOSA) and implementing it in a simulated environment (VISSIM), we can see the effect of changing the duration of red lights while keeping green lights constant. Overall, this solution can be implemented to change the times of traffic lights without the need for supplies, additional equipment, or warning signs because most cities’ traffic lights are already remotely controlled. In addition, this procedure is temporary to provide some freedom and does not adhere to the speed specified for drivers who wish to pass through residential areas outside of rush hour.

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“…Figure 6. 16 Comparison of the measured and predicted PL for the log-distance, RF and pre-trained CNN model on the testing set.…”

Section: List Of Figuresmentioning

confidence: 99%

“…Additionally, vehicular communication is a key technology for intelligent transportation systems (ITS) due to the need for safer, more efficient, and sustainable transportation [10]. ITS applications consider the exchange of data in different vehicular communication among vehicles and with road infrastructure referred to as vehicle-to-vehicle (V2V) [11,12], vehicle-to-infrastructure (V2I) [13,14,15], and vehicle-to-everything (V2X) [16] to provide secure and reliable wireless communications between vehicles to road infrastructure, and among vehicles, respectively, expected to operate in the frequency band below 6 GHz [17,18], and in millimeter wave [11], oriented to short-range communications [19].…”

Section: Motivationmentioning

confidence: 99%

“…In recent years, several works have attempted to use machine learning (ML) for PL prediction in different radio-propagation environments, mainly in urban [47,78,79], and suburban areas [63]. Others have focused on vehicle-tovehicle (V2V) communications [16,70], prediction of the received power from unmanned aerial vehicles (UAV) [48,51], aircraft communications [50], and also smart campus environments [80]. The dataset to design these models has been obtained by conducting measurement campaigns or trough simulation methods.…”

Section: Machine Learning For Path Loss Predictionmentioning

confidence: 99%

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On Machine Learning Techniques Toward Path Loss Modeling in 5g and Beyond Wireless Systems

ELEDUVITH NUNEZ RUIZ

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I would like to express my sincere gratitude to my co-advisor, Professor Lisandro Lovisolo, for his insightful suggestions, enthusiasm, and always being there when I needed his support. This work would not have been possible without his guidance.I would like to acknowledge and thank my family, my parents, my brother, and his wife. They always encouraged me and believed in me.I would like to thank my colleagues at PUC-Rio and CETUC, especially Johnes Ricardo, for their sincere friendship and assistance. A special appreciation to Prof. Guilherme Temporão, Marcelo Balisteri, and Marta Pudwell for their valuable support in the final stage of this journey.I would like to thank my colleagues from the Radio-Propagation Laboratory, CETUC, Carlos Orihuela, Marcelo Molina, Carlos Rodriguez, and Professor Glaucio Lopes, for helping me process the datasets from the measurement campaigns used in this research and always being there when I needed their support.A special appreciation and dedication to my husband Jorge for all the encouragement, love, patience, source of inspiration, and technical support he gave me during this journey. For always looking after my well-being.

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V2V- and V2X-Communication data within a distributed computing platform for adaptive radio channel modelling

Cited by 5 publications

References 5 publications

Vehicular Message Exchange in Cross-border Scenarios Using Public Cloud Infrastructure

Vehicular Message Exchange in Cross-border Scenarios Using Public Cloud Infrastructure

Controlling Traffic Congestion in a Residential Area via GLOSA Development

On Machine Learning Techniques Toward Path Loss Modeling in 5g and Beyond Wireless Systems

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