scholarly journals Multi-Hop Dynamic Map Data Propagation Algorithm for Clustered Vehicular Networks

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1728
Author(s):  
Odilbek Urmonov ◽  
HyungWon Kim
Keyword(s):  
Large Scale ◽  
Vehicular Networks ◽  
Dynamic Environment ◽  
Driving Safety ◽  
Local Dynamic ◽  
Vehicular Communication ◽  
Data Propagation ◽  
Dynamic Map ◽  
Map Data ◽  
Transmission Windows

To ensure the driving safety in vehicular network, it is necessary to construct a local dynamic map (LDM) for an extended range. Using the standard vehicular communication protocols, however, vehicles can construct the LDM for only one-hop range. Constructing large-scale LDM is highly challenging because vehicles randomly change their position. This paper proposes a dynamic map propagation (DMP) method, which builds a large aggregated LDM data using a multi-hop communication. To reduce the data overhead, we introduce an efficient clustering method based on a half-circle of the forwarder’s wireless range. The DMP elects one forwarder per cluster, which constructs LDM and forwards it to a neighbor cluster. The inter-cluster interference is minimized by allocating a different transmit window to each cluster. DMP copes with a dynamic environment by frequently re-electing the forwarders and their associated transmission windows. Simulation results reveal that DMP enhances the forwarders’ reception ratio by 20%, while extending LDM dissemination range by 29% over a previous work.

scholarly journals Interference Analysis for Vehicle-to-Vehicle Communications at 28 GHz

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 262 ◽  
Author(s):  
Omar A. Saraereh ◽  
Ashraf Ali ◽  
Imran Khan ◽  
Khaled Rabie
Keyword(s):  
Communication Networks ◽  
Large Scale ◽  
Vehicular Networks ◽  
High Capacity ◽  
Ergodic Capacity ◽  
Vehicular Communication ◽  
Interference Analysis ◽  
Vehicular Communication Networks ◽  
On The Road ◽  
The Impact

High capacity and ultra-reliable vehicular communication are going to be important aspects of beyond 5G communication networks. However, the vehicular communication problem becomes complex at a large scale when vehicles are roaming on the road, while simultaneously communicating with each other. Moreover, at higher frequencies (like 28 GHz), the dynamics of vehicular communication completely shift towards unpredictability and low-reliability. These factors may result in high packet error and a large amount of interference, resulting in regular disruptions in communications. A thorough understanding of performance variations is the key to moving towards the next generation of vehicular networks. With this intent, this article aims to provide a comprehensive interference analysis, wherein the closed-form expressions of packet error probability (PEP) and ergodic capacity are derived. Using the expression of the PEP, diversity analysis is provided which unveils the impact of channel nonlinearities on the performance of interference-constrained vehicular networks. The insights provided here are expected to pave the way for reliable and high capacity vehicular communication networks.

scholarly journals A Multi-Hop Data Dissemination Algorithm for Vehicular Communication

Computers ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 25 ◽  
Author(s):  
Odilbek Urmonov ◽  
HyungWon Kim
Keyword(s):  
Vehicular Networks ◽  
Data Dissemination ◽  
Propagation Distance ◽  
Ieee 802.11P ◽  
Local Dynamic ◽  
Vehicular Communication ◽  
Additional Time ◽  
The Road ◽  
Message Dissemination ◽  
On The Road

In vehicular networks, efficient multi-hop message dissemination can be used for various purposes, such a informing the driver about the recent emergency event or propagating the local dynamic map of a predefined region. Dissemination of warning information up to a longer distance can reduce the accidents on the road. It provides a driver additional time to react to the situations adequately and assists in finding a safe route towards the destination. The adopted V2X standards, ETSI TS’s C-ITS and IEEE 1609/IEEE 802.11p, specify only primitive multi-hop message dissemination schemes. IEEE 1609.4 standard disseminates the broadcast messages using the method of flooding, which causes high redundancy, severe congestion, and long delay during multi-hop propagation. To address these problems, we propose an effective broadcast message dissemination method. It introduces a notion of source Lateral Crossing Line (LCL) algorithm, which elects a set of relay vehicles for each hop based on the vehicle locations in a way that reduces the redundant retransmission and congestion, consequently minimizing the delays. Our simulation results demonstrated that the proposed method can achieve about 15% reduction in delays and 2 times the enhancement in propagation distance compared with the previous methods.

scholarly journals Joint optimization of network selection and task offloading for vehicular edge computing

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Lujie Tang ◽  
Bing Tang ◽  
Li Zhang ◽  
Feiyan Guo ◽  
Haiwu He
Keyword(s):  
Large Scale ◽  
Vehicular Networks ◽  
Access Point ◽  
Edge Computing ◽  
Network Selection ◽  
Network Access ◽  
Task Execution ◽  
Point Selection ◽  
Vehicle Movement ◽  
Task Offloading

AbstractTaking the mobile edge computing paradigm as an effective supplement to the vehicular networks can enable vehicles to obtain network resources and computing capability nearby, and meet the current large-scale increase in vehicular service requirements. However, the congestion of wireless networks and insufficient computing resources of edge servers caused by the strong mobility of vehicles and the offloading of a large number of tasks make it difficult to provide users with good quality of service. In existing work, the influence of network access point selection on task execution latency was often not considered. In this paper, a pre-allocation algorithm for vehicle tasks is proposed to solve the problem of service interruption caused by vehicle movement and the limited edge coverage. Then, a system model is utilized to comprehensively consider the vehicle movement characteristics, access point resource utilization, and edge server workloads, so as to characterize the overall latency of vehicle task offloading execution. Furthermore, an adaptive task offloading strategy for automatic and efficient network selection, task offloading decisions in vehicular edge computing is implemented. Experimental results show that the proposed method significantly improves the overall task execution performance and reduces the time overhead of task offloading.

scholarly journals Millimeter Wave Spatial Channel Characterization for Vehicular Communications

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 64 ◽  
Author(s):  
Fidel Rodríguez-Corbo ◽  
Leyre Azpilicueta ◽  
Mikel Celaya-Echarri ◽  
Peio López-Iturri ◽  
Imanol Picallo ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Autonomous Vehicles ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Small Scale ◽  
Vehicular Communications ◽  
Next Generation ◽  
Vehicular Communication ◽  
High Definition ◽  
High Data

With the growing demand of vehicle-mounted sensors over the last years, the amount of critical data communications has increased significantly. Developing applications such as autonomous vehicles, drones or real-time high-definition entertainment requires high data-rates in the order of multiple Gbps. In the next generation of vehicle-to-everything (V2X) networks, a wider bandwidth will be needed, as well as more precise localization capabilities and lower transmission latencies than current vehicular communication systems due to safety application requirements; 5G millimeter wave (mmWave) technology is envisioned to be the key factor in the development of this next generation of vehicular communications. However, the implementation of mmWave links arises with difficulties due to blocking effects between mmWave transceivers, as well as different channel impairments for these high frequency bands. In this work, the mmWave channel propagation characterization for V2X communications has been performed by means of a deterministic in-house 3D ray launching simulation technique. A complex heterogeneous urban scenario has been modeled to analyze the different propagation phenomena of multiple mmWave V2X links. Results for large and small-scale propagation effects are obtained for line-of-sight (LOS) and non-LOS (NLOS) trajectories, enabling inter-data vehicular comparison. These analyzed results and the proposed methodology can aid in an adequate design and implementation of next generation vehicular networks.

The impact of large-scale reclamation on hydro-dynamic environment–A case study of Xinghua Bay

2015 ◽  
Vol 15 (4) ◽  
pp. 583-592 ◽  
Author(s):  
Jing Yu ◽  
Xianwen Bao ◽  
Yang Ding ◽  
Wei Zhang ◽  
Lingling Zhou
Keyword(s):  
Large Scale ◽  
Dynamic Environment ◽  
The Impact

An Evaluation of Pseudonym Changes for Vehicular Networks in Large-Scale, Realistic Traffic Scenarios

2018 ◽  
Vol 19 (10) ◽  
pp. 3400-3405 ◽  
Author(s):  
David Forster ◽  
Hans Lohr ◽  
Anne Gratz ◽  
Jonathan Petit ◽  
Frank Kargl
Keyword(s):  
Large Scale ◽  
Vehicular Networks

scholarly journals Applying Machine Learning for Improving Performance Classification on Driving Behavior

2021 ◽  
Vol 4 (1) ◽  
pp. 8
Author(s):  
Ahmad Iwan Fadli ◽  
Selo Sulistyo ◽  
Sigit Wibowo
Keyword(s):  
Machine Learning ◽  
Traffic Accident ◽  
Large Scale ◽  
Detection System ◽  
Difficult Problem ◽  
Sensor Data ◽  
Driving Safety ◽  
Support Vector ◽  
Classification Methods ◽  
Machine Learning Classification

Traffic accident is a very difficult problem to handle on a large scale in a country. Indonesia is one of the most populated, developing countries that use vehicles for daily activities as its main transportation.  It is also the country with the largest number of car users in Southeast Asia, so driving safety needs to be considered. Using machine learning classification method to determine whether a driver is driving safely or not can help reduce the risk of driving accidents. We created a detection system to classify whether the driver is driving safely or unsafely using trip sensor data, which include Gyroscope, Acceleration, and GPS. The classification methods used in this study are Random Forest (RF) classification algorithm, Support Vector Machine (SVM), and Multilayer Perceptron (MLP) by improving data preprocessing using feature extraction and oversampling methods. This study shows that RF has the best performance with 98% accuracy, 98% precision, and 97% sensitivity using the proposed preprocessing stages compared to SVM or MLP.

scholarly journals Accurate Real-Time Traffic Speed Estimation Using Infrastructure-Free Vehicular Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Zongjian He ◽  
Buyang Cao ◽  
Yan Liu
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Vehicular Networks ◽  
Route Planning ◽  
Speed Estimation ◽  
Traffic Condition ◽  
Real Time Traffic ◽  
Traffic Trace ◽  
Traffic Speed ◽  
Traffic Speed Estimation

Real-time traffic speed is indispensable for many ITS applications, such as traffic-aware route planning and eco-driving advisory system. Existing traffic speed estimation solutions assume vehicles travel along roads using constant speed. However, this assumption does not hold due to traffic dynamicity and can potentially lead to inaccurate estimation in real world. In this paper, we propose a novel in-network traffic speed estimation approach using infrastructure-free vehicular networks. The proposed solution utilizes macroscopic traffic flow model to estimate the traffic condition. The selected model only relies on vehicle density, which is less likely to be affected by the traffic dynamicity. In addition, we also demonstrate an application of the proposed solution in real-time route planning applications. Extensive evaluations using both traffic trace based large scale simulation and testbed based implementation have been performed. The results show that our solution outperforms some existing ones in terms of accuracy and efficiency in traffic-aware route planning applications.

scholarly journals Reconstruction of three-dimensional maps based on closed-form solutions of the variational problem of multisensor data registration

2019 ◽  
Vol 484 (6) ◽  
pp. 672-677
Author(s):  
A. V. Vokhmintcev ◽  
A. V. Melnikov ◽  
K. V. Mironov ◽  
V. V. Burlutskiy
Keyword(s):  
Closed Form ◽  
Large Scale ◽  
Three Dimensional ◽  
Dynamic Environment ◽  
Closed Form Solution ◽  
Point Clouds ◽  
Accurate Method ◽  
Form Solution ◽  
Closed Form Solutions ◽  
Reconstruction Methods

A closed-form solution is proposed for the problem of minimizing a functional consisting of two terms measuring mean-square distances for visually associated characteristic points on an image and meansquare distances for point clouds in terms of a point-to-plane metric. An accurate method for reconstructing three-dimensional dynamic environment is presented, and the properties of closed-form solutions are described. The proposed approach improves the accuracy and convergence of reconstruction methods for complex and large-scale scenes.

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