Model Predictive Power Control for Cooperative Vehicle Safety Systems

In vehicular networking, the heavy traffic can cause channel congestion and hence, degrade the tracking accuracy of cooperative vehicle safety systems. To overcome this problem, a dynamic packet reception model that integrates the packets reception rate and the vehicle density is proposed. Then, a t...

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Main Authors: Fuxin Zhang, Yuyue Du, Wei Liu, Peng Li
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8251721/
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spelling doaj-b719628e070345fb95907c97128ed3b92021-03-29T20:30:44ZengIEEEIEEE Access2169-35362018-01-0164797481010.1109/ACCESS.2018.27915368251721Model Predictive Power Control for Cooperative Vehicle Safety SystemsFuxin Zhang0https://orcid.org/0000-0002-5548-2794Yuyue Du1https://orcid.org/0000-0002-5586-109XWei Liu2https://orcid.org/0000-0001-6468-3232Peng Li3College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaIn vehicular networking, the heavy traffic can cause channel congestion and hence, degrade the tracking accuracy of cooperative vehicle safety systems. To overcome this problem, a dynamic packet reception model that integrates the packets reception rate and the vehicle density is proposed. Then, a traffic-flow-based vehicle density estimation method is designed. This estimation method is capable of predicting the vehicle density in the scenario, where there exist strong interactions among the vehicles. Based on the vehicle density method, a dynamical transmission power control strategy is developed. This transmission power control strategy employs model predictive control to make the optimal control decisions based on the estimated vehicle density. Experimental analyses demonstrate that the dynamical power control strategy can greatly enhance the vehicle tracking performance of cooperative vehicle safety systems under dynamical traffic situation.https://ieeexplore.ieee.org/document/8251721/Cooperative vehicle safety systemsIEEE802.11pchannel congestiondensity estimationvehicle tracking
collection DOAJ
language English
format Article
sources DOAJ
author Fuxin Zhang
Yuyue Du
Wei Liu
Peng Li
spellingShingle Fuxin Zhang
Yuyue Du
Wei Liu
Peng Li
Model Predictive Power Control for Cooperative Vehicle Safety Systems
IEEE Access
Cooperative vehicle safety systems
IEEE802.11p
channel congestion
density estimation
vehicle tracking
author_facet Fuxin Zhang
Yuyue Du
Wei Liu
Peng Li
author_sort Fuxin Zhang
title Model Predictive Power Control for Cooperative Vehicle Safety Systems
title_short Model Predictive Power Control for Cooperative Vehicle Safety Systems
title_full Model Predictive Power Control for Cooperative Vehicle Safety Systems
title_fullStr Model Predictive Power Control for Cooperative Vehicle Safety Systems
title_full_unstemmed Model Predictive Power Control for Cooperative Vehicle Safety Systems
title_sort model predictive power control for cooperative vehicle safety systems
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description In vehicular networking, the heavy traffic can cause channel congestion and hence, degrade the tracking accuracy of cooperative vehicle safety systems. To overcome this problem, a dynamic packet reception model that integrates the packets reception rate and the vehicle density is proposed. Then, a traffic-flow-based vehicle density estimation method is designed. This estimation method is capable of predicting the vehicle density in the scenario, where there exist strong interactions among the vehicles. Based on the vehicle density method, a dynamical transmission power control strategy is developed. This transmission power control strategy employs model predictive control to make the optimal control decisions based on the estimated vehicle density. Experimental analyses demonstrate that the dynamical power control strategy can greatly enhance the vehicle tracking performance of cooperative vehicle safety systems under dynamical traffic situation.
topic Cooperative vehicle safety systems
IEEE802.11p
channel congestion
density estimation
vehicle tracking
url https://ieeexplore.ieee.org/document/8251721/
work_keys_str_mv AT fuxinzhang modelpredictivepowercontrolforcooperativevehiclesafetysystems
AT yuyuedu modelpredictivepowercontrolforcooperativevehiclesafetysystems
AT weiliu modelpredictivepowercontrolforcooperativevehiclesafetysystems
AT pengli modelpredictivepowercontrolforcooperativevehiclesafetysystems
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