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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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 |
_version_ |
1724194709605187584 |