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Infrastructure Allocation for Improving Sensing Accuracy and Connectivity Probability Based on Combination Strategy in Vehicular Networks.
- Source :
- IEEE Transactions on Intelligent Transportation Systems; Sep2022, Vol. 23 Issue 9, p15244-15255, 12p
- Publication Year :
- 2022
-
Abstract
- Sensing and communication are the two major concerns in vehicle-road collaboration system, whose function realization needs the support of RSE (roadside equipment). A misleading deployment incurs in waste of valuable resources and degradation of the network performance. Based on the combination strategy, this study proposed a hybrid allocation method to deploy RSE on a highway by considering the sensing capability of traditional ITS sensors and the communication feature of popular networking devices. Two sorts of RSE, the one integrated ITS sensor and networking device, named sensing & communication-RSE (scRSE), and the other belongs to networking devices, named communication-RSE (cRSE), were involved. A hybrid RSE allocation framework was proposed, in which an optimal method was adopted to deploy scRSE on key points for data acquisition and a connectivity probability-based uniform method was used to deploy cRSE for communication. The effectiveness of these methods was verified by case analysis. The results indicated that the proposed hybrid method was very effective and outperformed the conventional uniform deployment method. The key parameters, including the coverage range, RSE spacing, and vehicle density, had an important impact on network connectivity probability. To obtain high connectivity probability, a lower density of connected vehicles (CVs) needs the support of wide coverage of RSE, and vice versa. When the density of CVs reaches to a certain value, vehicular networks could be realized without the help of RSE. Benefitting from the mobility of CVs, increasing their transmission range was better than increasing RSE coverage radius in improving connectivity probability. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15249050
- Volume :
- 23
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Intelligent Transportation Systems
- Publication Type :
- Academic Journal
- Accession number :
- 159209244
- Full Text :
- https://doi.org/10.1109/TITS.2021.3138975