Abstract
Purpose This paper aims to introduce vehicular network platform, routing and broadcasting methods and vehicular positioning enhancement technology, which are three aspects of the applications of intelligent computing in vehicular networks. From this paper, the role of intelligent algorithm in the field of transportation and the vehicular networks can be understood. Design/methodology/approach In this paper, the authors introduce three different methods in three layers of vehicle networking, which are data cleaning based on machine learning, routing algorithm based on epidemic model and cooperative localization algorithm based on the connect vehicles. Findings In Section 2, a novel classification-based framework is proposed to efficiently assess the data quality and screen out the abnormal vehicles in database. In Section 3, the authors can find when traffic conditions varied from free flow to congestion, the number of message copies increased dramatically and the reachability also improved. The error of vehicle positioning is reduced by 35.39% based on the CV-IMM-EKF in Section 4. Finally, it can be concluded that the intelligent computing in the vehicle network system is effective, and it will improve the development of the car networking system. Originality/value This paper reviews the research of intelligent algorithms in three related areas of vehicle networking. In the field of vehicle networking, these research results are conducive to promoting data processing and algorithm optimization, and it may lay the foundation for the new methods.
Highlights
The advancement of computer technology in recent years has allowed researchers to develop efficient optimization techniques for solving large-scale problems in various fields and helped practitioners to incorporate some of these techniques into their planning activities through specific integrated decision support systems (Jin and Meng, 2010; Chiong and Weise, 2011)
It can be concluded that the intelligent computing in the vehicle network system is effective, and it will improve the development of the car networking system
This paper reviews the research of intelligent algorithms in three related areas of vehicle networking
Summary
The advancement of computer technology in recent years has allowed researchers to develop efficient optimization techniques for solving large-scale problems in various fields and helped practitioners to incorporate some of these techniques into their planning activities through specific integrated decision support systems (Jin and Meng, 2010; Chiong and Weise, 2011). Intelligent computing approaches inspired by principles of nature such as evolutionary algorithms, swarm intelligence algorithms, artificial neural networks and fuzzy logic have emerged as a rapidly growing research area. These approaches have been applied to various problems in different fields (Çatay et al, 2013; Jin and Hammer, 2014). © Daxin Tian, Weiqiang Gong, Wenhao Liu, Xuting Duan, Yukai Zhu, Chao Liu and Xin Li. Published in Journal of Intelligent and Connected Vehicles. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
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