Applications of intelligent computing in vehicular networks

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.