Trajectory-based data Forwarding with future Neighbor Prediction in autonomous driving vehicular environments

Chi En Chang, Yu Yuan Lin, Kuo Feng Ssu

研究成果: Conference contribution

6 引文 斯高帕斯(Scopus)

摘要

In VANETs, vehicle-to-vehicle communication is a challenge due to the fast topology changing, frequent disconnections, and highly variable traffic densities. This paper describes a Trajectory-based data Forwarding scheme with future Neighbor Prediction (TFNP) in autonomous driving vehicular environments. The most important characteristic of the environments is that the prediction for future position of vehicles could be sufficiently accurate. With the trajectory information of all autonomous vehicles, the future neighbors of each vehicle can be properly identified. The packet forwarding ability of the future neighbors is evaluated and forwarding sequences are thus constructed. When an autonomous vehicle needs to send data, it will transmit packets based on the constructed forwarding path. The simulation results demonstrate the effectiveness and efficiency of the developed scheme in the autonomous driving vehicular environments.

原文English
主出版物標題Proceedings of the 40th Annual IEEE Conference on Local Computer Networks, LCN 2015
編輯Salil Kanhere, Soumaya Cherkaoui, Jens Tolle
發行者IEEE Computer Society
頁面884-892
頁數9
ISBN(電子)9781467367738
DOIs
出版狀態Published - 2015 12月 24
事件40th Annual IEEE Conference on Local Computer Networks, LCN 2015 - Clearwater Beach, United States
持續時間: 2015 10月 262015 10月 29

出版系列

名字Proceedings - Conference on Local Computer Networks, LCN
2015-December

Other

Other40th Annual IEEE Conference on Local Computer Networks, LCN 2015
國家/地區United States
城市Clearwater Beach
期間15-10-2615-10-29

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 硬體和架構

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