A software framework of roadside units for traffic condition perception and broadcast

Shao Hua Wang, Wei Liang Yiu, Chia Heng Tu, Da Wei Chang, Wei Hsun Lee

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

While vehicle-to-everything technology has been proposed to improve road traffic efficiency and safety, it would suffer from the low coverage during an early stage of vehicle-to-everything deployment. The infrastructure-based solutions have been developed to tackle the problem by gathering traffic status on a roadside unit and broadcasting the detected information to nearby connected vehicles. In this work, we aim to augment such an infrastructure-centric design by proposing a multiple applications software framework to broadcast the sensed traffic conditions to connected vehicles in the vicinity. In addition, we propose a software module to improve the handling of multiple applications for the roadside unit. We have evaluated the proposed software in indoor tests, which shows that the framework can significantly improve traffic safety while conforming to the performance specifications of the standards defined by the Society of Automotive Engineers.

原文English
主出版物標題Proceedings of the 2022 Research in Adaptive and Convergent Systems, RACS 2022
發行者Association for Computing Machinery
頁面1-8
頁數8
ISBN(電子)9781450393980
DOIs
出版狀態Published - 2022 10月 3
事件2022 Conference on Research in Adaptive and Convergent Systems, RACS 2022 - Virtual, Online, Japan
持續時間: 2022 10月 32022 10月 6

出版系列

名字ACM International Conference Proceeding Series

Conference

Conference2022 Conference on Research in Adaptive and Convergent Systems, RACS 2022
國家/地區Japan
城市Virtual, Online
期間22-10-0322-10-06

All Science Journal Classification (ASJC) codes

  • 軟體
  • 人機介面
  • 電腦視覺和模式識別
  • 電腦網路與通信

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