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Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors.
Baek, Minjin; Mun, Jungwi; Kim, Woojoong; Choi, Dongho; Yim, Janghyuk; Lee, Sangsun.
Afiliação
  • Baek M; Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea.
  • Mun J; Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea.
  • Kim W; Department of Automotive Electronics and Control Engineering, Hanyang University, Seoul 04763, Korea.
  • Choi D; Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea.
  • Yim J; Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea.
  • Lee S; Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, Korea.
Sensors (Basel) ; 21(5)2021 Mar 07.
Article em En | MEDLINE | ID: mdl-33799998
ABSTRACT
Driving environment perception for automated vehicles is typically achieved by the use of automotive remote sensors such as radars and cameras. A vehicular wireless communication system can be viewed as a new type of remote sensor that plays a central role in connected and automated vehicles (CAVs), which are capable of sharing information with each other and also with the surrounding infrastructure. In this paper, we present the design and implementation of driving environment perception based on the fusion of vehicular wireless communications and automotive remote sensors. A track-to-track fusion of high-level sensor data and vehicular wireless communication data was performed to accurately and reliably locate the remote target in the vehicle surroundings and predict the future trajectory. The proposed approach was implemented and evaluated in vehicle tests conducted at a proving ground. The experimental results demonstrate that using vehicular wireless communications in conjunction with the on-board sensors enables improved perception of the surrounding vehicle located at varying longitudinal and lateral distances. The results also indicate that vehicle future trajectory and potential crash involvement can be reliably predicted with the proposed system in different cut-in driving scenarios.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article