International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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A Vehicle Recognition Method based on Radar and Camera Fusion in an Autonomous Driving Environment

  • Received : 2021.12.05
  • Accepted : 2021.12.09
  • Published : 2021.12.31
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Abstract

At a time when securing driving safety is the most important in the development and commercialization of autonomous vehicles, AI and big data-based algorithms are being studied to enhance and optimize the recognition and detection performance of various static and dynamic vehicles. However, there are many research cases to recognize it as the same vehicle by utilizing the unique advantages of radar and cameras, but they do not use deep learning image processing technology or detect only short distances as the same target due to radar performance problems. Radars can recognize vehicles without errors in situations such as night and fog, but it is not accurate even if the type of object is determined through RCS values, so accurate classification of the object through images such as cameras is required. Therefore, we propose a fusion-based vehicle recognition method that configures data sets that can be collected by radar device and camera device, calculates errors in the data sets, and recognizes them as the same target.

Keywords

Acknowledgement

This work was supported by Korea Institute of Police Technology (KIPoT) grant funded by the Korea government (KNPA) (No.202100200201, Development of Advanced Technology for Perception Improvement on Traffic Entities and Risk Mitigation on Adverse Driving Conditions for Lv.4 Connected Autonomous Driving)

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