발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.3] Method for Threat and Priority Decision of Smart Vehicles Using AI Algorithm |
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| 논문투고자 |
Wantae Kim |
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| 논문내용 |
Recently, there has been extensive research and development in the field of smart cars, including technologies related to autonomous driving. Especially, to achieve autonomous driving, it is necessary to ensure safety through technology that can detect surrounding vehicles and respond to dangerous situations while driving. Furthermore, safety systems focused on drivers must be advanced to achieve autonomous driving. Various industries are actively working towards creating efficient and safe self-driving cars. Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. One of the representative technologies being researched is the use of Frequency Modulated Continuous Wave (FMCW) radar. Automobile manufacturers are improving driving safety by equipping cars with Blind Spot Detection (BSD) radar systems that use FMCW technology. As the complexity of driving environments continues to grow, ongoing research is aimed at enhancing the accuracy and reliability of BSD radar technology for detecting blind spots in vehicles. BSD radar technology distributes the same time to all target vehicles to detect the target, so there is a problem of failing target tracking due to the specific situation of the target vehicle. To solve the problem, we propose a technology that can secure high accuracy by applying the Fuzzy algorithm and determining the threat and priority of the target, and designing systems with different tracking times. |
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