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Ȩ Ȩ > ¿¬±¸¹®Çå > Çмú´ëȸ ÇÁ·Î½Ãµù > Çѱ¹Á¤º¸Åë½ÅÇÐȸ Çмú´ëȸ > 2019³â Ãß°èÇмú´ëȸ

2019³â Ãß°èÇмú´ëȸ

Current Result Document : 17 / 73 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) ÀθíÇÇÇظ¦ ÃÖ¼ÒÈ­ÇÒ ¼ö ÀÖ´Â Á¦µ¿ ¹æÇâÀüȯ ½Ã½ºÅÛ
¿µ¹®Á¦¸ñ(English Title) Braking Redirection System(BRS) to minimize casualties
ÀúÀÚ(Author) ÃÖÈ£±æ   ±è°æ´ö   À̺´°ü   Ho-gil Choi   Kyung-Deuk Kim   Byung-Kwan Lee  
¿ø¹®¼ö·Ïó(Citation) VOL 23 NO. 02 PP. 0335 ~ 0338 (2019. 10)
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(Korean Abstract)
º» ³í¹®¿¡¼­´Â ÁÖÇà ÁßÀÎ Â÷·®ÀÌ Àü¹æ Â÷·®µéÀÇ ½Â°´ ¹èÄ¡ »óȲÀ» ÆľÇÇÏ°í À§Çè »óȲ¿¡¼­ ÀθíÇÇÇظ¦ ÃÖ¼ÒÈ­ÇÒ ¼ö ÀÖ´Â Á¦µ¿ ¹æÇâÀ» °áÁ¤ÇÏ´Â Braking Redirection System(BRS) to minimize casualties in consideration of the passenger's boarding situation in dangerous situationsÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈÇÏ´Â ½Ã½ºÅÛÀº µÎ °¡Áö ¸ðµâ·Î ±¸¼ºµÈ´Ù. ù°, Passenger Situation Extraction Module(PSEM)Àº Â÷·®¿¡ ž½ÂÇÏ°í ÀÖ´Â ½Â°´ »óȲÀ» ÃßÃâÇÑ´Ù. µÑ°, Front Passenger Extraction Situation Module(FPSEM)Àº Â÷·®¿¡ ÀåÂøµÈ Ä«¸Þ¶ó¿Í CNNÀ» »ç¿ëÇÏ¿© Â÷·® Àü¹æÀÇ À̹ÌÁö¸¦ ºÐ¼®ÇÏ°í, ºÐ¼®ÇÑ °á°ú¸¦ ´Ù¸¥ Â÷·®¿¡ Àü´ÞÇÑ´Ù. BRS´Â PSEM¿¡¼­ ÃßÃâÇÑ ½Â°´ ¹èÄ¡ »óȲ°ú FPSEM¿¡¼­ ÃßÃâÇÑ Àü¹æ ½Â°´ ¹èÄ¡ »óȲÀ» Random Forest·Î ¿¬»êÇÏ¿© À§Çè »óȲ¿¡¼­ ÀθíÇÇÇظ¦ ÃÖ¼ÒÈ­ÇÏ´Â Á¦µ¿ ¹æÇâÀ» °áÁ¤ÇÑ´Ù. Á¦¾ÈµÈ ½Ã½ºÅÛÀº Â÷·® ³»ºÎ¿¡ ü¾Ð ¼¾¼­¸¦ »ç¿ëÇØ ±âÁ¸¿¡ Á¦¾ÈµÈ ½Ã°¢È­ ¼¾¼­¸¦ »ç¿ëÇÑ ½Â°´ ŽÁö ¹æ¹ýº¸´Ù ½Â°´ÀÇ ¹èÄ¡ »óȲÀ» ÀÚ¼¼ÇÏ°Ô ºÐ¼®ÇÏ°í ³ôÀº Á¤È®µµ¸¦ º¸ÀåÇÑ´Ù.
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(English Abstract)
In this paper, the Braking Redirection System (BRS) to minimize the casualties in consideration of the passenger's boarding situation in dangerous situations is proposed. The proposed system consists of two modules. First, the Passenger Situation Extraction Module (PSEM) extracts the passenger situation in the vehicle. Second, the Front Passenger Extraction Situation Module (FPSEM) analyzes the image in front of the vehicle using the camera and CNN installed in the vehicle, and delivers the analysis results to other vehicles. The BRS calculates the braking direction to minimize the casualties in the dangerous situation by calculating the passenger arrangement situation extracted from the PSEM and the front passenger arrangement situation extracted from the FPSEM as Random Forest. The proposed system uses a body pressure sensor inside the vehicle to analyze the passenger's placement in detail and guarantee high accuracy than the passenger detection method using the previously proposed visualization sensor.
Å°¿öµå(Keyword) Autonomous Vehicle   CNN   Random Forset   Deep-Learning   V2V  
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