ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå ºÐ¼®°ú ¿¹Ãø(-2034³â) : À¯Çü, Á¦Ç°, ±â¼ú, ÄÄÆ÷³ÍÆ®, ¿ëµµ, ±â´É, ¼³Ä¡ À¯Çü, ¹èÆ÷, ÃÖÁ¾»ç¿ëÀÚ, ´Ü°è
AI In Autonomous Vehicle Sensors Market Analysis and Forecast to 2034: Type, Product, Technology, Component, Application, Functionality, Installation Type, Deployment, End User, Stage
»óǰÄÚµå : 1699171
¸®¼­Ä¡»ç : Global Insight Services LLC
¹ßÇàÀÏ : 2025³â 04¿ù
ÆäÀÌÁö Á¤º¸ : ¿µ¹® 420 Pages
 ¶óÀ̼±½º & °¡°Ý (ºÎ°¡¼¼ º°µµ)
US $ 4,750 £Ü 6,872,000
Single User License help
PDF º¸°í¼­¸¦ 1¸í¸¸ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. ÅØ½ºÆ®ÀÇ Copy & Paste °¡´ÉÇϸç, Àμâ´Â °¡´ÉÇÕ´Ï´Ù.
US $ 5,750 £Ü 8,319,000
Site License help
PDF, Excel º¸°í¼­¸¦ µ¿ÀÏ ±â¾÷(±¹°¡)ÀÇ ¸ðµç ºÐÀÌ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. ÅØ½ºÆ®ÀÇ Copy & Paste °¡´ÉÇÕ´Ï´Ù. Àμ⠰¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.
US $ 6,750 £Ü 9,766,000
Enterprise License help
PDF, Excel º¸°í¼­¸¦ µ¿ÀÏ ±â¾÷ÀÇ Àü ¼¼°è ¸ðµçºÐÀÌ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. ÅØ½ºÆ®ÀÇ Copy & Paste °¡´ÉÇÕ´Ï´Ù. Àμ⠰¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.


Çѱ۸ñÂ÷

ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀåÀº 2024³â 52¾ï ´Þ·¯¿¡¼­ 2034³â¿¡´Â 258¾ï ´Þ·¯·Î È®´ëÇϸç, ¾à 17.4%ÀÇ CAGR·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀÌ ½ÃÀå¿¡´Â Â÷·®ÀÇ ÀÚÀ²¼ºÀ» ³ôÀ̱â À§ÇØ ÀΰøÁö´É°ú ¼¾¼­¸¦ ÅëÇÕÇÏ´Â ±â¼úÀÌ Æ÷ÇԵ˴ϴÙ. ÀÌ ½ÃÀå¿¡´Â LiDAR, ·¹ÀÌ´õ, Ä«¸Þ¶ó, ÃÊÀ½ÆÄ ¼¾¼­°¡ Æ÷ÇԵǸç, ¸ðµÎ AI¸¦ Ȱ¿ëÇÏ¿© ÀνÄ, ÀÇ»ç°áÁ¤, Ž»öÀ» °³¼±ÇÕ´Ï´Ù. ÀÚÀ²ÁÖÇàÂ÷ ¼ö¿ä°¡ Áõ°¡ÇÔ¿¡ µû¶ó AI¸¦ Ȱ¿ëÇÑ ¼¾¼­ À¶ÇÕ, ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸®, ¾ÈÀü °­È­¿¡ ´ëÇÑ Çõ½ÅÀº ¸Å¿ì Áß¿äÇÕ´Ï´Ù. ½ÃÀå ¼ºÀåÀº ¸Ó½Å·¯´× ¾Ë°í¸®ÁòÀÇ ¹ßÀü°ú º¸´Ù ¾ÈÀüÇϰí È¿À²ÀûÀÎ ¿î¼Û ¼Ö·ç¼Ç¿¡ ´ëÇÑ °ü½ÉÀÌ ³ô¾ÆÁü¿¡ ÀÇÇØ ÃËÁøµÇ°í ÀÖ½À´Ï´Ù.

½ÃÀå °³¿ä

ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀåÀº LiDAR, ·¹ÀÌ´õ, Ä«¸Þ¶ó, ÃÊÀ½ÆÄ ¼¾¼­·Î ±¸ºÐµÇ¸ç, LiDAR ºÎ¹®Àº ÁÖ·Î ³»ºñ°ÔÀ̼ǰú Àå¾Ö¹° °¨Áö¿¡ ÇʼöÀûÀÎ °íÇØ»óµµ 3D ¸ÅÇÎÀ» Á¦°øÇÏ´Â ±â¼úÀû ¿ìÀ§¸¦ ¹ÙÅÁÀ¸·Î ÁÖ¿ä ºÎ¹®À¸·Î ºÎ»óÇϰí ÀÖ½À´Ï´Ù. Á¤È®ÇÑ È¯°æ ÀνĿ¡ ´ëÇÑ ¼ö¿ä Áõ°¡¿Í ¾ÈÀü ±â´É °­È­¿¡ Áß¿äÇÑ ¿ªÇÒÀ» Çϱ⠶§¹®ÀÔ´Ï´Ù. ·¹ÀÌ´õ ¼¾¼­´Â ¾ÇõÈÄ¿¡¼­µµ °ß°íÇÑ ¼º´ÉÀ» ¹ßÈÖÇÏ¿© LiDARÀÇ ´É·ÂÀ» º¸¿ÏÇϰí ÀÖ½À´Ï´Ù. ¼Ö¸®µå ½ºÅ×ÀÌÆ® LiDAR ¹× 4D À̹Ì¡ ·¹ÀÌ´õ¿Í °°Àº »õ·Î¿î ÇÏÀ§ ºÎ¹®Àº ºñ¿ë Àý°¨°ú ¼º´É Çâ»óÀ» ¾à¼ÓÇϸç Àα⸦ ¾ò°í ÀÖ½À´Ï´Ù. Ä«¸Þ¶ó ºÎ¹® ¿ª½Ã AI ±â¹Ý À̹ÌÁö ÀÎ½Ä ±â¼úÀ» ÅëÇØ ¹°Ã¼ °¨Áö ¹× ºÐ·ù¸¦ °­È­ÇÏ´Â µî ±â¼ú Çõ½ÅÀÌ ÀÌ·ç¾îÁö°í ÀÖ½À´Ï´Ù. ¿©·¯ ¼¾¼­ÀÇ µ¥ÀÌÅ͸¦ ÅëÇÕÇÏ´Â ¼¾¼­ À¶ÇÕ ±â¼ú¿¡¼­ AIÀÇ ÅëÇÕ È®´ë´Â ÀÇ»ç°áÁ¤ ÇÁ·Î¼¼½º¸¦ °³¼±ÇÏ°í º¸´Ù Áøº¸µÈ ÀÚÀ²ÁÖÇà ±â´ÉÀ» °¡´ÉÇÏ°Ô ÇÔÀ¸·Î½á ½ÃÀå¿¡ Å« ¿µÇâÀ» ¹ÌÄ¥ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

½ÃÀå ¼¼ºÐÈ­
À¯Çü ¶óÀÌ´Ù ¼¾¼­, ·¹ÀÌ´õ ¼¾¼­, ÃÊÀ½ÆÄ ¼¾¼­, Ä«¸Þ¶ó ¼¾¼­, Àû¿Ü¼± ¼¾¼­, Àû¿Ü¼± ¼¾¼­
Á¦Ç°¼Ò°³ ÅëÇÕ ¼¾¼­ ½Ã½ºÅÛ,µ¶¸³Çü ¼¾¼­ À¯´Ö,¼¾¼­ Ç»Àü ½Ã½ºÅÛ
±â¼ú ¸Ó½Å·¯´×, µö·¯´×, ÄÄÇ»ÅÍ ºñÀü, ¼¾¼­ À¶ÇÕ, ¸Ó½Å·¯´×, µö·¯´×, ÄÄÇ»ÅÍ ºñÀü
±¸¼º ¿ä¼Ò ÇÁ·Î¼¼¼­, ¸Þ¸ð¸® À¯´Ö, Åë½Å ¸ðµâ, Àü¿ø °ø±Þ Àåºñ ½Ã½ºÅÛ
Àû¿ë ºÐ¾ß ½Â¿ëÂ÷, »ó¿ëÂ÷, ½ÂÂ÷°øÀ¯ ¼­ºñ½º, ¹°·ù-¹è¼Û, ¹°·ù-¹è¼Û
±â´É Áö°¢, À§Ä¡, ¸ÅÇÎ, Á¦¾î, ÀÇ»ç°áÁ¤, ÀÇ»ç°áÁ¤
¼³Ä¡ À¯Çü OEM ¼³Ä¡, ¾ÖÇÁÅ͸¶ÄÏ ¼³Ä¡
Àü°³ Ŭ¶ó¿ìµå ±â¹Ý, ¿¡Áö ±â¹Ý, ÇÏÀ̺긮µå
ÃÖÁ¾»ç¿ëÀÚ ÀÚµ¿Â÷ Á¦Á¶¾÷ü, ±â¼ú ÇÁ·Î¹ÙÀÌ´õ, ¶óÀ̵å¼Î¾î¸µ ±â¾÷, ¹°·ù ±â¾÷
´Ü°è ¿¬±¸°³¹ß, Å×½ºÆ® ¹× °ËÁõ, »ý»ê, »ó¾÷Àû Ãâ½Ã

ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­ÀÇ AI ½ÃÀåÀº ADAS(÷´Ü¿îÀüÀÚÁö¿ø½Ã½ºÅÛ)¿Í ¿ÏÀüÀÚÀ²ÁÖÇàÂ÷¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡°¡ ÁÖ¿ä ¿äÀÎÀ¸·Î ÀÛ¿ëÇϰí ÀÖ½À´Ï´Ù. ¶óÀÌ´õ, ·¹ÀÌ´õ, Ä«¸Þ¶ó ¼¾¼­°¡ ÀÌ ½ÃÀåÀÇ ÃÖÀü¼±¿¡ ÀÖÀ¸¸ç, °¢°¢ÀÌ Àüü»ó¿¡ Å©°Ô ±â¿©Çϰí ÀÖ½À´Ï´Ù. ÀÚµ¿Â÷ ¾ÈÀü¿¡ ´ëÇÑ °ü½ÉÀÌ ³ô¾ÆÁö°í ±³Åë»ç°í °¨¼Ò°¡ ÃßÁøµÇ°í ÀÖ´Â °ÍÀÌ ½ÃÀå ¿ªÇп¡ ¿µÇâÀ» ¹ÌÄ¡´Â ÁÖ¿ä ¿äÀÎÀ¸·Î ÀÛ¿ëÇϰí ÀÖ½À´Ï´Ù. ºÏ¹Ì´Â ±â¼ú ¹ßÀü°ú Á¶±â µµÀÔÀ¸·Î ÀÎÇØ ÇöÀç ½ÃÀåÀ» µ¶Á¡Çϰí ÀÖÁö¸¸, À¯·´°ú ¾Æ½Ã¾ÆÅÂÆò¾çÀº Àü·«Àû ÅõÀÚ¿Í Á¤ºÎ ±¸»ó¿¡ ÈûÀÔ¾î Å« ÆøÀÇ ¼ºÀåÀ» º¸À̰í ÀÖ½À´Ï´Ù. °æÀï ȯ°æÀº Bosch, Continental, Velodyne°ú °°Àº ´ë±â¾÷ÀÇ Á¸Àç°¡ Ư¡À̸ç, ÀÌµé ±â¾÷Àº ¼¾¼­ÀÇ ±â´ÉÀ» °­È­ÇÏ°í ºñ¿ëÀ» Àý°¨Çϱâ À§ÇØ ¿¬±¸°³¹ß¿¡ Àû±ØÀûÀ¸·Î ÅõÀÚÇϰí ÀÖ½À´Ï´Ù. ¾ö°ÝÇÑ ¾ÈÀü ±âÁØÀ» °¡Áø À¯·´°ú °°Àº Áö¿ªÀÇ ±ÔÁ¦ ÇÁ·¹ÀÓ¿öÅ©´Â ½ÃÀå ±Ëµµ¸¦ Çü¼ºÇÏ´Â µ¥ ¸Å¿ì Áß¿äÇÕ´Ï´Ù. ÇâÈÄ AI¸¦ Ȱ¿ëÇÑ ºÐ¼® ±â¼úÀÇ ÅëÇÕ°ú º¸´Ù Áøº¸µÈ ¼¾¼­ ±â¼úÀÇ °³¹ß·Î ½ÃÀåÀÌ È®´ëµÉ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ³ôÀº °³¹ß ºñ¿ë°ú ±ÔÁ¦ ´ëÀÀÀ̶ó´Â °úÁ¦´Â ÀÖÁö¸¸, AI¿Í ¸Ó½Å·¯´×ÀÇ ¹ßÀüÀº Çõ½Å°ú ¼ºÀåÀÇ Å« ±âȸ¸¦ °¡Á®´ÙÁÖ°í ÀÖ½À´Ï´Ù.

ÁÖ¿ä µ¿Çâ ¹× ÃËÁø¿äÀÎ

ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­ÀÇ AI ½ÃÀåÀº ±â¼ú ¹ßÀü°ú ¼ÒºñÀÚ ±â´ëÄ¡ÀÇ ÁøÈ­¿¡ µû¶ó °­·ÂÇÑ ¼ºÀåÀ» º¸À̰í ÀÖ½À´Ï´Ù. ÁÖ¿ä µ¿Çâ¿¡´Â ¼¾¼­ÀÇ Á¤È®¼º°ú ÀÇ»ç°áÁ¤ ´É·ÂÀ» Çâ»ó½Ã۱â À§ÇÑ ¸Ó½Å·¯´× ¾Ë°í¸®ÁòÀÇ ÅëÇÕÀÌ Æ÷ÇԵ˴ϴÙ. ÀÌ·¯ÇÑ Ãß¼¼´Â Â÷·®ÀÌ º¹ÀâÇÑ µ¥ÀÌÅ͸¦ ½Ç½Ã°£À¸·Î ó¸®ÇÏ°í ¾ÈÀü°ú È¿À²¼ºÀ» Çâ»ó½Ãų ¼ö ÀÖÀ¸¹Ç·Î ¸Å¿ì Áß¿äÇÕ´Ï´Ù. ¶Ç ´Ù¸¥ Áß¿äÇÑ µ¿ÇâÀº ºñ¿ë È¿À²ÀûÀÎ °í¼º´É LiDAR ½Ã½ºÅÛÀÇ °³¹ßÀÔ´Ï´Ù. ÀÌ·¯ÇÑ ½Ã½ºÅÛÀº º¸´Ù ½±°Ô »ç¿ëÇÒ ¼ö ÀÖ°Ô µÇ¾î ¹Î°£ ¹× »ó¾÷¿ë ÀÚÀ²ÁÖÇà Â÷·® ¸ðµÎ¿¡ ³Î¸® äÅÃµÉ ¼ö ÀÖ´Â ±æÀ» ¿­¾îÁÖ°í ÀÖ½À´Ï´Ù. ¶ÇÇÑ ÀÚµ¿Â÷ Á¦Á¶¾÷ü¿Í ÇÏÀÌÅ×Å© ±â¾÷ °£ÀÇ Çù¾÷Àº ±â¼ú Çõ½ÅÀ» °¡¼ÓÈ­ÇÏ¿© ´õ¿í Á¤±³ÇÑ ¼¾¼­ ¼Ö·ç¼ÇÀ¸·Î À̾îÁö°í ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ½ÃÀå ¼ºÀå ÃËÁø¿äÀο¡´Â °­È­µÈ ¾ÈÀü ±â´É¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡¿Í ¿ÏÀü ÀÚÀ²ÁÖÇàÀ» ÇâÇÑ ÃßÁø·ÂÀÌ Æ÷ÇԵ˴ϴÙ. °¢±¹ Á¤ºÎ´Â ÷´Ü¿îÀüÀÚº¸Á¶½Ã½ºÅÛ(ADAS)ÀÇ »ç¿ëÀ» ÃËÁøÇÏ´Â ±ÔÁ¦¸¦ ½ÃÇàÇÔÀ¸·Î½á ¸Å¿ì Áß¿äÇÑ ¿ªÇÒÀ» Çϰí ÀÖ½À´Ï´Ù. ÀÎÇÁ¶ó ±¸ÃàÀÌ ÀÚÀ²ÁÖÇà ±â¼ú µµÀÔÀ» ÃËÁøÇÏ´Â ½ÅÈï ±¹°¡ ½ÃÀå¿¡´Â ¸¹Àº ±âȸ°¡ ÀÖ½À´Ï´Ù. Çõ½ÅÀûÀ̰í È®Àå °¡´ÉÇÑ ¼Ö·ç¼ÇÀ» Á¦°øÇÏ´Â ±â¾÷Àº ÀÌ·¯ÇÑ ±âȸ¸¦ Ȱ¿ëÇÒ ¼ö ÀÖ´Â À¯¸®ÇÑ À§Ä¡¿¡ ÀÖ½À´Ï´Ù. ź¼Ò ¹èÃâ·® °¨¼Ò¿Í ±³Åë °ü¸® °³¼±¿¡ ÁßÁ¡À» µÎ°í ÀÖ´Â °ÍÀº ½ÃÀåÀ» ´õ¿í ÃËÁøÇϰí Áö¼ÓÀûÀÎ ¼ºÀå°ú °³¹ßÀ» º¸ÀåÇϰí ÀÖ½À´Ï´Ù.

¾ïÁ¦¿Í °úÁ¦

ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­ÀÇ AI ½ÃÀåÀº ¸î °¡Áö Áß¿äÇÑ ¾ïÁ¦¿äÀΰú °úÁ¦¿¡ Á÷¸éÇØ ÀÖ½À´Ï´Ù. ù°, ¼¾¼­ ±â¼úÀÇ ³ôÀº ºñ¿ëÀº ƯÈ÷ ¼Ò±Ô¸ð Á¦Á¶¾÷ü¿Í ½ÅÈï ½ÃÀå¿¡¼­´Â ¿©ÀüÈ÷ Å« À庮À¸·Î ÀÛ¿ëÇϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ °æÁ¦Àû ºÎ´ãÀº º¸±Þ°ú Çõ½ÅÀ» Á¦ÇÑÇÕ´Ï´Ù. µÑ°, ±âÁ¸ Â÷·® ½Ã½ºÅÛ¿¡ AI¸¦ ÅëÇÕÇÏ´Â º¹À⼺Àº Àü¹® Áö½ÄÀ» ÇÊ¿ä·Î ÇÏ´Â ±â¼úÀû °úÁ¦¸¦ Á¦½ÃÇÏÁö¸¸, ÀÌ·¯ÇÑ Àü¹® Áö½ÄÀÌ Ç×»ó ½±°Ô ±¸ÇÒ ¼ö ÀÖ´Â °ÍÀº ¾Æ´Õ´Ï´Ù. ¼Â°, ±ÔÁ¦¿Í ¾ÈÀü¿¡ ´ëÇÑ ¿ì·Á°¡ Å« Àå¾Ö¹°ÀÌ µÉ ¼ö ÀÖÀ¸¸ç, ¾ö°ÝÇÑ ±ÔÁ¤ Áؼö ¿ä°ÇÀÌ Á¦Ç° °³¹ß ¹× ½ÃÀå °³¹ßÀ» Áö¿¬½Ãų ¼ö ÀÖ½À´Ï´Ù. ³Ý°, AI ±â¼úÀÇ ±Þ¼ÓÇÑ ¹ßÀüÀº ÇöÀçÀÇ ½Ã½ºÅÛÀ» ³ëÈÄÈ­½ÃÄÑ ÅõÀÚÀڵ鿡°Ô ºÒÈ®½Ç¼º°ú À§ÇèÀ» ÃÊ·¡ÇÒ ¼ö ÀÖ´Ù´Â °ÍÀ» ÀǹÌÇÕ´Ï´Ù. ¸¶Áö¸·À¸·Î ÀÚÀ²ÁÖÇàÂ÷°¡ »ý¼ºÇÏ´Â ¹æ´ëÇÑ µ¥ÀÌÅÍ´Â Ä§ÇØ¿Í ¾Ç¿ëÀ» ¹æÁöÇϱâ À§ÇØ °­·ÂÇÑ º¸È£ Á¶Ä¡°¡ ÇÊ¿äÇϹǷΠµ¥ÀÌÅÍ ÇÁ¶óÀ̹ö½Ã ¹× º¸¾È ¹®Á¦°¡ Å©°Ô ´ëµÎµÇ°í ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ¹®Á¦µéÀº ÃÑüÀûÀ¸·Î ½ÃÀå ¼ºÀåÀ» ÀúÇØÇϰí, Àü·«ÀûÀ¸·Î ÇØ°áÇØ¾ß ÇÒ Àå¾Ö¹°ÀÌ µÇ°í ÀÖ½À´Ï´Ù.

¸ñÂ÷

Á¦1Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå °³¿ä

Á¦2Àå °³¿ä

Á¦3Àå ½ÃÀå¿¡ °üÇÑ ÁÖ¿ä ÀλçÀÌÆ®

Á¦4Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå Àü¸Á

Á¦5Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå Àü·«

Á¦6Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå ±Ô¸ð

Á¦7Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå ±Ô¸ð : À¯Çüº°

Á¦8Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : Á¦Ç°º°

Á¦9Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : ±â¼úº°

Á¦10Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : ÄÄÆ÷³ÍÆ®º°

Á¦11Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : ¿ëµµº°

Á¦12Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : ±â´Éº°

Á¦13Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : ¼³Ä¡ À¯Çüº°

Á¦14Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : ¹èÆ÷º°

Á¦15Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : ÃÖÁ¾»ç¿ëÀÚº°

Á¦16Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : ´Ü°èº°

Á¦17Àå ÀÚÀ²ÁÖÇàÂ÷ ¼¾¼­¿ë AI ½ÃÀå : Áö¿ªº°

Á¦18Àå °æÀï ±¸µµ

Á¦19Àå ±â¾÷ °³¿ä

KSA
¿µ¹® ¸ñÂ÷

¿µ¹®¸ñÂ÷

AI In Autonomous Vehicle Sensors Market is anticipated to expand from $5.2 billion in 2024 to $25.8 billion by 2034, growing at a CAGR of approximately 17.4%. The market encompasses technologies integrating artificial intelligence with sensors to enhance vehicle autonomy. This market includes LiDAR, radar, cameras, and ultrasonic sensors, all leveraging AI for improved perception, decision-making, and navigation. As demand for autonomous vehicles rises, innovations in AI-driven sensor fusion, real-time data processing, and safety enhancements are pivotal. The market's growth is fueled by advancements in machine learning algorithms and the increasing push towards safer, more efficient transportation solutions.

Market Overview:

The AI in Autonomous Vehicle Sensors Market is segmented into LiDAR, radar, camera, and ultrasonic sensors. The LiDAR segment emerges as the leading segment, primarily due to its technological superiority in providing high-resolution 3D mapping, which is crucial for navigation and obstacle detection. LiDAR's dominance is driven by increasing demand for precise environmental perception and its critical role in enhancing safety features. Radar sensors follow closely, offering robust performance in adverse weather conditions, thereby supplementing LiDAR's capabilities. Emerging sub-segments such as solid-state LiDAR and 4D imaging radar are gaining traction, promising reduced costs and improved performance. The camera segment is also witnessing innovation, with AI-driven image recognition technologies enhancing object detection and classification. The growing integration of AI in sensor fusion technologies, which combines data from multiple sensors, is expected to significantly impact the market by improving decision-making processes and enabling more sophisticated autonomous driving functionalities.

Market Segmentation
TypeLidar Sensors, Radar Sensors, Ultrasonic Sensors, Camera Sensors, Infrared Sensors
ProductIntegrated Sensor Systems, Standalone Sensor Units, Sensor Fusion Systems
TechnologyMachine Learning, Deep Learning, Computer Vision, Sensor Fusion
ComponentProcessors, Memory Units, Communication Modules, Power Supply Systems
ApplicationPassenger Vehicles, Commercial Vehicles, Ride-sharing Services, Logistics and Delivery
FunctionalityPerception, Localization, Mapping, Control, Decision Making
Installation TypeOEM Installation, Aftermarket Installation
DeploymentCloud-based, Edge-based, Hybrid
End UserAutomotive Manufacturers, Technology Providers, Ride-sharing Companies, Logistics Firms
StageResearch and Development, Testing and Validation, Production, Commercial Deployment

The AI in Autonomous Vehicle Sensors market is predominantly driven by the increasing demand for advanced driver-assistance systems (ADAS) and fully autonomous vehicles. Lidar, radar, and camera sensors are at the forefront of this market, each contributing significantly to the overall landscape. The growing emphasis on vehicle safety and the push towards reducing road accidents are key factors influencing market dynamics. North America currently dominates the market, largely due to technological advancements and early adoption, while Europe and Asia-Pacific are witnessing substantial growth fueled by strategic investments and government initiatives. The competitive landscape is characterized by the presence of major players like Bosch, Continental, and Velodyne, who are actively investing in R&D to enhance sensor capabilities and reduce costs. Regulatory frameworks in regions such as Europe, with its stringent safety standards, are pivotal in shaping the market trajectory. Looking ahead, the market is set to expand with the integration of AI-driven analytics and the development of more sophisticated sensor technologies. Despite challenges such as high development costs and regulatory compliance, the ongoing advancements in AI and machine learning present significant opportunities for innovation and growth.

Geographical Overview:

The AI in autonomous vehicle sensors market is witnessing a diverse growth trajectory across regions, each exhibiting unique characteristics. North America stands at the forefront, propelled by technological innovation and substantial investments in autonomous driving technologies. The region's robust automotive industry and supportive regulatory environment further catalyze market expansion. Europe follows with a strong emphasis on sustainability and safety, driving advancements in AI sensor technologies. The region's automotive giants and research institutions are at the helm, fostering a conducive environment for market growth. Regulatory frameworks promoting autonomous vehicles also enhance the market landscape. In Asia Pacific, rapid urbanization and technological proliferation are key drivers of market growth. Countries like China and Japan are investing heavily in AI and autonomous vehicle technologies, supported by government initiatives. The region's automotive production capabilities further bolster market prospects. Latin America and the Middle East & Africa are emerging markets, gradually recognizing the potential of AI in autonomous vehicle sensors. Latin America is experiencing increased investments in automotive innovation, while the Middle East & Africa are exploring AI applications to enhance mobility and economic development.

Recent Developments:

The AI in autonomous vehicle sensors market has experienced noteworthy developments in recent months. Waymo, a subsidiary of Alphabet, announced a strategic partnership with Luminar to integrate advanced lidar sensors in its autonomous fleet, enhancing vehicle perception capabilities. In a significant merger and acquisition move, Mobileye acquired AI startup Moovit, aiming to bolster its autonomous vehicle sensor technology with advanced AI algorithms. Bosch unveiled a new suite of AI-driven sensors designed to improve the safety and efficiency of autonomous vehicles, focusing on enhanced object recognition and real-time data processing. In regulatory news, the European Union introduced new guidelines to standardize AI applications in autonomous vehicle sensors, emphasizing safety and interoperability across member states. Additionally, NVIDIA launched a groundbreaking AI platform, Drive Thor, designed to support next-generation autonomous vehicles with improved sensor fusion and decision-making capabilities. These developments underscore the rapid evolution and strategic investments in AI technologies for autonomous vehicle sensors, highlighting a promising trajectory for market growth.

Key Trends and Drivers:

The AI in autonomous vehicle sensors market is experiencing robust growth driven by technological advancements and evolving consumer expectations. Key trends include the integration of machine learning algorithms to enhance sensor accuracy and decision-making capabilities. This trend is crucial as it enables vehicles to process complex data in real-time, improving safety and efficiency. Another significant trend is the development of cost-effective, high-performance LiDAR systems. These systems are becoming more accessible, paving the way for widespread adoption in both consumer and commercial autonomous vehicles. Furthermore, the collaboration between automotive manufacturers and tech companies is accelerating innovation, leading to more sophisticated sensor solutions. Drivers of this market include the increasing demand for enhanced safety features and the push towards fully autonomous driving. Governments are also playing a pivotal role by implementing regulations that promote the use of advanced driver-assistance systems. Opportunities abound in emerging markets, where infrastructure development supports the adoption of autonomous technologies. Companies that provide innovative, scalable solutions are well-positioned to capitalize on these opportunities. The focus on reducing carbon emissions and improving traffic management further propels the market, ensuring sustained growth and development.

Restraints and Challenges:

The AI in Autonomous Vehicle Sensors Market is confronted with several significant restraints and challenges. Firstly, the high cost of sensor technology remains a formidable barrier, particularly for smaller manufacturers and emerging markets. This financial burden limits widespread adoption and innovation. Secondly, the complexity of integrating AI with existing vehicle systems presents technical challenges that require specialized expertise, which is not always readily available. Thirdly, regulatory and safety concerns pose substantial hurdles, as stringent compliance requirements can delay product development and market entry. Fourthly, the evolving nature of AI technology means that rapid advancements can render current systems obsolete, creating uncertainty and risk for investors. Lastly, data privacy and security issues loom large, as the vast amount of data generated by autonomous vehicles necessitates robust protection measures to prevent breaches and misuse. These challenges collectively impede the market's growth and present obstacles that must be strategically navigated.

Key Companies:

Innoviz Technologies, Luminar Technologies, Ouster, Velodyne Lidar, Quanergy Systems, Cepton Technologies, Aeva Technologies, Arbe Robotics, Innovusion, LeddarTech, Tetravue, Baraja, Blickfeld, RoboSense, Aeye, Sense Photonics, Ibeo Automotive Systems, Waymo, XenomatiX, TriEye, Opsys Tech, PreAct Technologies, Light Detection and Ranging Technologies, Sensible 4, Aptiv, Momenta, Perceptive Automata, Zvision, Metawave, Hesai Technology, Cohda Wireless, DeepMap, Nauto, Aptonomy, Pony.ai, Voyant Photonics, Bright Way Vision, Xenomatix, Sensata Technologies, Kalray

Sources:

National Highway Traffic Safety Administration (NHTSA), European Commission - Mobility and Transport, International Transport Forum (ITF) at the OECD, U.S. Department of Transportation (DOT), Japan Automobile Research Institute (JARI), Intelligent Transportation Systems Society of Canada (ITS Canada), Society of Automotive Engineers (SAE) International, Institute of Electrical and Electronics Engineers (IEEE) - Intelligent Transportation Systems Society, International Road Transport Union (IRU), World Economic Forum - Future of Mobility, European Union Agency for Cybersecurity (ENISA), United Nations Economic Commission for Europe (UNECE) - Transport Division, Korea Automotive Technology Institute (KATECH), National Renewable Energy Laboratory (NREL), Automotive Research Association of India (ARAI), International Conference on Intelligent Transportation Systems (IEEE ITSC), Automated Vehicles Symposium, International Conference on Robotics and Automation (ICRA), Consumer Electronics Show (CES) - Automotive Section, European Conference on Artificial Intelligence (ECAI)

Research Scope:

Our research scope provides comprehensive market data, insights, and analysis across a variety of critical areas. We cover Local Market Analysis, assessing consumer demographics, purchasing behaviors, and market size within specific regions to identify growth opportunities. Our Local Competition Review offers a detailed evaluation of competitors, including their strengths, weaknesses, and market positioning. We also conduct Local Regulatory Reviews to ensure businesses comply with relevant laws and regulations. Industry Analysis provides an in-depth look at market dynamics, key players, and trends. Additionally, we offer Cross-Segmental Analysis to identify synergies between different market segments, as well as Production-Consumption and Demand-Supply Analysis to optimize supply chain efficiency. Our Import-Export Analysis helps businesses navigate global trade environments by evaluating trade flows and policies. These insights empower clients to make informed strategic decisions, mitigate risks, and capitalize on market opportunities.

TABLE OF CONTENTS

1: AI In Autonomous Vehicle Sensors Market Overview

2: Executive Summary

3: Premium Insights on the Market

4: AI In Autonomous Vehicle Sensors Market Outlook

5: AI In Autonomous Vehicle Sensors Market Strategy

6: AI In Autonomous Vehicle Sensors Market Size

7: AI In Autonomous Vehicle Sensors Market, by Type

8: AI In Autonomous Vehicle Sensors Market, by Product

9: AI In Autonomous Vehicle Sensors Market, by Technology

10: AI In Autonomous Vehicle Sensors Market, by Component

11: AI In Autonomous Vehicle Sensors Market, by Application

12: AI In Autonomous Vehicle Sensors Market, by Functionality

13: AI In Autonomous Vehicle Sensors Market, by Installation Type

14: AI In Autonomous Vehicle Sensors Market, by Deployment

15: AI In Autonomous Vehicle Sensors Market, by End User

16: AI In Autonomous Vehicle Sensors Market, by Stage

17: AI In Autonomous Vehicle Sensors Market, by Region

18: Competitive Landscape

19: Company Profiles

(ÁÖ)±Û·Î¹úÀÎÆ÷¸ÞÀÌ¼Ç 02-2025-2992 kr-info@giikorea.co.kr
¨Ï Copyright Global Information, Inc. All rights reserved.
PC¹öÀü º¸±â