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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) À̵¿ °´Ã¼ÀÇ ºÎºÐ À¯»ç±ËÀû Ž»öÀ» È°¿ëÇÑ ±³Â÷·Î °ËÃâ ±â¹ý
¿µ¹®Á¦¸ñ(English Title) Detecting Road Intersections using Partially Similar Trajectories of Moving Objects
ÀúÀÚ(Author) ¹Úº¸±¹   ¹ÚÁø°ü   ±èÅ¿렠 Á¶È¯±Ô   Bokuk Park   Jinkwan Park   Taeyong Kim   Hwan-Gue Cho  
¿ø¹®¼ö·Ïó(Citation) VOL 43 NO. 04 PP. 0404 ~ 0410 (2016. 04)
Çѱ۳»¿ë
(Korean Abstract)
´ëºÎºÐÀÇ Â÷·®¿¡¼­ GPS ±â¹ÝÀÇ ³»ºñ°ÔÀ̼ÇÀ» »ç¿ëÇÔ¿¡ µû¶ó, µµ·Î Áöµµ¸¦ ÀÚµ¿ÀûÀ¸·Î »ý¼ºÇÏ´Â °ÍÀº Áß¿äÇÑ ¿¬±¸ ¹®Á¦ÀÌ´Ù. º» ³í¹®¿¡¼­´Â Áöµµ Á¤º¸ ¾øÀÌ GPS ±ËÀûÀ» ÀÌ¿ëÇÑ ±³Â÷·Î °ËÃâ ±â¹ýÀ» Á¦¾ÈÇÑ´Ù. ÀÌ ±â¹ýÀº ±ËÀûÀÌ ±³Â÷·Î¿¡¼­ ¿©·¯ °¥·¡·Î ³ª´©¾îÁö´Â °ÍÀ» ÀÌ¿ëÇÑ´Ù. ÀÌÀüÀÇ ±³Â÷·Î °ËÃâ ¿¬±¸¿¡¼­´Â Á¤Â÷ ºóµµ³ª ȸÀü¹æÇâÀ» ÀÌ¿ëÇÏ¿´´Ù. ±×·¯³ª Á¦¾ÈÇÏ´Â ±³Â÷·Î °ËÃâ ±â¹ýÀº ÀÌ·¯ÇÑ º¹ÀâÇÑ Á¤º¸¸¦ ÀÌ¿ëÇÏÁö ¾Ê´Â´Ù. ÀÌ ±â¹ýÀº ÁÖ¾îÁø ±ËÀû¿¡ ´ëÇÑ ºÎºÐ ±ËÀû ¸ÅĪ °á°ú¸¦ ÀÌ¿ëÇÏ¿© ±³Â÷·Î¿¡ ÁøÀÔÇÑ ±ËÀûµéÀÌ ¼­·Î ´Ù¸¥ µµ·Î·Î ³ª´µ¾î À̵¿ÇÏ´Â °ÍÀ» ÀÌ¿ëÇÑ´Ù. °­³²±¸¿¡¼­ ¼öÁýµÈ ½ÇÁ¦ Â÷·® ±ËÀû 1266°³¸¦ ´ë»óÀ¸·Î ½ÇÇèÇÏ¿´´Ù. ½ÇÇè °á°ú Á¦¾ÈÇÑ ±â¹ýÀº ÀϹÝÀûÀÎ ½ÊÀÚ ¸ð¾çÀÇ ±³Â÷·Î¿¡¼­ ÁÁÀº ¼º´ÉÀ» º¸¿´´Ù. Á¦¾È½Ã½ºÅÛÀº ¼±Á¤ÇÑ ±³Â÷·Î¿¡ ´ëÇØ ÀçÇöÀ² 75%, ¹Î°¨µµ 78%ÀÇ ¼º´ÉÀ» º¸¿´´Ù. ´õ ¸¹Àº ±ËÀûÀ» ÀÌ¿ëÇÏ¸é ´õ ½Å·ÚÇÒ ¼ö ÀÖ´Â °ËÃâ °á°ú¸¦ ³¾ ¼ö ÀÖÀ» °ÍÀ¸·Î ¿¹»óµÈ´Ù.
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(English Abstract)
Automated road map generation poses significant research challenges since GPS-based navigation systems prevail in most general vehicles. This paper proposes an automated detecting method for intersection points using GPS vehicle trajectory data without any background digital map information. The proposed method exploits the fact that the trajectories are generally split into several branches at an intersection point. One problem in previous work on this intersection detecting is that those approaches require stopping points and direction changes for every testing vehicle. However our approach does not require such complex auxiliary information for intersection detecting. Our method is based on partial trajectory matching among trajectories since a set of incoming trajectories split other trajectory cluster branches at the intersection point. We tested our method on a real GPS data set with 1266 vehicles in Gangnam District, Seoul. Our experiment showed that the proposed method works well at some bigger intersection points in Gangnam. Our system scored 75% sensitivity and 78% specificity according to the test data. We believe that more GPS trajectory data would make our system more reliable and applicable in a practice.
Å°¿öµå(Keyword) Áöµµ »ý¼º   GPS ±ËÀû   ±³Â÷·Î °ËÃâ   ±ËÀû À¯»ç¼º   map generation   GPS trajectory   intersection detection   trajectory similarity  
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