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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ ³í¹®Áö C : ÄÄÇ»ÆÃÀÇ ½ÇÁ¦

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Current Result Document : 5 / 9 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) ±³ÅëÆÐÅÏ ÇнÀ±â¹Ý ¹Ýº¹Àû ±³ÅëÈ¥ÀâÀ» °í·ÁÇÑ ±³Â÷·Î ½ÅÈ£ Á¦¾î
¿µ¹®Á¦¸ñ(English Title) Intersection Traffic Signal Control based on Traffic Pattern Learning for Repetitive Traffic Congestion
ÀúÀÚ(Author) Á¶¿µÅ   ÃÖÁø¼·   Á¤Àιü   YoungTae Jo   JinSup Choi   InBum Jung  
¿ø¹®¼ö·Ïó(Citation) VOL 20 NO. 08 PP. 0450 ~ 0465 (2014. 08)
Çѱ۳»¿ë
(Korean Abstract)
±³Åë ÀÎÇÁ¶óÀÇ È¿À²Àû »ç¿ëÀ» À§ÇÑ Áö´ÉÇü ±³Åë½Ã½ºÅÛÀÌ ÃÖ±Ù ¸¹ÀÌ ¿¬±¸µÇ°í ÀÖ´Ù. ±³Â÷·Î ½ÅÈ£Á¦¾î ¿ª½Ã ±³Åë½Ã½ºÅÛÀÇ ¹ßÀü¿¡ ÈûÀÔ¾î ±âÁ¸ÀÇ °íÁ¤Çü ½ÅÈ£Á¦¾î¹æ½ÄÀ» ¹þ¾î³ª ½Ç½Ã°£ ±³Åë È帧¿¡ µû¶ó ´Éµ¿ÀûÀ¸·Î º¯È­ÇÏ´Â ½ÅÈ£Á¦¾î¹æ½ÄÀ¸·Î º¯È­ÇÏ°í ÀÖ´Ù. º» ³í¹®¿¡¼­´Â µµ½É±³Åë¿¡¼­ ±³Åë ¾ÈÁ¤¼º °¨¼Ò³ª ¿À¿° Áõ°¡ °°Àº Áß¿ä ¹®Á¦µéÀ» ÀÏÀ¸Å°´Â ¹Ýº¹Àû ±³ÅëÈ¥ÀâÀ» °í·ÁÇÑ ±³Åë ½ÅÈ£Á¦¾î ¾Ë°í¸®ÁòÀ» ¼Ò°³ÇÑ´Ù. Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀº ¹Ýº¹Àû ±³ÅëÈ¥ÀâÇÏ¿¡¼­µµ ½É ±³Â÷·ÎÀÇ Æò±Õ Áö¿¬°¨¼Ò¿Í ±³Åë·® Áõ°¡¸¦ ¸ñÇ¥·Î ÇÑ´Ù. ±âÁ¸ ±³ÅëÁ¤º¸¸¦ ±â¹ÝÀ¸·Î ÇнÀµÈ ±³ÅëÆÐÅÏÀ» ÅëÇØ ÇâÈÄ ¹ß»ý °¡´ÉÇÑ ±³ÅëÈ¥ÀâÀ» ¿¹ÃøÇÑ´Ù. Á¤È®ÇÑ ¿¹ÃøÀ» À§ÇØ º» ³í¹®¿¡¼­´Â »ó°ü°è¼ö¸¦ È°¿ëÇÑ´Ù. Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀÇ ½Ç¿ë¼ºÀ» ³ôÀ̱â À§ÇÏ¿© ÇöÀç ½ÇÁ¦µµ·Î¿¡¼­ °¡Àå ¸¹ÀÌ »ç¿ëµÇ°í ÀÖ´Â Actuated controlÀ» ±â¹ÝÀ¸·Î ¼³°èÇÑ´Ù. Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀº VISSIM ¸¶ÀÌÅ©·Î½ºÄÚÇÈ ½Ã¹Ä·¹ÀÌÅ͸¦ ÅëÇØ Æò°¡µÇ¾ú°í Æò°¡ °á°ú¸¦ ÅëÇØ ÁÖ±âÀû ±³ÅëÈ¥Àâ¿¡¼­ ±³Åë È帧 °³¼±À» È®ÀÎÇÏ¿´´Ù.
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(English Abstract)
Recently, intelligent transportation system (ITS) has been studied for efficient use of road infrastructure. With the advance of transportation systems, traffic signal control methods have been improved from conventional pre-timed signal controls to active strategies that dynamically schedule the traffic signal based on real-time traffic flow. This paper introduces a novel algorithm to minimize average delay and improve throughput for the repetitive traffic congestion that is a critical problem at urban intersections, leading to various problems such as safety reduction, increase of pollution, and so on. In our algorithm, future traffic congestion is estimated using traffic pattern learning based on historical traffic information. We use adjusted correlation coefficient for accurate congestion estimation with previously learned traffic data. To improve the utility of our algorithm, the actuated control is included which has been used widely in real field. In our experiments, the microscopic traffic simulator VISSIM performed our modeling works. The results show that the proposed algorithm has good effect to the intersections struggling with repetitive traffic congestion problems.
Å°¿öµå(Keyword) ±³ÅëÆÐÅÏÇнÀ   ´ÙÁß±³Â÷·Î   ±³Â÷·Î½ÅÈ£Á¦¾î   ¹Ýº¹Àû±³ÅëÈ¥Àâ   traffic pattern learning   multiple intersections   traffic signal control   repetitive traffic congest  
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