| ¼ö·Ï»çÇ× |
µµ½Ã¼³°è(Çѱ¹µµ½Ã¼³°èÇÐȸÁö) , Vol.23 No.4(Åë±Ç Á¦112È£)(2022-08) |
| ÁÖÁ¦¾î |
ÆÛ½º³Î ¸ðºô¸®Æ¼; ÁÖÇà Æ¯¼º; µµ½Ã ¹°¸®Àû ȯ°æ; ½ÇÇè ¿¬±¸ ; Personal Mobility; Driving Characteristics; Urban Physical Environments; Experimental Research |
| ¿ä¾à1 |
º» ¿¬±¸´Â ÃÖ±Ù °³ÀÎ¿ë ´Ü°Å¸® À̵¿¼ö´ÜÀ¸·Î µµ½Ã°ø°£¿¡ ±Þ°ÝÇÏ°Ô µµÀÔ ¹× Ȱ¿ëµÇ°í ÀÖ´Â ÆÛ½º³Î¸ðºô¸®Æ¼ÀÇ µµ½Ã ¹°¸®Àû ȯ°æ¿¡ µû¸¥ ÁÖÇà Æ¯¼ºÀ» ºÐ¼®ÇÏ¿´´Ù.??À̸¦ À§ÇØ,??ÆÛ½º³Î ¸ð´ÏÅ͸µ °ü¼º¼¾¼¿ÍGPS?? ¼Óµµ°è¸¦ Ȱ¿ëÇÏ¿© ÀÚÀü°Å¿Í Àü±âÀÚÀü°Å,?? ±×¸®°í Àüµ¿Å±º¸µå¸¦ ´ë»óÀ¸·Î ½ÇÇèÀÚ°¡ Á÷Á¢ ¿¬±¸ÁÖÇà ½ÇÇèÀ» ½Ç½ÃÇÏ¿´´Ù.??¼¿ï½Ã µ¿´ë¹®±¸ ¿ë½Åµ¿ ÀÏ´ë 1.35km??°æ·Î¸¦ ¼±Á¤ÇÏ¿©,?? 2021³â 5¿ù ÆòÀϰúÁÖ¸» ¹× °øÈÞÀÏ,?? ÷µÎ½Ã¿Í ºñ÷µÎ½Ã·Î ±¸ºÐÇÏ¿© µ¥ÀÌÅ͸¦ ÃøÁ¤ Á¶»çÇϰí Python°ú ArcGIS?? Pro¸¦È°¿ëÇÏ¿© ºÐ¼®ÇÏ¿´´Ù.??°á°úÀûÀ¸·Î,??º» ¿¬±¸´Â ´ÙÀ½ÀÇ ÃÖÁ¾ °á·Ð¿¡ µµ´Þ ÇÏ¿´´Ù.??ù°,??ÆÛ½º³Î ¸ðºô¸®Æ¼ÁÖÇàÀº ½Ã°£´ëº°·Î ±³Åë·®¿¡ ¿µÇâÀ» ¸¹ÀÌ ¹Þ¾ÒÀ¸¸ç,??À¯Çüº°·Î Àüµ¿Å±º¸µå°¡ Àü±âÀÚÀü°Å³ª ÀÚÀü°Åº¸´Ù³·Àº Áøµ¿°µµ ¹× Ãæ°Ý°µµ¿¡µµ ºÒ±¸Çϰí,??³ôÀº º¯µ¿ °è¼ö¸¦ º¸¿´´Ù.??µÑ°,??ÆÛ½º³Î ¸ðºô¸®Æ¼ ÁÖÇàÀº¿ìȸÀü ÄÚ³Ê,?? Ⱦ´Üº¸µµ,?? Â÷·® ÁøÃâÀÔ±¸,??±³Â÷·Î µîÀÇ µµ½Ã ¹°¸®Àû ȯ°æ ¿ä¼Ò¿¡ ¸¹Àº ¿µÇâÀ» ¹Þ¾Ò´Ù.?? ¼Â°,??ÆÛ½º³Î ¸ðºô¸®Æ¼ÀÇ ¾ÈÀüÇÑ ÁÖÇàÀ» À§Çؼ´Â Àü¿ë Â÷·Î ºÐ¸®,??´ë±â Â÷·Î ¶Ç´Â Å¥¹Ú½º È®º¸,??½Ã°¢Àû±¸ºÐ µîÀÌ ±ÇÀåµÈ´Ù.??º» ¿¬±¸´Â µµ½Ã ¹°¸®Àû ȯ°æ¿¡ µû¸¥ ÆÛ½º³Î ¸ðºô¸®Æ¼ ÁÖÇà Æ¯¼ºÀ» ½ÇÇè ¿¬±¸¸¦ÅëÇØ ¹Ì½ÃÀûÀ¸·Î ±Ô¸íÇÏ¿´´Ù´Â Á¡¿¡¼ ÀÇÀǰ¡ ÀÖ´Ù. |
| ¿ä¾à2 |
This study analyzed driving characteristics of personal mobility, which has been rapidly introduced and utilized in urban space as a personal short-distance transportation means, according to urban physical environments. For this, the study directly conducted a driving experiment research with bicycles, electric bicycles, and electric scooters installing personal monitoring devices such as an inertial sensor and a GPS speedometer. A route of 1.35km in Yongsin-dong, Dongdaemun-gu, Seoul was selected. The data were measured and surveyed in May 2021 according to the temporal divides including weekdays or weekends and holidays, peak or non-peak hours, and analyzed using Python and ArcGIS Pro. As a result, the study reached the following final conclusions. First, the driving of personal mobility was greatly affected by the traffic volume by time. By type, electric scooters showed a coefficient of variation higher than electric bicycles or bicycles, even though the former had lower vibration intensity and impact strength than the latter. Second, the driving of personal mobility was greatly influenced by urban physical environment factors such as right-turn corners, crosswalks, vehicle entrances, and intersections. Third, for safe driving of personal mobility, separation of dedicated lanes, installment of waiting lanes or cue boxes, and visual classification are recommended. This study is significant in that it microscopically identified driving characteristics of personal mobility according to urban physical environments through experimental research. |