Mobile QR Code QR CODE : Journal of the Korean Society of Civil Engineers

  1. ์˜๋‚จ๋Œ€ํ•™๊ต ๋„์‹œ๊ณตํ•™๊ณผ ์„์‚ฌ๊ณผ์ • (Yeungnam University)
  2. ์˜๋‚จ๋Œ€ํ•™๊ต ๋„์‹œ๊ณตํ•™๊ณผ ์กฐ๊ต์ˆ˜ (Yeungnam University)


๊ตํ†ต์‚ฌ๊ณ , ์ฐจ๋Ÿ‰๋ธ”๋ž™๋ฐ•์Šค, ์ด๋ฅœ์ฐจ, ํƒ์‹œ, ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„, ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•
Crash, Vehicle black box, Two wheeler (TW), Taxi, Injury severity, Ordered probit model

  • 1. ์„œ ๋ก 

  • 2. ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ

  • 3. ์ž๋ฃŒ ๊ตฌ์ถ•

  • 4. ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„

  •   4.1 ์ˆœ์„œํ˜• ํ”„๋กœ๋น— ๋ชจํ˜•

  •   4.2 ์ถ”์ •๋œ ๋ชจํ˜•์˜ ํ‰๊ฐ€

  •   4.3 ๋ชจํ˜•์˜ ํ•ด์„

  • 5. ๊ฒฐ ๋ก 

1. ์„œ ๋ก 

์ž์ „๊ฑฐ์™€ ์˜คํ† ๋ฐ”์ด์™€ ๊ฐ™์€ ์ด๋ฅœ์ฐจ(Two Wheeler: TW)๋Š” ์‚ฌ๊ณ  ๋ฐœ์ƒ ์‹œ ์šด์ „์ž์˜ ์ถฉ๊ฒฉ์„ ๋ณดํ˜ธํ•  ์ˆ˜ ์žˆ๋Š” ์ฐจ์ฒด๊ฐ€ ์—†์–ด ์šด์ „์ž์˜ ์น˜์‚ฌ์œจ์„ ๋†’์ด๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๊ตํ†ต์‚ฌ๊ณ ๋ถ„์„์‹œ์Šคํ…œ(Traffic Accident Analysis System: TAAS)1)์— ๋”ฐ๋ฅด๋ฉด ์ „๊ตญ ๊ตํ†ต์‚ฌ๊ณ  ์‚ฌ๋ง๊ฑด์ˆ˜๋Š” 2012๋…„ 5,392๊ฑด์—์„œ 2017๋…„ 4,185๊ฑด์œผ๋กœ ์—ฐํ‰๊ท  ์•ฝ 5%์”ฉ ๊ฐ์†Œํ•˜๊ณ  ์žˆ๋Š” ๋ฐ˜๋ฉด, ์ด๋ฅœ์ฐจ ์‚ฌ๊ณ  ์‚ฌ๋ง๊ฑด์ˆ˜๋Š” 2012๋…„ 694๊ฑด์—์„œ 2017๋…„ 671๊ฑด์œผ๋กœ ์—ฐํ‰๊ท  1%์”ฉ ๊ฐ์†Œํ•˜์—ฌ ์ „๊ตญ ๊ตํ†ต์‚ฌ๊ณ ์— ๋น„ํ•ด ์‚ฌ๋ง๊ฑด์ˆ˜ ๊ฐ์†Œ๊ฐ€ ๋”๋”˜ ํŽธ์ด๋‹ค. ๋˜ํ•œ ์ „๊ตญ ๊ตํ†ต์‚ฌ๊ณ  ๋ฐœ์ƒ๊ฑด์ˆ˜๋Š” 2012๋…„ 223,656๊ฑด์—์„œ 2017๋…„ 216,335๊ฑด์œผ๋กœ ์—ฐํ‰๊ท  ์•ฝ 1%์”ฉ ๊ฐ์†Œํ•˜๊ณ  ์žˆ๋Š” ๋ฐ˜๋ฉด, ์ด๋ฅœ์ฐจ ์‚ฌ๊ณ  ๋ฐœ์ƒ๊ฑด์ˆ˜๋Š” 2012๋…„ 23,323๊ฑด์—์„œ 2017๋…„ 27,793๊ฑด์œผ๋กœ ์•ฝ 4%์”ฉ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค.

1) http://taas.kroad.or.kr/

2. ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ

์˜คํ† ๋ฐ”์ด ์šด์ „์ž ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„์— ๋Œ€ํ•œ ์ดˆ๊ธฐ ์—ฐ๊ตฌ๋Š” ๋Œ€ํ‘œ์ ์œผ๋กœ ๋จธ๋ฆฌ ๋ถ€์ƒ ๋ฐ ํ—ฌ๋ฉง ์ฐฉ์šฉ๊ณผ ๊ฐ™์ด ์ธ์ ํŠน์„ฑ์„ ์ค‘์‹ฌ์œผ๋กœ ์—ฐ๊ตฌ๊ฐ€ ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค(Goldstein, 1986; Weiss, 1992). Goldstein(1986)์€ ๋จธ๋ฆฌ, ๋ชฉ, ๊ทธ๋ฆฌ๊ณ  ๋‹ค๋ฅธ ์‹ ์ฒด ๋ถ€์œ„ ๋ถ€์ƒ์— ๋Œ€ํ•œ ์‹ฌ๊ฐ๋„ ๋ถ„์„์„ ์œ„ํ•ด ํ† ๋น—๋ชจํ˜•์„ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ, Weiss(1992)๋Š” ์‹ ์ฒด ๋ถ€์ƒ ์ž๋ฃŒ๋ฅผ ๊ทผ๊ฑฐ๋กœ ๋จธ๋ฆฌ ์ถฉ๋Œ์— ๋Œ€ํ•œ ์‹ฌ๊ฐ๋„๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์„ ํ™œ์šฉํ•˜์˜€๋‹ค(Shankar and Mannering, 1996). ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํ—ฌ๋ฉง ์ฐฉ์šฉ์ด ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๊ฐ์†Œ์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๊ฐ•์กฐํ•˜์˜€๋‹ค. ์ดํ›„ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด ์ธ์ ํŠน์„ฑ์™ธ์— ์™ธ๋ถ€ํ™˜๊ฒฝํŠน์„ฑ, ๋„๋กœํŠน์„ฑ, ์‚ฌ๊ณ ํŠน์„ฑ, ๊ทธ๋ฆฌ๊ณ  ์ฐจ๋Ÿ‰ํŠน์„ฑ์„ ๊ณ ๋ คํ•œ ๋‹ค๋ณ€๋Ÿ‰ ๋ถ„์„์ด ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. Quddus et al.(2002)์€ ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ ๊ธฐ๋ฐ˜ ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์„ ํ™œ์šฉํ•˜์—ฌ ์˜คํ† ๋ฐ”์ด ์šด์ „์ž ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ๋น„์‹ฑ๊ฐ€ํด๊ตญ์ ์ธ, ์—”์ง„ ์šฉ๋Ÿ‰ ์ฆ๊ฐ€, ์ฐจ๋Ÿ‰ ์ „์กฐ๋“ฑ์ด ๊บผ์ง„ ์ฃผ๊ฐ„ ์‹œ๊ฐ„๋Œ€, ์ด๋ฅธ ์•„์นจ, ์˜คํ† ๋ฐ”์ด์— ๋™์Šน์ž๊ฐ€ ํƒ‘์Šน(pillion passenger)ํ•œ ์‚ฌ๊ณ ์ธ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. Savolainen and Mannering(2007)์€ ์˜คํ† ๋ฐ”์ด ์šด์ „์ž ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์กฐ์‚ฌ ์ž๋ฃŒ ๊ธฐ๋ฐ˜ ๋„ค์Šคํ‹ฐ๋“œ ๋กœ์ง“๋ชจํ˜• ๋ฐ ๋‹ค๋ณ€๋Ÿ‰ ๋กœ์ง“๋ชจํ˜•์„ ์ ์šฉํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ์ œํ•œ๋œ ์‹œ์•ผ(์ˆ˜ํ‰ ๊ตฌ๊ฐ„, ์ˆ˜์ง ๊ตฌ๊ฐ„, ์•ผ๊ฐ„ ์‹œ๊ฐ„๋Œ€), ๊ณผ์†, ์Œ์ฃผ์šด์ „, ํ—ฌ๋ฉง ๋ฏธ์ฐฉ์šฉ, ์šฐ์ธก ์ธก๋ฉด ๋ฐ ์ •๋ฉด์ถฉ๋Œ, ๊ทธ๋ฆฌ๊ณ  ๊ณต์ž‘๋ฌผ ์‚ฌ๊ณ ์ธ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , ์ –์€ ๋…ธ๋ฉด์ƒํƒœ, ๊ต์ฐจ๋กœ ์ธ๊ทผ, ๊ทธ๋ฆฌ๊ณ  ์˜คํ† ๋ฐ”์ด์— ๋™์Šน์ž๊ฐ€ ํƒ‘์Šนํ•œ ์‚ฌ๊ณ ์˜ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋‚ฎ์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. Na and Park(2012)์€ ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ ๊ธฐ๋ฐ˜ ์ฒญ์ฃผ์‹œ ์ฃผ๊ฐ„์„ ๋„๋กœ์—์„œ ๋ฐœ์ƒํ•œ ์˜คํ† ๋ฐ”์ด ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„์„ ์œ„ํ•ด ์ˆœ์„œํ˜• ๋กœ์ง“๋ชจํ˜•์„ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ, ๊ฒจ์šธ์ฒ , ์ฃผ๊ฐ„ ์‹œ๊ฐ„๋Œ€, 25์„ธ ์ดํ•˜, ๊ทธ๋ฆฌ๊ณ  ์ด๋ฅœ์ฐจ ๋Œ€ ์ฐจ๋Ÿ‰ ์‚ฌ๊ณ ๊ฐ€ ์˜คํ† ๋ฐ”์ด ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋†’์ธ๋‹ค๋Š” ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. Choi and Kum(2014)์€ ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ ๊ธฐ๋ฐ˜ ์„œ์šธํŠน๋ณ„์‹œ ์ „ ๊ตฌ๊ฐ„์—์„œ ๋ฐœ์ƒํ•œ ์˜คํ† ๋ฐ”์ด ์‚ฌ๊ณ  ์ž๋ฃŒ๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์„ ์ ์šฉํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ์ด๋ฅœ์ฐจ ๋‹จ๋…, ์ขŒ์ธก ๋‚ด๋ฆฌ๋ง‰ ์„ ํ˜•, ์ขŒ์ธก ํ‰์ง€, ์ง์„  ๋‚ด๋ฆฌ๋ง‰ ์„ ํ˜•, ๊ทธ๋ฆฌ๊ณ  ์ด๋ฅœ์ฐจ ๋ฐฐ๊ธฐ๋Ÿ‰(50cc ์ด์ƒ)์ธ ์‚ฌ๊ณ ์˜ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ์ฃผ๊ฐ„ ์‹œ๊ฐ„๋Œ€, ์ด๋ฅœ์ฐจ ๋Œ€ ์ฐจ๋Ÿ‰, ๊ทธ๋ฆฌ๊ณ  ์ด๋ฅœ์ฐจ ๋Œ€ ์‚ฌ๋žŒ ์‚ฌ๊ณ ์ธ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋‚ฎ์•„์ง€๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค.

๋งˆ์ฐฌ๊ฐ€์ง€๋กœ 1990๋…„๋Œ€ ๋ง ์ดํ›„, ์ž์ „๊ฑฐ ์šด์ „์ž ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด ์—ฌ๋Ÿฌ ํŠน์„ฑ์„ ๊ณ ๋ คํ•œ ๋‹ค๋ณ€๋Ÿ‰ ๋ถ„์„์ด ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. Klop and Khattak(1999)์€ ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ ๊ธฐ๋ฐ˜ ์ž์ „๊ฑฐ ์šด์ „์ž ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„์„ ์œ„ํ•ด ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์„ ์ ์šฉํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ์ง์„  ๋ฐ ๊ณก์„  ์˜ค๋ฅด๋ง‰ ๊ตฌ๊ฐ„, ์•ผ๊ฐ„ ์‹œ๊ฐ„๋Œ€, ์•ˆ๊ฐœ, ๊ทธ๋ฆฌ๊ณ  ์ œํ•œ ์†๋„๊ฐ€ ๋†’์€ ๊ณณ์—์„œ ๋ฐœ์ƒํ•œ ์‚ฌ๊ณ ์˜ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐ˜๋Œ€๋กœ, ๋†’์€ ์—ฐํ‰๊ท  ์ผ๊ตํ†ต๋Ÿ‰(Annual Average Daily Traffic: AADT), ์ œํ•œ์†๋„๊ฐ€ ๋†’๊ณ  ๊ธธ์–ด๊นจ ํญ์ด๋„“์€ ๊ตฌ๊ฐ„, ๊ทธ๋ฆฌ๊ณ  ์•ผ๊ฐ„์— ๊ฐ€๋กœ๋“ฑ์ด ์ผœ์ง„ ๊ณณ์—์„œ ๋ฐœ์ƒํ•œ ์‚ฌ๊ณ ์ธ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋‚ฎ์•„์ง„๋‹ค๋Š” ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. Oh et al.(2007)์€ ์ธ์ฒœ๊ด‘์—ญ์‹œ ์ „ ์ง€์—ญ ๊ต์ฐจ๋กœ์—์„œ ๋ฐœ์ƒํ•œ ์ž์ „๊ฑฐ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„์„ ์œ„ํ•ด ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์„ ์ ์šฉํ•˜์˜€๋‹ค. ์ธ์ฒœ์‹œ ๋ถ€ํ‰๊ตฌ์™ธ ๋‹ค๋ฅธ ์ง€์—ญ์—์„œ ๋ฐœ์ƒํ•œ ์‚ฌ๊ณ , ๋†’์€ ํ‰๊ท  ์ผ๊ตํ†ต๋Ÿ‰(Average Daily Traffic: ADT), ๊ฐ€ํ•ด์ž ์ฐจ๋Ÿ‰์˜ ์†๋„๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก, ๊ทธ๋ฆฌ๊ณ  ๊ฐ€ํ•ด์ž ์ฐจ๋Ÿ‰์ด ์ง์ง„ ์ค‘์— ๋ฐœ์ƒํ•œ ์‚ฌ๊ณ ์ธ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋†’์ด๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐ˜๋Œ€๋กœ, ๊ต์ฐจ๋กœ ๋ฐ–, ๊ตํ†ต์„ฌ, ์ž์ „๊ฑฐ ์ „์šฉ๋„๋กœ, ๊ทธ๋ฆฌ๊ณ  ํšก๋‹จ๋ณด๋„๊ฐ€ ์„ค์น˜๋œ ๊ณณ์—์„œ ๋ฐœ์ƒํ•œ ์‚ฌ๊ณ ๋Š” ์ž์ „๊ฑฐ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋‚ฎ์ถ”๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. Yan et al.(2011)์€ ์ž์ „๊ฑฐ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„์„ ์œ„ํ•ด ๋‹ค๋ณ€๋Ÿ‰ ๋กœ์ง“๋ชจํ˜• ๋ฐ ์ดํ•ญ ๋กœ์ง“๋ชจํ˜•, ๊ฒฝํ–ฅ๋ถ„์„(propensity analysis)์„ ์ ์šฉํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ์ถฉ๋Œ ํ›„ ์šด์ „์ž๊ฐ€ ํŠ•๊ฒจ์ ธ ๋‚˜๊ฐˆ ๊ฒฝ์šฐ, ์ •๋ฉด์ถฉ๋Œ, ์ž์ „๊ฑฐ ์ฃผํ–‰ ์ค‘ ์‚ฌ๊ณ , ์•ผ๊ฐ„์— ๊ฐ€๋กœ๋“ฑ์ด ์—†๋Š” ๊ณณ์—์„œ ๋ฐœ์ƒํ•œ ์‚ฌ๊ณ , ์ค‘์•™๋ถ„๋ฆฌ๋Œ€๊ฐ€ ์—†๋Š” ๊ณณ์—์„œ ๋ฐœ์ƒํ•œ ์‚ฌ๊ณ , ๋†’์€ ์ œํ•œ์†๋„, ๊ทธ๋ฆฌ๊ณ  ํ™”๋ฌผ์ฐจ ์‚ฌ๊ณ ๋Š” ์ž์ „๊ฑฐ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋†’์ด๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. Shin et al.(2012)์€ ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ ๊ธฐ๋ฐ˜ ์„œ์šธํŠน๋ณ„์‹œ์—์„œ ๋ฐœ์ƒํ•œ ์ž์ „๊ฑฐ ์šด์ „์ž ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„์„ ์œ„ํ•ด ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ชจํ˜•์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ, ์ž์ „๊ฑฐ ์šด์ „์ž์˜ ๋ฒ•๊ทœ์œ„๋ฐ˜, ํšก๋‹จ๋ณด๋„๋ฅผ ๊ฑด๋„ˆ๋Š” ์ž์ „๊ฑฐ ์šด์ „์ž, ์ฐจ๋Ÿ‰ ์šด์ „์ž ๋ฒ•๊ทœ์œ„๋ฐ˜, ๊ทธ๋ฆฌ๊ณ  ์ž์ „๊ฑฐ ์šด์ „์ž์˜ ์—ฐ๋ น์ด ์ฆ๊ฐ€ํ•  ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , ์—ฌ์„ฑ ์ž์ „๊ฑฐ ์šด์ „์ž, ๊ณก์„  ๋ฐ ๊ฒฝ์‚ฌ์ง€์—์„œ ๋ฐœ์ƒํ•œ ์‚ฌ๊ณ ์ธ ๊ฒฝ์šฐ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋‚ฎ์•„์ง€๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค.

์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ์„ ํ†ตํ•ด ๋ณธ ์—ฐ๊ตฌ์˜ ์ฐจ๋ณ„์„ฑ์„ ๋„์ถœํ•˜์˜€๋‹ค. ์„ ํ–‰์—ฐ๊ตฌ๋“ค์˜ ์‚ฌ๊ณ  ์ž๋ฃŒ ์ˆ˜์ง‘์€ ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ ํ™œ์šฉํ•˜์—ฌ ๋ถ€์ƒ ์ˆ˜์ค€์ด ๊ฒฝ๋ฏธํ•œ ์ด๋ฅœ์ฐจ ์‚ฌ๊ณ ์˜ ๊ฒฝ์šฐ ์ˆ˜์ง‘ํ•˜์ง€ ๋ชปํ•  ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ๋‹ค. ์ฆ‰, ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ๊ฐ€ ์•„๋‹Œ ์ƒˆ๋กœ์šด ์ˆ˜์ง‘ ๊ธฐ์ˆ ์„ ํ™œ์šฉํ•œ ์‚ฌ๊ณ  ๋ถ„์„์œผ๋กœ ์—ฐ๊ตฌ์˜ ์ •ํ™•์„ฑ์„ ๋†’์ผ ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋ธ”๋ž™๋ฐ•์Šค ์ž๋ฃŒ๋Š” ์˜์ƒ ์ •๋ณด๋ฅผ ํ†ตํ•ด ์‚ฌ๊ณ  ์ƒํ™ฉ์„ ํ™•์ธํ•˜์—ฌ ๋ถ„์„์ž๊ฐ€ ์‚ฌ๊ณ  ๋‹น์‹œ ์ •๋ณด๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ํŒ๋‹จํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ฐจ๋Ÿ‰ ์ฃผํ–‰ ๋ฐฉํ–ฅ, ์ถฉ๋Œ ์†๋„, ์ถฉ๋Œ ์œ„์น˜, ๊ทธ๋ฆฌ๊ณ  2, 3์ฐจ ์ถฉ๊ฒฉ๊ณผ ๊ฐ™์ด ๊ธฐ์กด์— ํ™•์ธํ•  ์ˆ˜ ์—†์—ˆ๋˜ ์ธ์ž๋ฅผ ์ถ”๊ฐ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ˆ˜ํ–‰๋  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ํƒ์‹œ-์ด๋ฅœ์ฐจ ์‚ฌ๊ณ  ๋ธ”๋ž™๋ฐ•์Šค ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ธ์ž๋ฅผ ๋„์ถœํ•˜๊ณ ์ž ํ•œ๋‹ค.

3. ์ž๋ฃŒ ๊ตฌ์ถ•

๋ณธ ์—ฐ๊ตฌ๋Š” 2010๋…„๋ถ€ํ„ฐ 2011๋…„๊นŒ์ง€ 2๋…„ ๊ฐ„ ์ธ์ฒœํƒ์‹œ๊ณต์ œ์กฐํ•ฉ์—์„œ ์ˆ˜์ง‘ํ•œ ์ธ์ฒœ๊ด‘์—ญ์‹œ ํƒ์‹œ-์ด๋ฅœ์ฐจ ๊ตํ†ต์‚ฌ๊ณ  248๊ฑด์— ๋Œ€ํ•œ ๋ธ”๋ž™๋ฐ•์Šค ์˜์ƒ ์ž๋ฃŒ์™€ ์ด์— ๋Œ€ํ•œ ์‚ฌ๊ณ  ๊ธฐ๋ก ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์˜€๋‹ค. ๋จผ์ € ๋ถ„์„์ž๊ฐ€ ๋ธ”๋ž™๋ฐ•์Šค ์˜์ƒ ์ •๋ณด๋ฅผ ํ†ตํ•ด ์‚ฌ๊ณ  ์ƒํ™ฉ์„ ํ™•์ธํ•จ์œผ๋กœ์จ ํƒ์‹œ์™€ ์ด๋ฅœ์ฐจ์˜ ํŒŒ์†์—ฌ๋ถ€, ์ฃผํ–‰ ๋ฐฉํ–ฅ, ์ถฉ๋Œ ์†๋„, ์ถฉ๋Œ ์œ„์น˜, ์‚ฌ๊ณ  ํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ณดํ–‰์—ฌ๋ถ€, ๊ทธ๋ฆฌ๊ณ  2, 3์ฐจ ์ถฉ๊ฒฉ ์—ฌ๋ถ€ ๋“ฑ ๊ธฐ์กด ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ์—์„œ ์ˆ˜์ง‘ํ•  ์ˆ˜ ์—†์—ˆ๋˜ ์ƒˆ๋กœ์šด ์ธ์ž๋ฅผ ์ถ”๊ฐ€ํ•˜์˜€๋‹ค. ์ด ์ค‘ ํƒ์‹œ์™€ ์ด๋ฅœ์ฐจ์˜ ํŒŒ์†์—ฌ๋ถ€๋Š” ๋ธ”๋ž™๋ฐ•์Šค๋ฅผ ํ†ตํ•ด ์ฐจ๋Ÿ‰์˜ ํŒŒ์†์ด ํ™•์ธ๋˜๋Š” ๊ฒฝ์šฐ โ€˜ํŒŒ์† ์žˆ์Œโ€™, ํ™•์ธ๋˜์ง€ ์•Š์•˜์„ ๊ฒฝ์šฐ โ€˜ํŒŒ์† ์—†์Œโ€™์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์˜€์œผ๋ฉฐ, ์ฃผํ–‰๋ฐฉํ–ฅ์€ ์‚ฌ๊ณ  ๋‹น์‹œ ํƒ์‹œ์™€ ์ด๋ฅœ์ฐจ ๊ฐ๊ฐ์˜ ์ฃผํ–‰๋ฐฉํ–ฅ(์ง์ง„, ์ขŒยท์šฐํšŒ์ „, Uํ„ด)์„ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. ๋‹ค์Œ์œผ๋กœ ์ถฉ๋Œ ์†๋„๋Š” ์˜์ƒ ์ •๋ณด์—์„œ ํ™•์ธ๋œ ์ถฉ๋Œ ์ง์ „์˜ ํƒ์‹œ์˜ ์†๋„๋ฅผ ๋‚˜ํƒ€๋‚ด๋ฉฐ, ์ถฉ๋Œ ์œ„์น˜๋Š” ํƒ์‹œ์™€ ์˜คํ† ๋ฐ”์ด์˜ ์ถฉ๋Œ ์œ„์น˜๋ฅผ ์ •๋ฉด์ถฉ๋Œ, ์ธก๋ฉด์ถฉ๋Œ, ์ถ”๋Œ, ๊ทธ๋ฆฌ๊ณ  ์‚ฌ์ด๋“œ(sidewipe)๋กœ ๋‚˜๋ˆ„์–ด ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. ๋˜ํ•œ ์‚ฌ๊ณ  ํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ณดํ–‰์—ฌ๋ถ€๋Š” ์˜์ƒ์„ ํ†ตํ•ด ์‚ฌ๊ณ ๊ฐ€ ๊ฒฝ๋ฏธํ•˜์—ฌ ์ด๋ฅœ์ฐจ ์šด์ „์ž๊ฐ€ ๋ณดํ–‰ํ•œ ๊ฒƒ์ด ํ™•์ธ๋˜๋Š” ๊ฒฝ์šฐ โ€˜๋ณดํ–‰ ๊ฐ€๋Šฅโ€™์œผ๋กœ ์ •์˜ํ•˜์˜€์œผ๋ฉฐ, ๋ฐ˜๋ฉด์— ์‚ฌ๊ณ  ํ›„ ์‚ฌ๋งํ–ˆ๊ฑฐ๋‚˜ ๋ถ€์ƒ ์ •๋„๊ฐ€ ์‹ฌํ•˜์—ฌ ๋ณดํ–‰์ด ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค๊ณ  ํŒ๋‹จ๋˜๋Š” ๊ฒฝ์šฐ โ€˜๋ณดํ–‰ ๋ถˆ๊ฐ€๋Šฅโ€™์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ 2, 3์ฐจ ์ถฉ๊ฒฉ ์—ฌ๋ถ€๋Š” ์‚ฌ๊ณ  ๊ณผ์ •์—์„œ ํƒ์‹œ-์ด๋ฅœ์ฐจ ๊ฐ„ 1์ฐจ ์ถฉ๋Œ ์ดํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ 2, 3์ฐจ ์ถฉ๊ฒฉ ์—ฌ๋ถ€๋ฅผ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค.

๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ธ์ฒœํƒ์‹œ๊ณต์ œ์กฐํ•ฉ์—์„œ ์ˆ˜์ง‘ํ•œ ๊ธฐ์กด์˜ ์‚ฌ๊ณ  ๊ธฐ๋ก ์ž๋ฃŒ์—์„œ ์‚ฌ๊ณ ์ž ์ˆ˜, ๊ฐ€ํ•ด์ž/ํ”ผํ•ด์ž ๊ตฌ๋ถ„, ํƒ์‹œ ๋ฐ ์ด๋ฅœ์ฐจ ์‚ฌ๊ณ ์›์ธ, ์ด๋ฅœ์ฐจ ์šด์ „์ž ์ง„๋‹จ ์ •๋ณด๋ฅผ ๋ณ€์ˆ˜๋กœ์„œ ํ™œ์šฉํ•˜์˜€๋‹ค. ์—ฌ๊ธฐ์„œ ์ด๋ฅœ์ฐจ ์šด์ „์ž ์ง„๋‹จ ์ •๋ณด๋ฅผ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ณ€์ˆ˜๋กœ ํ™œ์šฉํ•˜๊ธฐ ์œ„ํ•ด ๊ฒฝ์ฐฐ์ฒญ(the Korean National Policy Agency: KNPA)์—์„œ ์ œ์‹œํ•œ ๊ธฐ์ค€์„ ํ™œ์šฉํ•˜์˜€๋‹ค: 1) ๊ณ ํ†ต ํ˜ธ์†Œ, ๋ฏธ๋ฐœ๊ธ‰ ๋˜๋Š” ์‘๊ธ‰์น˜๋ฃŒ; 2) ์œก์•ˆ ๋ถ€์ƒ, ์ „์น˜ 2์ฃผ ์ดํ•˜๋กœ ์ง„๋‹จ๋ฐ›์€ ๊ฒฝ์šฐ; 3) ํ™œ๋™ ๋ถˆ๊ฐ€, ์ „์น˜ 3์ฃผ ์ด์ƒ์œผ๋กœ ์ง„๋‹จ๋ฐ›์€ ๊ฒฝ์šฐ; 4) ์‚ฌ๋ง. Table 1์€ ๋ณธ ์—ฐ๊ตฌ์— ์ ์šฉ๋œ ๋ณ€์ˆ˜์™€ ๋ณ€์ˆ˜์˜ ํŠน์„ฑ์„ ์ •๋ฆฌํ•œ ๊ฒƒ์ด๋‹ค.

Table 1. Descriptive Statistics of Taxi-Two Wheeler Crash Data

Category Variable definition Description and coding input value
Vehicle characteristics Taxi vehicle maneuver


TW maneuver

If straight through: 1, otherwise: 0
If right and left turn: 1, otherwise: 0
If U-turn: 1, otherwise: 0
If straight through: 1, otherwise: 0
If right and left turn: 1, otherwise: 0
If U-turn: 1, otherwise: 0
Human characteristics TW driver gender If TW driver was male: 1, otherwise: 0
Environmental characteristics Weather
Road surface condition


Time period
Sight obstruction
If rainy: 1, otherwise: 0
If dry: 1, otherwise: 0
If wet: 1, otherwise: 0
If snow: 1, otherwise: 0
If daytime periods (07:00-18:00): 1, otherwise: 0
If near parking: 1, otherwise: 0
Road characteristics Number of lanes
Road section




Segregation of vehicle and
pedestrian paths
Median
Traffic control type

1, 2, 4, 6, 8, 10 (ratio scale)
If near intersection:1, otherwise: 0
If intersection: 1, otherwise: 0
If near crosswalk: 1, otherwise: 0
If crosswalk: 1, otherwise: 0
If roadway segment: 1, otherwise: 0
If segregation: 1, otherwise: 0
If median on the road:1, otherwise: 0
If normal: 1, otherwise: 0
If flashing: 1, otherwise: 0
If none: 1, otherwise: 0
Crash characteristics Number injured
Assault/Victim
Helmet
Vehicle speed

TTC (Time To Collision)
Taxi damage
TW damage
Crash cause(taxi)






Crash cause(TW)





Vehicle type
Crash location



TW rollover
2nd impact of TW driver
3rd impact of TW driver
TW driver impairment level
1, 2, 3+ (ratio scale)
If assault: 1, otherwise: 0
If wear: 1, otherwise: 0
Running speed (running speed prior to starting break)
Crash speed (speed at the crash moment reconstructed by VBB)
Time difference between braking start and crash moment (ratio scale)
If damage: 1, otherwise: 0
If damage: 1, otherwise: 0
If passenger getting on/off taxi: 1, otherwise: 0
If driver was running at the red light signal: 1, otherwise: 0
If merging in traffic, otherwise: 0
If passing, otherwise: 0
If driver distracted: 1, otherwise: 0
If driver was crossing the central line: 1. otherwise: 0
If other factors: 1, otherwise: 0
If normal driving: 1, otherwise: 0
If two wheeler was jaywalking: 1, otherwise: 0
If two wheeler was running at the red light signal: 1, otherwise: 0
If merging in traffic, otherwise: 0
If passing, otherwise: 0
If two wheeler was crossing the central line: 1, otherwise: 0
If motor cycle: 1, bicycle: 0
If head-on collision: 1, otherwise: 0
If rear-ending: 1, otherwise: 0
If broadside collision: 1, otherwise: 0
If sidewipe: 1, otherwise: 0
If rollover: 1, otherwise: 0
If 2nd impact of driver: 1, otherwise: 0
If 3rd impact of driver: 1, otherwise: 0
If not standing after crash: 1, otherwise: 0
Injury severity Injury level Complaints of pain: 0, visible injury: 1, incapacitating injury: 2, and fatality: 3

4. ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„

4.1 ์ˆœ์„œํ˜• ํ”„๋กœ๋น— ๋ชจํ˜•

๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ 4๋‹จ๊ณ„(๊ณ ํ†ต ํ˜ธ์†Œ, ์œก์•ˆ ๋ถ€์ƒ, ํ™œ๋™ ๋ถˆ๊ฐ€, ์‚ฌ๋ง)๋กœ ๊ตฌ๋ถ„ํ•˜์˜€์œผ๋ฉฐ, ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„์— ๋Œ€ํ•œ ์˜ํ–ฅ์ธ์ž๋ฅผ ๋„์ถœํ•˜๊ธฐ ์œ„ํ•ด ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์„ ์ ์šฉํ•˜์˜€๋‹ค. ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์€ 2๊ฐœ ์ด์ƒ์˜ ์ˆœ์œ„๊ฐ€ ์žˆ๋Š” ์ข…์†๋ณ€์ˆ˜์™€ ์„ค๋ช…๋ณ€์ˆ˜ ๊ฐ„ ๊ด€๊ณ„ ํŒŒ์•…์— ์ ํ•ฉํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ์„œ ๋ชจํ˜•์˜ ์ˆ˜๋ฆฌ์  ํ‘œํ˜„์€ ๋‹ค์Œ Eq. (1)๊ณผ ๊ฐ™๋‹ค.

y i * = x i ' ฮฒ + ฮต i ,   ฮต i = N 0 ,   1 (1)

Eq. (1)์—์„œ x i ' ๋Š” ์„ค๋ช…๋ณ€์ˆ˜ ๋ฒกํ„ฐ, ๐›ฝ๋Š” ์ถ”์ •๋  ํŒŒ๋ผ๋ฉ”ํƒ€ ๋ฒกํ„ฐ, ๊ทธ๋ฆฌ๊ณ  ๐œ€i๋Š” ์ •๊ทœ๋ถ„ํฌ๋ฅผ ๋”ฐ๋ฅด๋Š” ๊ฒƒ์œผ๋กœ ๊ฐ€์ •ํ•œ ์˜ค์ฐจํ•ญ์„ ์˜๋ฏธํ•œ๋‹ค. ๋˜ํ•œ y i * ๋Š” i๋ฒˆ์งธ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” ์ž ์žฌ์  ์ข…์†๋ณ€์ˆ˜๋ฅผ ์˜๋ฏธํ•œ๋‹ค. yi๋Š” ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์˜ ์ข…์†๋ณ€์ˆ˜๋ฅผ ์˜๋ฏธํ•˜๋ฉฐ, Eq. (2)์™€ ๊ฐ™์ด ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ๋‹ค.

$$\begin{array}{l}y_i=\left\{\begin{array}{l}0\;if\;-\infty\leq y_i^\ast\leq\mu_0(complaint\;of\;pain)\\\begin{array}{l}1\;if\;\mu_0\leq y_i^\ast\leq\mu_1(visible\;injury)\\\begin{array}{l}2\;if\;\mu_1\leq y_i^\ast\leq\mu_2(incapacitating\;injury)\\3\;if\;\mu_2\;\leq y_i^\ast\leq\infty(fatality)\end{array}\end{array}\end{array}\right.\\\\\\\end{array}$$ (2)

Eq. (2)์—์„œ๋Š” yi์˜ ๋ฒ”์œ„์— ๋”ฐ๋ผ ๊ณ ํ†ต ํ˜ธ์†Œ(complaint of pain): 0, ์œก์•ˆ ๋ถ€์ƒ(visible injury): 1, ํ™œ๋™ ๋ถˆ๊ฐ€(incapacitating injury): 2, ์‚ฌ๋ง(fatality): 3์œผ๋กœ ์ข…์†๋ณ€์ˆ˜๋ฅผ ์„ค์ •ํ•˜์˜€๋‹ค. ๐œ‡0, ๐œ‡1, ๊ทธ๋ฆฌ๊ณ  ๐œ‡2๋Š” ๊ฐ ์„ค๋ช…๋ณ€์ˆ˜์˜ ์ถ”์ •๊ณ„์ˆ˜ ๐›ฝ๋ฅผ ์ทจํ•˜์—ฌ ์ถ”์ • ๊ฐ€๋Šฅํ•œ ๋ฏธ์ง€์˜ ๊ฐ’์ด๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๊ฐ ์‚ฌ๊ณ ๊ฐ€ ํŠน์ • ์‹ฌ๊ฐ๋„ ์ˆ˜์ค€์— ํฌํ•จ๋  ํ™•๋ฅ ์„ ๊ณ„์‚ฐํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์ž ์žฌ๋ณ€์ˆ˜ y i * ๊ฐ€ ํŠน์ • ๊ตฌ๊ฐ„์— ํฌํ•จ๋  ํ™•๋ฅ ์„ Eqs. (3)~(6)๊ณผ ๊ฐ™์ด ๋‚˜ํƒ€๋‚ผ ์ˆ˜ ์žˆ๋‹ค.

P ( y i = 0 ) = โˆซ - โˆž - x i ' ฮฒ f ( ฮต i ) d ฮต i = F ( - x i ' ฮฒ ) (3)
P ( y i = 1 ) = โˆซ - โˆž ฮผ 1 - x i ' ฮฒ f ( ฮต i ) d ฮต i = F ( ฮผ 1 - x i ' ฮฒ ) - F ( - x i ' ฮฒ ) (4)
P ( y i = 2 ) = โˆซ - โˆž ฮผ 2 - x i ' ฮฒ f ( ฮต i ) d ฮต i = F ( ฮผ 2 - x i ' ฮฒ ) - F ( ฮผ 1 - x i ' ฮฒ ) (5)
P ( y i = 3 ) = โˆซ - โˆž ฮผ 3 - x i ' ฮฒ f ( ฮต i ) d ฮต i = 1 - F ( ฮผ 2 - x i ' ฮฒ ) (6)

์—ฌ๊ธฐ์„œ, f*๋Š” ํ‘œ์ค€์ •๊ทœํ™•๋ฅ ๋ฐ€๋„, F(*)๋Š” ๋ˆ„์ ๋ถ„ํฌํ•จ์ˆ˜๋ฅผ ์˜๋ฏธํ•œ๋‹ค.

4.2 ์ถ”์ •๋œ ๋ชจํ˜•์˜ ํ‰๊ฐ€

๋ถ„์„ ๊ฒฐ๊ณผ, ์ถฉ๋Œ ์ง์ „ ํƒ์‹œ์˜ ์†๋„, ํƒ์‹œ ํŒŒ์† ์—ฌ๋ถ€, ์ด๋ฅœ์ฐจ ํŒŒ์† ์—ฌ๋ถ€, ์‚ฌ๊ณ  ํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ณดํ–‰ ์—ฌ๋ถ€, ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ 2, 3์ฐจ ์ถฉ๊ฒฉ ์—ฌ๋ถ€๊ฐ€ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค(Table 2 ์ฐธ์กฐ). ์ฆ‰, ์ถฉ๋Œ ์ง์ „์˜ ํƒ์‹œ ์†๋„๊ฐ€ ๋†’์„์ˆ˜๋ก, ํƒ์‹œ ๋˜๋Š” ์ด๋ฅœ์ฐจ์˜ ํŒŒ์†์ด ๋ฐœ์ƒํ•œ ๊ฒฝ์šฐ, ์‚ฌ๊ณ  ํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ณดํ–‰์ด ๋ถˆ๊ฐ€๋Šฅํ•  ๊ฒฝ์šฐ, ๊ทธ๋ฆฌ๊ณ  ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ 2, 3์ฐจ ์ถฉ๊ฒฉ์œผ๋กœ ์‚ฌ๊ณ ๊ฐ€ ์ด์–ด์ง„ ๊ฒฝ์šฐ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๊ฐ€ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค.

Table 2. Results of Ordered Probit Model on Injury Severity

Variables Coefficient p-value 95% confidence interval
Crash speed 0.148 0.004 0.005 0.249
Taxi vehicle damage 0.569 0.004 0.185 0.952
TW damage 0.558 0.018 0.097 1.018
TW driver impairment level 1.042 0.000 0.675 1.410
2nd impact of driver 0.394 0.000 -0.038 0.826
3rd impact of driver 0.922 0.074* 0.419 1.425
u0 0.417 0.034 0.800
u1 2.144 1.678 2.611
u3 5.053 4.193 5.913
Number of crashes 248
McFadden's 0.299
LR chi2 169.30

4.3 ๋ชจํ˜•์˜ ํ•ด์„

์ˆœ์„œํ˜• ํ”„๋กœ๋น— ๋ชจํ˜•์„ ์ ์šฉํ•˜์—ฌ ์ถ”์ •๋œ ๋ณ€์ˆ˜๋Š” ํ•œ๊ณ„ํšจ๊ณผ๋ฅผ ํ†ตํ•ด ๋ชจํ˜• ํ•ด์„์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ํ•œ๊ณ„ํšจ๊ณผ๋Š” ๋…๋ฆฝ๋ณ€์ˆ˜์˜ ํ•œ ๋‹จ์œ„ ๋ณ€ํ™”๊ฐ€ ์ข…์†๋ณ€์ˆ˜(์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„)์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋‚˜ํƒ€๋‚ธ๋‹ค. ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„์— ๋Œ€ํ•œ ์ˆœ์„œํ˜• ํ”„๋กœ๋น— ๋ชจํ˜•์€ ๋น„์„ ํ˜•์ด๊ธฐ ๋•Œ๋ฌธ์—, ์ถ”์ •๋œ ๊ณ„์ˆ˜๋Š” ํ•œ๊ณ„ํšจ๊ณผ๋ฅผ ๋‚˜ํƒ€๋‚ด์ง€ ๋ชปํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐ ๋…๋ฆฝ๋ณ€์ˆ˜์— ๋Œ€ํ•œ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ผ๋Š” ์กฐ๊ฑด๋ถ€ ํ™•๋ฅ ์˜ ํŽธ๋ฏธ๋ถ„์„ ํ†ตํ•ด ํ•œ๊ณ„ํšจ๊ณผ๋ฅผ ๋„์ถœํ•œ๋‹ค. Table 3์€ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ์ถ”์ • ๋ชจํ˜•์„ ๋ฐ”ํƒ•์œผ๋กœ ๊ฐ ๋…๋ฆฝ๋ณ€์ˆ˜์— ๋Œ€ํ•œ ํ•œ๊ณ„ํšจ๊ณผ๋ฅผ ์ œ์‹œํ•œ ๊ฒƒ์ด๋‹ค.

Table 3. Marginal Probability Effects of Estimated Model

Variables Average Marginal Probability Effects
Average ๏ฝœchange๏ฝœ Complaint of pain Visible injury Incapacitating injury Fatality
TW driver impairment level 0.118 -0.216 -0.020 0.208 0.029
3rd impact of driver 0.105 -0.191 -0.018 0.184 0.025
Taxi vehicle damage 0.065 -0.118 -0.011 0.114 0.016
TW damage 0.063 -0.116 -0.011 0.111 0.015
2nd impact of driver 0.045 -0.082 -0.008 0.079 0.011
Crash speed 0.002 -0.003 -0.000 0.003 0.000

๋จผ์ €, ์‚ฌ๊ณ  ํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ณดํ–‰์ด ๋ถˆ๊ฐ€๋Šฅํ•  ๊ฒฝ์šฐ โ€˜ํ™œ๋™ ๋ถˆ๊ฐ€โ€™ ๋ฐ โ€˜์‚ฌ๋งโ€™ ํ™•๋ฅ ์ด ๊ฐ๊ฐ 20.8%, 2.9% ์ฆ๊ฐ€ํ•˜๊ณ , โ€˜๊ณ ํ†ต ํ˜ธ์†Œโ€™ ๋ฐ โ€˜์œก์•ˆ ๋ถ€์ƒโ€™ ํ™•๋ฅ ์ด ๊ฐ๊ฐ 21.6%, 2.0% ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Š” ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ํฌ๊ฒŒ ๊ฒฝ์ƒ(๊ณ ํ†ตํ˜ธ์†Œ, ์œก์•ˆ๋ถ€์ƒ)๊ณผ ์ค‘์ƒ(ํ™œ๋™ ๋ถˆ๊ฐ€, ์‚ฌ๋ง) 2๊ฐ€์ง€๋กœ ๋‚˜๋ˆ„๋ฉด, ์ค‘์ƒ ํ™•๋ฅ ์„ ๋†’์ด๊ณ , ๊ฒฝ์ƒ ํ™•๋ฅ ์„ ๋‚ฎ์ถ”๋Š” ๊ฒƒ์œผ๋กœ ํ•ด์„ํ•  ์ˆ˜ ์žˆ๋‹ค(Chung et al., 2014). ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ถ€์ƒ ์ •๋„๊ฐ€ ์‹ฌ๊ฐํ•˜์—ฌ, ์‚ฌ๊ณ  ํ˜„์žฅ์„ ์‹ ์†ํ•˜๊ฒŒ ๋Œ€ํ”ผํ•˜์ง€ ๋ชปํ•˜๋Š” ์œ„ํ—˜์„ฑ์„ ๊ณ ๋ คํ•  ๋•Œ ํƒ€๋‹นํ•œ ๊ฒฐ๊ณผ๋ผ๊ณ  ํŒ๋‹จ๋œ๋‹ค. ๋˜ํ•œ ํƒ์‹œ-์ด๋ฅœ์ฐจ ๊ฐ„ 1์ฐจ ์ถฉ๋Œ ์ดํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ 2์ฐจ ์ถฉ๊ฒฉ์ด ๋ฐœ์ƒํ•œ ๊ฒฝ์šฐ ํ™œ๋™ ๋ถˆ๊ฐ€ ๋ฐ ์‚ฌ๋ง ํ™•๋ฅ ์ด ๊ฐ๊ฐ 7.9%, 1.1% ์ฆ๊ฐ€ํ•˜๊ณ , 3์ฐจ ์ถฉ๊ฒฉ์ด ๋ฐœ์ƒํ•œ ๊ฒฝ์šฐ์—๋Š” ๊ฐ๊ฐ 18.4%, 2.5% ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚˜, 2์ฐจ ์ถฉ๊ฒฉ๋ณด๋‹ค 3์ฐจ ์ถฉ๊ฒฉ์— ๋Œ€ํ•œ ์ค‘์ƒ ํ™•๋ฅ ์ด ๋” ๋†’๋‹ค๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ์ด๋Š” ์ถฉ๊ฒฉ ํšŸ์ˆ˜๊ฐ€ ๋งŽ์„์ˆ˜๋ก ๋” ์‹ฌ๊ฐํ•œ ๋ถ€์ƒ์„ ์ž…์„ ๊ฒƒ์ด๋ผ๋Š” ์ƒ์‹์ ์ธ ํŒ๋‹จ๊ณผ ๋ถ€ํ•ฉํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํƒ์‹œ ํŒŒ์†์ด ๋ฐœ์ƒํ–ˆ์„ ๊ฒฝ์šฐ ํ™œ๋™ ๋ถˆ๊ฐ€ ๋ฐ ์‚ฌ๋ง ํ™•๋ฅ ์ด ๊ฐ๊ฐ 11.4%, 1.6% ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ์ด๋ฅœ์ฐจ ํŒŒ์†์ด ๋ฐœ์ƒํ–ˆ์„ ๊ฒฝ์šฐ์—๋„ ๊ฐ๊ฐ 11.1%, 1.5% ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰, ์ฐจ๋Ÿ‰์˜ ํŒŒ์†์ด ๋ฐœ์ƒํ–ˆ์„ ๊ฒฝ์šฐ ์ด๋ฅœ์ฐจ ์šด์ „์ž์—๊ฒŒ ์ „ํ•ด์ง€๋Š” ๋” ํฐ ์ถฉ๊ฒฉ์ด ๊ฐ€ํ•ด์งˆ ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์—, ์ฐจ๋Ÿ‰์˜ ํŒŒ์†์ด ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„์— ์˜ํ–ฅ์„ ๋ฏธ์นœ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์ถฉ๋Œ ์ง์ „ ํƒ์‹œ์˜ ์†๋„๋Š” ์—ฐ์†ํ˜• ๋ณ€์ˆ˜๋กœ์„œ, ํ•œ๊ณ„ํšจ๊ณผ๋ฅผ ํ•ด์„ํ•  ๋•Œ ๊ทธ๋ž˜ํ”„๋ฅผ ํ™œ์šฉํ•˜์—ฌ ํ•ด์„ํ•˜๋Š” ๊ฒƒ์ด ์šฉ์ดํ•˜๋‹ค(Chung et al., 2014). Fig. 1์€ ์ถฉ๋Œ ์†๋„์— ๋Œ€ํ•œ ํ•œ๊ณ„ ํšจ๊ณผ๋ฅผ ๋‚˜ํƒ€๋‚ธ ๊ฒƒ์œผ๋กœ, ์ด๋ฅผ ํ†ตํ•˜์—ฌ ์ถฉ๋Œ ์†๋„๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ํ™œ๋™ ๋ถˆ๊ฐ€ ๋ฐ ์‚ฌ๋ง ํ™•๋ฅ ์€ ์ฆ๊ฐ€ํ•˜๊ณ , ๊ณ ํ†ต ํ˜ธ์†Œ ๋ฐ ์œก์•ˆ ๋ถ€์ƒ ํ™•๋ฅ ์€ ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์„ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ์ถฉ๋Œ ์†๋„๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๋ถ€์ƒ ์ˆ˜์ค€์ด ๋†’์•„์งˆ ๊ฒƒ์ด๋ผ๋Š” ๊ธฐ์กด ์—ฐ๊ตฌ๊ฒฐ๊ณผ์™€ ๋ถ€ํ•ฉํ•œ๋‹ค(Chung et al., 2014).

Figure_KSCE_38_6_15_F1.jpg
Fig. 1.

Predicted Probabilities by Crash Speed

5. ๊ฒฐ ๋ก 

๋ณธ ์—ฐ๊ตฌ๋Š” ํƒ์‹œ ๋ธ”๋ž™๋ฐ•์Šค ์ž๋ฃŒ ๊ธฐ๋ฐ˜ ์ˆœ์„œํ˜• ํ”„๋กœ๋น—๋ชจํ˜•์„ ํ™œ์šฉํ•˜์—ฌ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด 248๊ฑด์˜ ๋ธ”๋ž™๋ฐ•์Šค ์˜์ƒ ์ž๋ฃŒ ๋ฐ ์ด์— ๋Œ€ํ•œ ์‚ฌ๊ณ  ๊ธฐ๋ก ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ, ์˜์ƒ ์ •๋ณด๋ฅผ ํ†ตํ•ด ํƒ์‹œ์™€ ์ด๋ฅœ์ฐจ์˜ ํŒŒ์†์—ฌ๋ถ€, ์ฃผํ–‰ ๋ฐฉํ–ฅ, ์ถฉ๋Œ ์†๋„, ์ถฉ๋Œ ์œ„์น˜, ์‚ฌ๊ณ  ํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ณดํ–‰์—ฌ๋ถ€, ๊ทธ๋ฆฌ๊ณ  2, 3์ฐจ ์ถฉ๊ฒฉ ์—ฌ๋ถ€ ๋“ฑ ๊ธฐ์กด ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ์—์„œ ์ˆ˜์ง‘ํ•  ์ˆ˜ ์—†์—ˆ๋˜ ์ƒˆ๋กœ์šด ์ธ์ž๋ฅผ ์ถ”๊ฐ€ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, ์ถฉ๋Œ ์ง์ „์˜ ํƒ์‹œ ์†๋„๊ฐ€ ๋†’์„์ˆ˜๋ก, ํƒ์‹œ ๋˜๋Š” ์ด๋ฅœ์ฐจ์˜ ํŒŒ์†์ด ๋ฐœ์ƒํ•œ ๊ฒฝ์šฐ, ์‚ฌ๊ณ  ํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ณดํ–‰์ด ๋ถˆ๊ฐ€๋Šฅํ•  ๊ฒฝ์šฐ, ๊ทธ๋ฆฌ๊ณ  2, 3์ฐจ ์ถฉ๊ฒฉ์œผ๋กœ ์‚ฌ๊ณ ๊ฐ€ ์ด์–ด์ง„ ๊ฒฝ์šฐ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋†’์ด๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํ•œ๊ณ„ํšจ๊ณผ ๋ถ„์„์„ ํ†ตํ•˜์—ฌ ์ด์ƒ์˜ ๋ณ€์ˆ˜๋“ค์ด ๋ชจ๋‘ ์ค‘์ƒ(ํ™œ๋™ ๋ถˆ๊ฐ€, ์‚ฌ๋ง) ํ™•๋ฅ ์„ ์ฆ๊ฐ€์‹œํ‚ค๊ณ , ๊ฒฝ์ƒ(๊ณ ํ†ตํ˜ธ์†Œ, ์œก์•ˆ๋ถ€์ƒ) ํ™•๋ฅ ์„ ๊ฐ์†Œ์‹œํ‚ค๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ ์‚ฌ๊ณ  ํ›„ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ๋ณดํ–‰์ด ๋ถˆ๊ฐ€๋Šฅํ•œ ๊ฒฝ์šฐ๊ฐ€ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ์˜ํ–ฅ์ธ์ž ์ค‘ ๊ฐ€์žฅ ์น˜๋ช…์ ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ๋‹ค์Œ์œผ๋กœ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ 3์ฐจ ์ถฉ๊ฒฉ, ํƒ์‹œ ํŒŒ์†, ์ด๋ฅœ์ฐจ ํŒŒ์†, ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ 2์ฐจ ์ถฉ๊ฒฉ์ด ๋ฐœ์ƒํ•œ ๊ฒฝ์šฐ, ๊ทธ๋ฆฌ๊ณ  ์ถฉ๋Œ ์ง์ „ ํƒ์‹œ์˜ ์†๋„ ์ˆœ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๊ฐ์†Œ ์ „๋žต ์ˆ˜๋ฆฝ์„ ์œ„ํ•œ ๊ธฐ๋ฐ˜ ์ •๋ณด๋กœ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.

๋ณธ ์—ฐ๊ตฌ๋Š” ํƒ์‹œ ๋ธ”๋ž™๋ฐ•์Šค ์˜์ƒ ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ด๋ฅœ์ฐจ ์šด์ „์ž์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ถ„์„์ž๊ฐ€ ๋ธ”๋ž™๋ฐ•์Šค ์˜์ƒ์˜ ์ „๋ฐฉ ์ƒํ™ฉ์„ ํ† ๋Œ€๋กœ ์‚ฌ๊ณ  ์ธ์ž๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๊ธฐ ๋•Œ๋ฌธ์—, ์ธก๋ฐฉ ๋ฐ ํ›„๋ฐฉ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์‚ฌ๊ณ  ์ƒํ™ฉ์„ ํŒŒ์•…ํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ๋˜ํ•œ ๊ธฐ์กด ๊ฒฝ์ฐฐ์กฐ์‚ฌ ์ž๋ฃŒ์—์„œ ์ˆ˜์ง‘ํ•  ์ˆ˜ ์—†์—ˆ๋˜ ์ƒˆ๋กœ์šด ์ธ์ž๋ฅผ ์ถ”๊ฐ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€์œผ๋‚˜, ํƒ์‹œ ๋‚ด๋ถ€์˜ ์ธ์ ํŠน์„ฑ์€ ํŒŒ์•…ํ•  ์ˆ˜ ์—†๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์กด์žฌํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ํ–ฅํ›„ ์—ฐ๊ตฌ์—์„œ๋Š” ์ฐจ๋Ÿ‰ ๋‚ด๋ถ€๋„ ์ดฌ์˜๊ฐ€๋Šฅํ•œ ์žฅ๋น„๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ฐจ๋Ÿ‰ ๋‚ด๋ถ€ ์šด์ „์ž ๊ฐœ์ธ ํ–‰ํƒœ๋ฅผ ๊ณ ๋ คํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ง„ํ–‰๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ๋ธ”๋ž™๋ฐ•์Šค ๊ธฐ๋ฐ˜ ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ, ํƒ์‹œ-์Šน์šฉ์ฐจ, ํƒ์‹œ-ํ™”๋ฌผ์ฐจ ๋“ฑ์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„๋„ ์ด๋ฃจ์–ด ์งˆ ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ, ์ฐจ๋Ÿ‰ ๋ธ”๋ž™๋ฐ•์Šค์˜ ์žฅ์ ์€ ๊ฐ€ํ•ด์ž์™€ ํ”ผํ•ด์ž์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ๊ตฌ๋ถ„์ด ๊ฐ€๋Šฅํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ๊ฐ€ํ•ด์ž์™€ ํ”ผํ•ด์ž ์ž…์žฅ์—์„œ์˜ ์‚ฌ๊ณ  ์‹ฌ๊ฐ๋„ ๋ถ„์„๋„ ํฅ๋ฏธ๋กœ์šด ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๊ตฌ์กฐ๋ฐฉ์ •์‹, ๋‹คํ•ญ๋กœ์ง“๋ชจํ˜• ๋“ฑ์˜ ๋ชจํ˜• ์ถ”์ • ๊ฒฐ๊ณผ์™€ ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜๋Š” ์—ฐ๊ตฌ๊ฐ€ ์ˆ˜ํ–‰๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.

Acknowledgements

๋ณธ ๋…ผ๋ฌธ์€ 2018๋…„๋„ ์ •๋ถ€(๊ตญํ† ๊ตํ†ต๋ถ€)์˜ ์žฌ์›์œผ๋กœ ๊ตญํ† ๊ตํ†ต๊ณผํ•™๊ธฐ์ˆ ์ง„ํฅ์›์˜ ์ง€์›์„ ๋ฐ›์•„ ์ˆ˜ํ–‰๋œ ์—ฐ๊ตฌ์ž„(No.18TLRP-B148386-01, ์‚ฌ์—…์šฉ ์ฐจ๋Ÿ‰์„ ์ด์šฉํ•œ ๋„๋กœ๊ตํ†ต ์ •๋ณด ์ˆ˜์ง‘ ๋ฐ ํ™œ์šฉ๊ธฐ์ˆ  ๊ฐœ๋ฐœ).

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