한국ITS학회 논문지 (The Journal of The Korea Institute of Intelligent Transport Systems)

  • 제14권4호
  • /
  • Pages.62-72
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  • 2015
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  • 1738-0774(pISSN)
  • /
  • 2384-1729(eISSN)
한국ITS학회 (The Korea Institute of Intelligent Transport Systems)
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고령자 통행시간예산의 영향요인 규명에 관한 연구

A Study on the Key Factors Affecting Travel Time Budget for Elderly Pedestrians

  • 최성택 (홍익대학교 과학기술연구소) ;
  • 김수재 (홍익대학교 도시계획과) ;
  • 장진영 (홍익대학교 도시계획과) ;
  • 이향숙 (인천대학교 동북아물류대학원) ;
  • 추상호 (홍익대학교 도시공학과)
  • 투고 : 2015.06.09
  • 심사 : 2015.07.30
  • 발행 : 2015.08.31
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초록

2000년대에 들어 급속한 고령화 사회로 접어든 현 시점에 교통계획 및 수요예측의 관점에서 고령자가 차지하는 비중은 매우 높아지고 있다. 따라서 고령자 그룹의 통행 행태를 분석하고 수요를 추정하는 별도의 과정이 요구된다. 본 연구는 SUR모형을 활용해 고령자의 목적별 통행시간예산의 영향요인을 규명하였다. 통행시간예산은 통행수단의 발달과는 상관없이 하루 약 1시간 정도로 할당된다는 점에 비추어 볼 때, 각 목적별 통행의 영향요인을 규명하기 위해서는 오차항간의 상관성을 고려하는 SUR모형이 적합하다. 분석 결과, 여가목적 통행의 비중이 매우 높으며 개인, 가구, 도시시설, 교통 인프라 등 다양한 요인에 의해 통행시간예산이 영향을 받는 것으로 나타났다. 특히, 여가목적과 관련된 노유자 시설, 운동 시설, 종교 시설 등이 통행시간예산과 양(+)의 상관관계를 갖는 것으로 나타났다. 또한 특정 직업에 종사하지 않거나 월 소득이 낮은 가구에 속한 고령자일수록 사회 경제적 활동의 빈도가 낮아지는 것으로 분석되었다. 이러한 결과는 고령자의 장래 통행행태를 예측하고 수요를 예측하는데 있어 많은 시사점을 제공할 것으로 기대한다.

Nowadays the issue of aging society has received considerable critical attention, especially in transportation planning and demand forecasting. This study identified the factors related to travel time budget for elderly by purpose using seemingly unrelated regression model (SUR model). The SUR model is suitable when error terms of each equation are assumed to be correlated across the equations in terms of travel time budget which is constant in 2 hours per day commonly. The results showed that elderly's travel time budget was affected by individual, household, urban facility and transportation service. The leisure travel comprised a large proportion of total travel time and had a positive relationship with elderly, sports, religious facilities. Moreover, the elderly who had low income or unemployed person had low frequency of social activity such as leisure, shopping and business. This study can provide a comprehensive implications of forecasting the future travel demand and analyzing the travel behavior.

키워드

참고문헌

  1. S. H. Choo, J. I. Song and B. S. Kwon, "Exploring Key Factors Influencing Travel of the Elderly: A Case of Seoul Metropolitan Area", Journal of Korea Planners Association, vol. 46, no. 2, pp.235-250, Apr. 2011.
  2. S. E. Seoh, J. H. Jeong and S. G. Kim, "Analysis of Elderly Travel Characteristics and Travel Behavior with Daily Activity Schedules (the Case of Seoul, Korea)", Journal of Korean Society of Transportation, vol. 24, no. 5, pp.89-108, Aug. 2008.
  3. D. S. Yun and Y. H. Ahn, "Analysis of the Elderly's Travel Characteristics and Travel Behavior", Journal of Korea Planners Association, vol. 37, no. 7, pp.91-107, Dec. 2003.
  4. J. H. Rho, "Transportation Planning - Travel Demand Theory and Model, 2nd edition", Nanam, 2012.
  5. Y. Zahavi, "UMOT Project", Prepared for US Department of Transportation, Washinton DC and Ministry of Transport, Federal Republic of Germany, Bonn. Report DOT-RSPA-DPB-20-79-3, Aug. 1979.
  6. P. L. Mokhtarian, "How derived is the demand for travel? Some conceptual and measurement considerations", Transportation Research A, pp.695-719, 2001.
  7. C. Marchetti, "Anthropological invariants in travel behavior, Technological Forecasting and social change", pp.75-88, 1994.
  8. M. Fraire, "Multiway data analysis for comparing time use in different countries-application to time budgets at different stages of life in six european countries", Electronic International Journal of Time Use Research, pp.88-109, 2006.
  9. D. Levinson and A. Kumar, "Activity, travel and allocation of time", APA Journal Autumn, pp. 458-470, 1995.
  10. G. Barnes, "Population and Employment Density in Large U.S Cities", Minesota Department of Transportaion, 2001.
  11. A. Schafer, D. G. Victor, "The future mobility of Worlk Population", Transport Research A, pp. 171-205, 2000.
  12. L. S. Prendergast and R. D. Williams, "Individual travel budgets", Transportation Research A, pp.39-46, 1981.
  13. S. H. Choo and S. W. Na, "Exploring Characteristics on travel time budget: A Case study of Seoul Metropolitan Area", Journal of Korean Urban Management Association, vol. 24, no.2, pp.3-22, Jun. 2011.
  14. Y. D. Park, An Analysis of the Affective Factors in Travel Time Budget, Master's degree, Hanyang University, 2007.
  15. T. H. Kim, J. J. Park, K. Y. Lee and Y. D. Park, "Analysis and Estimation of Factors Affecting Travel Time Budget", Journal of Korean Society of Road Engineers, vol. 11, no. 3, pp.13-21, Sep. 2009.
  16. I. J. Jeon, A Study on the Factors Affecting Leisure Time Budget, Master's degree, Hanyang University, 2010.
  17. D. Metz, "Travel Time Constraints in Transport Policy", Proceedings of the Institution of Civil Engineers, pp.99-105, 2004.
  18. Z, Arnold, "An efficient method of estimating seemingly unrelated regression equations and tests for aggregation bias", Journal of the American Statistical Association, no. 58, pp.348-368, 1962.
  19. K. W. Shin and K. C. Choi, "Analyzing the Relationship Between Precipitation and Transit Ridership Through a Seemingly Unrelated Regression Model", Journal of Korean Society of Transportation, vol. 32, no. 2, pp.83-92, Apr. 2014. https://doi.org/10.7470/jkst.2014.32.2.083
  20. C. F. Baum, An Introduction to Modern Econometrics Using Stata, Stata Press, 2006.
  21. I. S. Min and P. S. Choi, Advanced Panel Data Analysis, The Korean Association of STATA, Jiphil Press, 2012.

피인용 문헌

  1. Identification of Key Factors of Travel Time Budget by Mode in Seoul: Using Seemingly Unrelated Regression Model vol.15, pp.3, 2016, https://doi.org/10.12815/kits.2016.15.3.023
  2. Analysis of Factors Affecting Travel Time Change Using the Time Use Survey Data in Seoul vol.17, pp.1, 2018, https://doi.org/10.12815/kits.2018.17.1.01