인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
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지원사업
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커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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초록·키워드
This study emphasizes improved techniques for analyzing TDM policies by increasing the level of details of traditional four-step transportation demand forecasting method. A desirable model needs to analize any changes of travel pattern affected by TDM measures. For this purpose, a micro representation network coding and multi-class traffic assignment algorithm are proposed. The study also emphasized the need of system-wide analysis for analyzing large-scale TDM policies. If TDM policies is expected to affect citywide network beyond the target area, the focusing approach is recommended for the concerning sub-area analysis. The focusing method makes possible to analyze not only sophisticated effects on the sub-area but also system-wide effects as the whole city simultaneously. The results of the focusing approach based on the four-step forecasting method can be used as basic data for evaluating TDM policies. For such evaluation, system-wide measurements of effectiveness are needed. This study suggests five system-wide measurements of determining the effectiveness of alternative TDM policies such as average trip distance, average travel time, average space mean speed, average volume-capacity ratio and average monetary cost. They can be used as critical indices in a TDM policy making process viewed from system-wide perspective of the effectiveness. This study analyzes the impacts of congestion charging and 5-day cycle car-using restriction policies appled for Yoi Island in Seoul, Korea as a case study by using myopic (windowing) and system-wide (focusing) analysis. As a result, the study shows that the myopic analysis can guide to wrong policy decisions. Therefore, the focusing method should be adopted for getting a better forecasting results of area-wide impacts of TDM.
본문·목차
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UCI(KEPA) : I410-ECN-0101-2009-531-018561590
