在路徑衝突下行人移動行為模式之研究

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Title:	在路徑衝突下行人移動行為模式之研究
Other Titles:	Study of pedestrian movement behavior model based on pathways conflict
Authors:	陳孝慈;Chen, Hsiao-Tzu
Contributors:	淡江大學運輸管理學系碩士班范俊海;Fan, Chun-Hai
Keywords:	行人移動行為;反應區域;格子;邏輯斯迴歸;Pedestrian Movement Behavior;Responsive Area;Lattice;Logistic Regression
Date:	2013
Issue Date:	2014-01-23 14:07:54 (UTC+8)
Abstract:	本研究在路徑衝突的條件下，探討行人移動行為的特性，藉由標記衝突主角及周遭影響對象各時點之座標位置，利用格子的概念，將資訊匯入處理平台中，並加以分析以了解行人移動行為。而在資訊相同之條件下，本研究針對不同之處理平台進行相關研究，主要分為矩形及扇形兩種平台，其設定概念有所不同，包括：劃分空間變數個數及行人領地範圍之設定；之後利用SPSS軟體進行多元邏輯斯迴歸之模式檢定，透過適配度統計量及類R2指標進行分析，得到研究結果以矩形平台作為模式之處理平台較為合適。而在此行人移動行為中，當衝突情況發生時，行人反應區域約落在0.97公尺的環形帶狀區域內，與他人之間的距離範圍約集中在58.21~136.17公分之間，而此區域之距離與行人的步行速度則沒有明顯的相關性。本研究將模式應用於預測路徑衝突情形下之行人移動行為，其預測率為78%，倘若屏除因行人心理因素所產生之特殊行走行為，則利用本模式預測行人移動行為仍具有其可行性。 In this study, taking the pathways conflict situations as a condition to construct a model of pedestrian movement behavior, by marking coordinates of conflict pedestrian and the people who around the pedestrian at each time and place, using the concept of the lattice, the range of the information to import information and analyzed in order to understand the moving behavior of pedestrians. However, under the same conditions of information, this study research different processing platforms, including rectangular platform and fan-shaped platform, which setting concepts are different, including dividing the number of space variables and setting pedestrian territorial range, then using SPSS software for multiple logistic regression model calibration by analyzing Goodness-of-fit and Pseudo R-Square. Research result is taking rectangular platform as the processing platform is more appropriate. In this pedestrian movement behavior, when a conflict occurs, the responsive area is contained in the endless belt shape area which about 0.97 meters. The distance between pedestrian about 58.21 cm to 136.17 cm, the distance and pedestrian walking speed in this area does not have significant correlation. In this study, the model used to predict the pedestrian movement behavior, the predicted rate of 78%. If you dismiss the special walking behavior due to psychological factors of the pedestrian, then use this model to predict pedestrian movement behavior does have its feasibility.
Appears in Collections:	[Graduate Institute & Department of Transportation Management] Thesis

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