都市鏈結旅次多項決策行為之兩階段區別分析研究－以台北都會區為例

Application of Two-Step Discriminant Model on Multi-Choice Urban Chained Travel Analysis － A Case Study of Taipei Metropolitan Area

楊士賢(Shih-Hsien Yang)

指導教授 ： 廖祐君

中原大學/工學院/土木工程研究所/碩士(2003年)

https://doi.org/10.6840/cycu200300550

摘要

都會區內之通勤個體，為了在有限之時間預算內參與既定之活動，並使其在參與活動之過程中得到最大之總效用，傾向將旅次以鏈結之方式進行，以減少旅行時間耗費所帶來之負效用。個體在決策活動排置及旅次鏈結時，受到能力限制、權限限制及聯結限制之影響，而決定不同之活動/旅運型態。本研究以活動理論為基礎，並因旅次鏈之特性以家旅程為分析單位。研究之基本流程可分為（1）訂定家旅程類別（2）擷取影響特徵（3）模式建構等三部分，以分析通勤個體之複雜旅運行為。
傳統之旅運行為研究多以羅吉特模式推估個體可能選擇之方案，由於羅吉特模式為一機率模式，無法正確得知每一家旅程型態之效用函數。本研究以區別分析方法建構通勤者之活動/旅運型態模式，不僅可以得知各個家旅程型態之效用函數，更可藉由多重羅吉特函數將其轉為被選機率，而推得個體可能選擇之家旅程型態。在影響變數選擇方面，除了沿用先前研究之個人、家戶社經特性及家戶成員間互動特性外，本研究嘗試以群落分析方法，強調時窗特性對於個體活動排置之影響，並以兩階段模式建構之方式，呈現出時窗特性對於模式推估準確度改善之差異。
利用89年台北都會區住戶交通旅次調查資料之模式建構結果顯示，除了先前選取之影響變數具有顯著之影響力外，時窗影響因子扮演著重要之角色。此外，由於家旅程型態內之旅次數目越多，排置情形也越複雜，錯估之情形通常發生在複雜度類似之家旅程型態之中。本研究透過群落分析之方法，將異質個體之時窗特性納入類別考量中，結果顯示，確實能將複雜度類似之家旅程型態做有效之判別，減少錯估之情形發生。

關鍵字

區別分析 ； 效用函數 ； 群落分析 ； 旅次鏈 ； 旅運行為

並列摘要

In order to participate in planned activities within the limited time budget and to maximize the total utility, the urban commuters tend to link trips into trip-chains to reduce negative effects induced by wasteful travel. The trip makers’ arrangements of daily activities and trip chains mainly depend on capability constraints, coupling constraints, and authority constraints; therefore individuals make different activity/travel patterns accordingly. This study was based on the activity theory and incorporated the concept of trip chaining by using “tours” as analysis units instead of trips. The process of research was comprised of three successive sections: (1) pattern identification, (2) influence factor specification and (3) model development. The study was expected to present additional details useful to understand the complicated travel behavior of urban commuters.
The conventional approach in travel behavior studies mostly use the logit models to estimate the possible choices of individuals. Since the logit model is probability-based, the utility function of each tour pattern is hard to formulate. By using discriminant analysis, not only can the utility function of each tour pattern been obtained, but also the possible choices been recognized by using multi-logit functions. The choice of variables in the model was guided by previous empirical studies. In addition to the socio-economic characteristics and the household-member interrelationships, we used the cluster analysis to emphasize that individual’s trip scheduling was constrained by time window factors. Based on these hypotheses, the two-step model was established to explore the effect of time windows on improving the model accuracies.
By using the travel data collected in Taipei metropolitan area in year 2000, the modeling results showed that in addition to the conventional attributes, the time window variables played an important role in category discrimination. Furthermore, the complexity of trip scheduling growed with the increasing trip legs in the tour, and the biased estimation was therefore frequently generated between patterns with similar complexity. Acknowledging this problem, the cluster analysis was adopted to revise tour patterns by joint consideration of trip scheduling and time windows; the second-step modification largely rectified the problems mentioned above and the results were satisfied.

並列關鍵字

cluster analysis ； travel behavior ； discriminant analysis ； trip chaining ； utility function

參考文獻

23. 黃俊勳，民國90年，應用隸屬函數及倒傳遞網路於都市通勤旅程預估模式之研究，私立中原大學土木工程學系碩士論文。

8. 謝幼屏，民國81年，個體可及效益與行旅／活動行為之研究，國立交通大學土木工程系碩士論文。

14. 陳宥欽，民國88年，個體選擇模式效用函數之研究－以電動機車為例，國立成功大學交通管理學系碩士論文。

18. 方菀萍，民國89年，個體選擇模式選擇集合之研究—以國道客運北高路線為例，國立成功大學交通管理學系碩士論文。

26. Adler, T. and M. Ben-Akiva, (1976) “Joint choice model for frequency, destination, and travel mode for shopping trips,” Transportation Research Record 569, pp.24-31.