發(fā)布時(shí)間：2018-10-10 07:53

【摘要】：近年來(lái),城市社會(huì)經(jīng)濟(jì)的快速發(fā)展及機(jī)動(dòng)車保有量的不斷增加,導(dǎo)致行車難、停車難等問(wèn)題日益突顯,交通擁堵問(wèn)題已經(jīng)給人們生活帶來(lái)了極大的不便。交通擁堵現(xiàn)象是交通流在特定時(shí)間、空間下所表現(xiàn)的一種狀態(tài),其本質(zhì)是出行需求主體——大量個(gè)體出行者出行行為決策實(shí)施宏觀涌現(xiàn)的結(jié)果。目前的研究大多建立在出行者同質(zhì)的基礎(chǔ)上,忽略了出行者之間的差異性;且集中在單方面的決策行為上,對(duì)于兩種及兩種以上決策行為的聯(lián)合決策研究較少。由此可見,有必要對(duì)通勤出行下的出行聯(lián)合決策行為進(jìn)行研究,分析不同出行群體的出行聯(lián)合決策行為,為制定精細(xì)化的交通需求管理策略提供科學(xué)依據(jù)。首先,在分析出行決策影響因素的基礎(chǔ)上,闡述了出行者的異質(zhì)性,并對(duì)出行者差異化分類的方法進(jìn)行對(duì)比分析;通過(guò)行為調(diào)查和意向調(diào)查獲取基礎(chǔ)調(diào)查數(shù)據(jù),在對(duì)調(diào)查數(shù)據(jù)的有效性和可靠性進(jìn)行檢驗(yàn)的基礎(chǔ)上,對(duì)出行者的社會(huì)經(jīng)濟(jì)屬性進(jìn)行統(tǒng)計(jì)分析,同時(shí)利用聚類分析方法對(duì)出行者進(jìn)行人群歸并,形成出行者差異化的分類結(jié)果。其次,根據(jù)出行者差異化的分類結(jié)果,對(duì)不同出行群體的出行特征進(jìn)行歸納分析,采用主成分分析法確定通勤出行下不同出行群體的參照點(diǎn)構(gòu)成因素為行程時(shí)間和到達(dá)時(shí)間;利用不確定理論構(gòu)建行程時(shí)間及到達(dá)時(shí)間的參照點(diǎn)函數(shù),并利用參照點(diǎn)及風(fēng)險(xiǎn)偏好系數(shù)的聯(lián)系,構(gòu)建風(fēng)險(xiǎn)偏好系數(shù)函數(shù),同時(shí)結(jié)合貝葉斯更新模型對(duì)出行前及出行后的參照點(diǎn)及風(fēng)險(xiǎn)偏好系數(shù)函數(shù)進(jìn)行更新。然后,從出行行為形成及響應(yīng)過(guò)程剖析出行選擇行為決策機(jī)理,并對(duì)出行聯(lián)合決策進(jìn)行界定;根據(jù)出行者的聯(lián)合決策過(guò)程,選取前景理論對(duì)通勤出行聯(lián)合決策進(jìn)行分析;建立用于描述各備選方案可能發(fā)生結(jié)果的價(jià)值函數(shù)、感知概率函數(shù)及權(quán)重函數(shù),將計(jì)算所得的價(jià)值函數(shù)、感知概率函數(shù)及權(quán)重函數(shù)帶入計(jì)算公式中,計(jì)算得到各備選方案的前景值。最后,選取西安市的路網(wǎng)作為實(shí)例,調(diào)查得到路網(wǎng)的基礎(chǔ)數(shù)據(jù),在出行者差異化分類的基礎(chǔ)上,構(gòu)建基于前景理論的出行聯(lián)合決策行為模型,分析在通勤出行時(shí)不同出行群體的出行聯(lián)合決策行為,結(jié)果表明建立的出行決策模型與實(shí)際結(jié)果較為符合,可以準(zhǔn)確地描述不同類型出行群體的出行決策行為。
[Abstract]:In recent years, with the rapid development of urban social economy and the increasing number of motor vehicles, the problems such as driving difficulties and parking difficulties have become increasingly prominent. Traffic congestion has brought great inconvenience to people's lives. Traffic congestion is a state of traffic flow in a specific time and space, and its essence is the result of macro emergence of travel behavior decision of a large number of individual travelers. Most of the current studies are based on the homogeneity of travelers, ignoring the differences between travelers, and focused on unilateral decision-making behavior, and for two or more kinds of decision-making behavior joint decision-making research is less. Therefore, it is necessary to study the travel joint decision-making behavior under commuter travel, analyze the travel joint decision-making behavior of different travel groups, and provide scientific basis for the formulation of fine traffic demand management strategy. First of all, on the basis of analyzing the influencing factors of travel decision, this paper expounds the heterogeneity of travelers, and compares the methods of passenger differentiation classification; obtains the basic survey data through behavior survey and intention survey. On the basis of testing the validity and reliability of the survey data, this paper makes a statistical analysis on the social and economic attributes of the travelers, and at the same time uses the method of cluster analysis to merge the travelers and form the differentiated classification results of the travelers. Secondly, according to the classification results of different travel groups, the travel characteristics of different travel groups are summarized and analyzed. The principal component analysis method is used to determine that the reference points of different travel groups under commuting travel are travel time and arrival time. The reference point function of travel time and arrival time is constructed by using uncertainty theory, and the risk preference coefficient function is constructed by using the relation between reference point and risk preference coefficient. At the same time, the reference points and risk preference coefficient functions before and after travel are updated with Bayesian updating model. Then, the decision-making mechanism of trip choice behavior is analyzed from the process of trip behavior formation and response, and the travel joint decision is defined. According to the joint decision process of travelers, the prospect theory is selected to analyze the joint decision making of commuting trip. The value function, perceptual probability function and weight function are established to describe the possible results of each alternative scheme, and the calculated value function, perceptual probability function and weight function are introduced into the calculation formula. The foreground value of each alternative is calculated. Finally, the road network in Xi'an is selected as an example, and the basic data of the road network are investigated, and based on the differentiation classification of travelers, a travel joint decision behavior model based on prospect theory is constructed. The travel decision behavior of different travel groups during commuting is analyzed. The results show that the established travel decision model is in good agreement with the actual results and can accurately describe the travel decision behavior of different types of travel groups.
【學(xué)位授予單位】：長(zhǎng)安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U491

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