本文選題：交通需求預(yù)測 + 方式劃分��； 參考：《吉林大學(xué)》2015年碩士論文

【摘要】：隨著我國城鎮(zhèn)化和機(jī)動(dòng)化出行水平的提高，城市交通擁堵狀況不斷加劇。交通擁堵以及由此引發(fā)的交通事故和環(huán)境污染問題已經(jīng)影響到城市生活的效率和質(zhì)量。在擁堵治理策略上，多數(shù)國家已轉(zhuǎn)向以管理交通需求為主，增加交通供給為輔。但無論何種策略，在實(shí)施前，模擬和預(yù)測策略實(shí)施效果、評(píng)價(jià)策略可行性都是十分必要的。其中，方案效果評(píng)價(jià)的兩個(gè)重要指標(biāo)是預(yù)測實(shí)施后的各交通方式分擔(dān)率和交通網(wǎng)絡(luò)分配流量。傳統(tǒng)的“四階段”法將交通方式劃分和交通分配分為兩個(gè)獨(dú)立的階段分別進(jìn)行預(yù)測，，弱化了兩者之間的密切聯(lián)系和相互依賴關(guān)系，存在一些明顯不合理的地方，降低了預(yù)測的準(zhǔn)確性。因此，十分有必要研究交通方式劃分與分配組合模型，以提高預(yù)測精度，為交通行為分析與研究提供理論支持，為交通規(guī)劃方案、管理政策的評(píng)估提供依據(jù)。 為實(shí)現(xiàn)這一目的，首先采用實(shí)際調(diào)查數(shù)據(jù)對(duì)影響居民出行選擇的三方面因素（出行主體特性、出行特性和交通方式特性）的影響情況逐一進(jìn)行了分析，并根據(jù)影響因素作用機(jī)理的不同進(jìn)行分類，篩選出主要影響因素；其次，提出了城市交通超級(jí)網(wǎng)絡(luò)的構(gòu)造方法，描述了不同子網(wǎng)絡(luò)層應(yīng)具有的屬性值，以此為基礎(chǔ)，將各交通方式出行成本分解為出行時(shí)間、費(fèi)用、舒適度三個(gè)方面，逐一討論了各方式廣義出行成本的表征；此后，給出了組合模型的基本假設(shè)、自變量、因變量和約束條件，引用Logit隨機(jī)平衡理論給出了方式劃分與分配組合模型的平衡條件，構(gòu)造了變分不等式模型，并證明了模型的等價(jià)性及解的存在性，給出了具體求解步驟；最后，以山東省中北部G縣為例進(jìn)行了實(shí)例分析，闡述了模型的具體應(yīng)用方法，并將組合模型預(yù)測結(jié)果、傳統(tǒng)分階段模型預(yù)測結(jié)果及實(shí)際調(diào)查數(shù)據(jù)進(jìn)行比較，分析了模型的優(yōu)劣。 結(jié)果表明，在交通方式劃分方面，組合模型累計(jì)預(yù)測誤差比Logit模型低13.2%；在道路斷面車流量預(yù)測方面，組合模型的預(yù)測誤差為15.32%，比隨機(jī)用戶平衡模型降低了6.35%；在公交站間斷面客流量預(yù)測方面，組合模型的預(yù)測誤差為18.05%，比隨機(jī)用戶平衡模型降低了4.36%。組合模型在三個(gè)方面的預(yù)測精度都有一定程度的提高，具有良好的應(yīng)用價(jià)值。
[Abstract]:With the improvement of urbanization and motorized travel level in China, traffic congestion in cities is increasing. Traffic congestion and the resulting traffic accidents and environmental pollution have affected the efficiency and quality of urban life. In the strategy of congestion control, most countries have turned to the management of traffic demand and increase the supply of traffic. But no matter what kind of strategy, it is necessary to simulate and predict the implementation effect of the strategy and evaluate the feasibility of the strategy before it is implemented. Among them, the two important indexes of the project effect evaluation are the traffic mode sharing rate and the traffic network distribution flow after the implementation. The traditional "four stage" method divides the traffic mode and the traffic distribution. It is divided into two independent stages, which weaken the close relations and interdependence between the two. There are some obvious and unreasonable places, which reduce the accuracy of the prediction. Therefore, it is necessary to study the model of traffic mode division and distribution combination to raise the accuracy of prediction and provide a rational analysis and research for traffic behavior. Support is the basis for traffic planning and management policy evaluation.
In order to achieve this goal, first of all, the actual survey data are used to analyze the influence of three factors (travel characteristics, travel characteristics and traffic characteristics) on the travel choice of residents, and the main influencing factors are selected according to the different mechanism of influence factors. Secondly, the urban intersection is put forward. According to the construction method of super network, the attribute values of different sub network layers should be described. Based on this, the travel cost is decomposed into three aspects of travel time, cost and comfort, and the characterization of the generalized travel cost is discussed one by one. After that, the basic assumptions, variables, variables, and variables of the combined model are given. Constraint conditions, the equilibrium condition of mode division and distribution combination model is given by using Logit stochastic equilibrium theory. A variational inequality model is constructed. The equivalence of the model and the existence of the solution are proved. The concrete solution is given in the case of G County in the middle north part of Shandong Province, and the concrete needs of the model are expounded. By using the method, the prediction results of the combined model, the traditional model and the actual survey data are compared, and the advantages and disadvantages of the model are analyzed.
The results show that the cumulative prediction error of the combined model is 13.2% lower than that of the Logit model, and the prediction error of the combined model is 15.32%, which is 6.35% lower than that of the random user equilibrium model. The prediction error of the combined model is 18.05%, and the prediction error of the combined model is 18.05%, and the ratio of the combined model is 18.05%. The stochastic user equilibrium model reduces the prediction accuracy of the 4.36%. combination model in three aspects to a certain extent, and has good application value.

【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：U491.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 吳紅兵,陳義華;混合交通方式劃分與交通分配聯(lián)合模型[J];系統(tǒng)工程;2005年07期

2 宗芳;雋志才;;基于活動(dòng)的出行方式選擇模型與交通需求管理策略[J];吉林大學(xué)學(xué)報(bào)(工學(xué)版);2007年01期

3 黃樹森;宋瑞;陶媛;;大城市居民出行方式選擇行為及影響因素研究——以北京市為例[J];交通標(biāo)準(zhǔn)化;2008年09期

4 殷煥煥;關(guān)宏志;;基于BP神經(jīng)網(wǎng)絡(luò)的居民出行方式選擇模型[J];交通信息與安全;2011年03期

5 鮮于建川;雋志才;朱泰英;;基于貝葉斯網(wǎng)絡(luò)的出行選擇行為分析[J];交通運(yùn)輸系統(tǒng)工程與信息;2011年05期

本文編號(hào)：1878187