本文關(guān)鍵詞：基于出行活動(dòng)的城市居民低碳交通出行模型及算法　出處：《北京交通大學(xué)》2015年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 低碳出行 交通調(diào)查 出行結(jié)構(gòu) 出行效益 出行活動(dòng) 出行行為選擇

【摘要】：隨著社會(huì)的發(fā)展,人類消耗的能源和產(chǎn)生的污染物逐年上升,已經(jīng)危害到全球生態(tài)環(huán)境與人類生活安全。國(guó)家能源戰(zhàn)略和國(guó)家應(yīng)對(duì)氣候變化規(guī)劃都提出了對(duì)能源消耗和碳排放量的約束要求。交通運(yùn)輸活動(dòng)能源使用量大、排放強(qiáng)度高,是城市能源和污染物排放的主要來(lái)源,也成為實(shí)現(xiàn)節(jié)能減排的重要領(lǐng)域。不同交通方式的能耗和排放存在較大差異,出行結(jié)構(gòu)的優(yōu)化對(duì)于降低能耗和污染物排放具有重要作用。若北京出行結(jié)構(gòu)模式轉(zhuǎn)變?yōu)橐攒壍澜煌橹鞯哪Ｊ?能源消耗、污染物和碳排放分別能夠?qū)崿F(xiàn)降低10%-50%,對(duì)于環(huán)境改善將起到積極作用。因此,解析交通行為,研究基于能源環(huán)境約束的出行結(jié)構(gòu)優(yōu)化調(diào)整,對(duì)于積極應(yīng)對(duì)政府對(duì)能耗排放的約束考核,滿足對(duì)藍(lán)天白云的期許具有重要的現(xiàn)實(shí)意義,對(duì)于完善出行結(jié)構(gòu)及出行行為研究方法也具有推動(dòng)作用。本論文分別從宏觀的出行結(jié)構(gòu)優(yōu)化、中觀的出行活動(dòng)調(diào)整、微觀的交通方式選擇三個(gè)方面研究基于低碳目標(biāo)的出行結(jié)構(gòu)和出行行為優(yōu)化調(diào)整的理論與方法。為了支持模型構(gòu)建,進(jìn)一步拓展研究了出行行為調(diào)查技術(shù)和多源數(shù)據(jù)分析方法。論文的主要內(nèi)容包括以下4方面:(1)基于多源異構(gòu)數(shù)據(jù)的交通出行行為調(diào)查技術(shù)和數(shù)據(jù)分析方法。分析了出行行為調(diào)查方法的優(yōu)缺點(diǎn)和適用性,構(gòu)建以入戶調(diào)查為核心,道路流量、GPS定位、手機(jī)APP為校核,手機(jī)定位數(shù)據(jù)、公共交通調(diào)查、出租汽車調(diào)查為互補(bǔ),意愿調(diào)查為共生關(guān)系的出行者交通出行綜合調(diào)查體系。對(duì)調(diào)查獲取數(shù)據(jù)特征進(jìn)行分析,針對(duì)多源數(shù)據(jù),給出加權(quán)擴(kuò)樣和綜合校核的數(shù)據(jù)分析技術(shù)路線,并以北京市第四次全市交通綜合調(diào)查為例,進(jìn)行了調(diào)查項(xiàng)目設(shè)置和多源數(shù)據(jù)分析的實(shí)證研究。(2)基于低碳目標(biāo)的城市交通出行結(jié)構(gòu)優(yōu)化模型研究。從宏觀出行結(jié)構(gòu)調(diào)整目標(biāo)層面,以降低碳排放和提高政府交通建設(shè)資金投入產(chǎn)出比為目標(biāo),構(gòu)建基于社會(huì)成本投入的城市交通出行結(jié)構(gòu)優(yōu)化模型。將居民出行社會(huì)效益作為模型的目標(biāo)函數(shù),將能耗、排放降低水平、公共交通滿載率等作為約束條件,使用分枝定界法對(duì)模型進(jìn)行求解。開(kāi)展實(shí)證研究,分析北京市出行結(jié)構(gòu)、出行費(fèi)用、政府投資、能耗和排放約束等指標(biāo)數(shù)據(jù),經(jīng)模型測(cè)算得到低碳目標(biāo)下的城區(qū)最優(yōu)出行結(jié)構(gòu)。(3)基于居民出行活動(dòng)的出行組合鏈預(yù)測(cè)模型研究。首先分析居民一日出行數(shù)據(jù),將出行活動(dòng)和交通方式按照發(fā)生序列串聯(lián)起來(lái),構(gòu)成組合鏈,組合鏈包含一日活動(dòng)序列、每次活動(dòng)目的、采取的交通方式等信息。而后對(duì)組合鏈進(jìn)行編碼,轉(zhuǎn)化計(jì)算機(jī)能夠識(shí)別和計(jì)算的0-1代碼模式。之后應(yīng)用神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)模型,通過(guò)訓(xùn)練數(shù)據(jù)對(duì)組合鏈模型進(jìn)行模擬訓(xùn)練,預(yù)測(cè)居民出行活動(dòng),獲取出行總量變化。最后應(yīng)用模型開(kāi)展實(shí)證分析,對(duì)人均收入加倍及取消小汽車搖號(hào)措施進(jìn)行分析,測(cè)算居民出行量和交通碳排放量的變化。(4)基于低碳政策的個(gè)體出行者交通方式選擇模型研究。應(yīng)用北京市第四次交通綜合調(diào)查數(shù)據(jù),分析影響個(gè)體進(jìn)行交通方式選擇的因素,構(gòu)建基于Mixed Logit模型的個(gè)體出行者交通方式選擇模型,進(jìn)行基于優(yōu)化退火算法的模型參數(shù)求解。開(kāi)展實(shí)證分析,對(duì)擁堵收費(fèi)和公交提高運(yùn)行速度兩項(xiàng)措施對(duì)出行方式轉(zhuǎn)變和碳排放量變化效果進(jìn)行預(yù)測(cè)和評(píng)估分析。
[Abstract]:With the development of society, the human consumption of energy and pollutants increased year by year, has been harmful to the safety of ecological environment and human life world. The national energy strategy and the national climate change plan are put forward on energy consumption and carbon emissions constraints. Transport activities using a large amount of energy, the emission intensity is high. The main source of city energy and pollutant emissions, has also become an important field for energy conservation. There is a big difference between the energy consumption and emissions of different transport modes, optimization of travel structure plays an important role in reducing energy consumption and pollutant discharge. If the energy consumption changes of Beijing travel structure model to track traffic patterns, pollutants and carbon emissions can be reduced to 10%-50%, to improve the environment will play a positive role. Therefore, analysis of traffic behavior, based on energy and environmental constraints Optimization and adjustment of travel structure, to actively respond to the government on the assessment of energy consumption and emissions constraints, has important practical significance to meet the expectations of the blue sky and white clouds, but also play an important role in improving the travel structure and travel behavior research methods. This paper respectively from the macro meso structure optimization of travel, travel activities, study three aspects of selection the microscopic traffic model structure and travel behavior optimization theory and method of adjustment based on low carbon target. In order to build support model, to further expand the research on travel behavior survey technology and multi-source data analysis methods. The main contents of this paper include the following 4 aspects: (1) travel behavior survey and data analysis method of multi-source heterogeneous technology based on the data analysis. The advantages and disadvantages and the applicability of the investigation methods of travel behavior and the household survey as the core, road traffic, construction of GPS positioning, hand APP check, the mobile phone location data, public traffic survey, car rental survey to complement each other, the survey for the symbiotic relationship between traveler traffic comprehensive survey system. The data obtained were analyzed according to the characteristics of investigation, multi-source data, nuclear data gives weighted sampling expansion and comprehensive analysis of technical route, and in Beijing city fourth times the city's traffic survey as an example, makes an empirical research on the investigation and analysis of the project settings and multi-source data. (2) research of traffic structure optimization model based on the goal of low carbon city. From the macro travel structure adjustment target level, to reduce carbon emissions and improve government transportation construction funds input-output ratio as the goal, to build traffic the travel structure optimization model of social cost investment. Based on the city residents social benefit as the objective function, the model will reduce energy consumption, emission level, public traffic load ratio As the constraints, the model was solved using branch and bound method. To carry out empirical research, analysis of Beijing city travel structure, travel cost, government investment, energy consumption and emission constraint index data, the model estimates obtained in optimal travel structure of low carbon target. (3) model of the combination of travel chain residents travel activities based on the prediction analysis of residents. First day of travel data, travel and transportation activities in accordance with the sequence together, constitute a combination of chain, chain combination comprises a day activity sequence, each event to take the information traffic way. And then the encoding of the combination of transformation chain, the computer can recognize and calculate the 0-1 code mode after the application of neural network prediction model, through simulation training of combination chain model training data, predict the residents travel activities, access to travel amount changes. Finally the application of model To carry out the empirical analysis, the per capita income doubled and cancel the car Yaohao measures for analysis, measure changes in residents travel and traffic emissions. (4) low carbon policy individual traveler traffic mode choice model based on the application of data traffic. A comprehensive survey of fourth in Beijing City, analysis the influence factors of traffic mode choice of the individual Mixed Logit, the construction model of the individual traveler traffic mode choice model based on the solution of parameter optimization algorithm based on annealing. Carry out empirical analysis, the effect of change speed two measures on travel mode change and carbon emissions of congestion charging and bus analysis prediction and assessment.

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：U491

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1 明士軍;楊德明;;出行梯度與出行結(jié)構(gòu)關(guān)系研究[J];西華大學(xué)學(xué)報(bào)(自然科學(xué)版);2010年05期

2 全永q，

本文編號(hào)：1422768