本文關(guān)鍵詞：基于DDDAS的高速公路異常事件影響范圍仿真分析　出處：《重慶大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 高速公路 DDDAS 交通仿真 數(shù)據(jù)同化 粒子濾波

【摘要】：高速公路異常事件(如車輛故障、交通事故等)會(huì)降低路段通行效率,在車流量較大的情況下,可能會(huì)引發(fā)道路交通阻塞和車輛排隊(duì)的問題。異常事件的影響范圍和發(fā)展趨勢(shì)的可靠估計(jì)是制定針對(duì)性交通管控策略的前提和基礎(chǔ),對(duì)保障高速公路的暢通運(yùn)行和提高高速公路的管理服務(wù)水平具有重要的現(xiàn)實(shí)意義。目前高速公路異常事件的影響范圍主要是通過交通流理論建立預(yù)測(cè)模型來進(jìn)行估計(jì),由于現(xiàn)有交通參數(shù)檢測(cè)精度無法滿足模型的輸入要求尚難以在工程中進(jìn)行應(yīng)用。針對(duì)此問題論文引入仿真分析技術(shù),對(duì)高速公路交通流時(shí)間關(guān)聯(lián)特性進(jìn)行分析,并結(jié)合歷史車檢器數(shù)據(jù)特性提出了基于VISSIM仿真系統(tǒng)的交通流參數(shù)標(biāo)定方法和駕駛行為參數(shù)校正方法。在此基礎(chǔ)上,結(jié)合對(duì)粒子濾波算法的深入分析,研究了基于DDDAS的高速公路異常事件影響范圍仿真分析方法。論文主要內(nèi)容包括:(1)仿真模型交通流參數(shù)標(biāo)定和駕駛行為參數(shù)校正。在對(duì)高速公路交通流時(shí)間關(guān)聯(lián)特性分析的基礎(chǔ)上,結(jié)合歷史車檢器數(shù)據(jù)對(duì)仿真模型交通流參數(shù)進(jìn)行了標(biāo)定;針對(duì)仿真模型駕駛行為參數(shù)默認(rèn)值標(biāo)定不準(zhǔn)確的情況,結(jié)合單因素差方法進(jìn)行敏感性分析確定用于校正的核心參數(shù),研究了基于遺傳算法的仿真模型駕駛行為參數(shù)校正方法;最后利用實(shí)際車檢器數(shù)據(jù)進(jìn)行了模型驗(yàn)證。結(jié)果表明建立的仿真模型能準(zhǔn)確的對(duì)道路上的交通流運(yùn)行趨勢(shì)進(jìn)行仿真。(2)研究基于粒子濾波算法的交通仿真模型數(shù)據(jù)同化方法。結(jié)合交通波理論和閾值理論,建立高速公路車檢器數(shù)據(jù)預(yù)處理方法。在此基礎(chǔ)上結(jié)合DDDAS范式和粒子濾波理論,研究了基于DDDAS的高速公路異常事件仿真分析方法,最后對(duì)模型的有效性進(jìn)行了算例驗(yàn)證。結(jié)果表明,基于粒子濾波的交通仿真模型能夠不斷地同化實(shí)時(shí)數(shù)據(jù),實(shí)現(xiàn)對(duì)道路上堵塞事件位置和實(shí)時(shí)排隊(duì)長(zhǎng)度的精確估計(jì)。最后介紹了基于粒子濾波算法的交通仿真系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn),并結(jié)合G75高速北碚隧道段車檢器數(shù)據(jù),選取典型真實(shí)交通異常事件構(gòu)建相應(yīng)的仿真場(chǎng)景,驗(yàn)證了基于DDDAS的高速公路異常事件影響范圍仿真系統(tǒng)的有效性。結(jié)果表明:本文方法可以準(zhǔn)確地對(duì)異常事件引起的排隊(duì)長(zhǎng)度進(jìn)行估計(jì)。
[Abstract]:Expressway abnormal events (such as vehicle failures, traffic accidents, etc.) will reduce the efficiency of road sections, in the case of large traffic flow. The problem of road traffic jam and vehicle queuing may be caused. The reliable estimation of the influence range and development trend of abnormal events is the premise and foundation of formulating targeted traffic control strategy. It is of great practical significance to ensure the smooth operation of expressway and to improve the level of management and service of expressway. At present, the influence of abnormal events on expressway is mainly carried out through the establishment of prediction model based on traffic flow theory. Estimate. Because the existing precision of traffic parameter detection can not meet the input requirements of the model, it is difficult to be applied in engineering. In order to solve this problem, the paper introduces simulation analysis technology to analyze the characteristics of time correlation of expressway traffic flow. The calibration method of traffic flow parameters and the method of correcting driving behavior parameters based on VISSIM simulation system are proposed based on the data characteristics of historical vehicle detector. On this basis, the particle filter algorithm is deeply analyzed. This paper studies the simulation and analysis method of the influence range of expressway abnormal events based on DDDAS. The main contents of this paper are as follows: 1). The traffic flow parameters calibration and driving behavior parameters calibration of the simulation model. Based on the analysis of the time correlation characteristics of expressway traffic flow. The traffic flow parameters of the simulation model are calibrated with the historical vehicle detector data. In view of the inaccurate calibration of the default values of driving behavior parameters in the simulation model, the core parameters for correction are determined by sensitivity analysis combined with the single factor difference method. The driving behavior parameters correction method of simulation model based on genetic algorithm is studied. Finally, the model is verified by using the actual vehicle detector data. The results show that the established simulation model can accurately simulate the traffic flow running trend on the road. The data assimilation method of traffic simulation model based on particle filter algorithm is studied. The traffic wave theory and threshold theory are combined. Based on the DDDAS normal form and particle filter theory, the simulation analysis method of highway abnormal events based on DDDAS is studied. Finally, the validity of the model is verified by an example. The results show that the traffic simulation model based on particle filter can assimilate real-time data continuously. Finally, the design and implementation of traffic simulation system based on particle filter algorithm are introduced. And combined with the G75 high-speed Beibei tunnel section vehicle detector data, select typical real traffic anomalies to build the corresponding simulation scene. The effectiveness of the simulation system based on DDDAS is verified. The results show that the proposed method can accurately estimate the queue length caused by abnormal events.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：U491

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1 胡滄粟;基于DDDAS的高速公路異常事件影響范圍仿真分析[D];重慶大學(xué);2016年

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本文編號(hào)：1408089