【摘要】：城市交通擁堵已成為世界性的難題。交通擁堵不僅造成了運(yùn)輸成本增加、居民出行延誤、空氣質(zhì)量下降,還給整個(gè)社會(huì)造成了巨大的生態(tài)環(huán)境污染、資源浪費(fèi)、道路事故率增加等無(wú)謂損失。作為交通優(yōu)化設(shè)計(jì)的主要工具,交通仿真通過(guò)對(duì)路網(wǎng)的設(shè)計(jì)、交通流的管控、信號(hào)燈控制等對(duì)城市交通狀況進(jìn)行仿真模擬,評(píng)估和優(yōu)化交通方案,為達(dá)到提高城市道路的利用率,緩解城市交通擁堵的目的提供了理論依據(jù)和決策支持。微觀交通仿真能直觀的刻畫(huà)車(chē)輛、行人等交通個(gè)體行為,隨著對(duì)交通仿真精度、效率、規(guī)模和準(zhǔn)確性等需求的日益增長(zhǎng),因而已成為分析交通流特性的關(guān)鍵技術(shù),備受研究者的關(guān)注,成為近年來(lái)研究的熱點(diǎn)。面對(duì)微觀交通仿真中的近鄰車(chē)輛查詢(xún)的效率問(wèn)題、安全換道模型中的縱向加速度自適應(yīng)變化問(wèn)題和基于公交IC卡數(shù)據(jù)的大規(guī)模OD矩陣推導(dǎo)問(wèn)題已成為實(shí)際應(yīng)用的困擾,本文從分析現(xiàn)有微觀交通仿真技術(shù)出發(fā),針對(duì)微觀交通仿真的近鄰車(chē)輛查詢(xún)算法的可擴(kuò)展性和效率問(wèn)題、縱向加速度自適應(yīng)調(diào)整的情況下車(chē)輛的安全換道距離問(wèn)題,以及基于公交IC卡數(shù)據(jù)的大規(guī)模OD矩陣推導(dǎo)問(wèn)題進(jìn)行了深入研究。論文的主要?jiǎng)?chuàng)新成果如下:(1)提出了一種適用于微觀交通仿真的基于局部索引的近鄰查詢(xún)算法。針對(duì)微觀交通仿真中的多一維的有向近鄰查詢(xún)問(wèn)題,提出了一種基于局部索引的近鄰車(chē)輛查詢(xún)算法。該算法在B+樹(shù)的基礎(chǔ)上,通過(guò)維護(hù)仿真單元的局部位置索引,使其同時(shí)具有B+樹(shù)與線性方法的優(yōu)點(diǎn)。對(duì)算法時(shí)間復(fù)雜度和期望查詢(xún)長(zhǎng)度的分析結(jié)果顯示,該算法可滿(mǎn)足大規(guī)模、擁堵的微觀交通仿真近鄰車(chē)輛查詢(xún)需求,提高了仿真系統(tǒng)的仿真效率。(2)提出了一種新型微觀交通仿真的加速度自適應(yīng)的安全換道模型。針對(duì)車(chē)輛換道過(guò)程中加速度自適應(yīng)變化的問(wèn)題,提出了一種縱向加速度自適應(yīng)的安全換道模型。該模型通過(guò)定義車(chē)輛換道的臨界碰撞時(shí)間節(jié)點(diǎn),將換道過(guò)程分為四個(gè)階段,并結(jié)合了加速度變化和模型參數(shù)對(duì)臨界碰撞時(shí)間節(jié)點(diǎn)以及安全換道距離的影響,使其能更真實(shí)地表征車(chē)輛換道的情況。該模型具有較高的精度,可有效模擬車(chē)輛換道過(guò)程的加速度變化,使得安全換道距離的計(jì)算更為準(zhǔn)確。(3)提出了一種基于公交IC卡數(shù)據(jù)補(bǔ)全的大規(guī)模OD矩陣推導(dǎo)算法。針對(duì)城市公交的大規(guī)模OD矩陣推導(dǎo)問(wèn)題,提出了一種基于公交IC卡數(shù)據(jù)補(bǔ)全的大規(guī)模OD矩陣推導(dǎo)算法。該算法在不關(guān)聯(lián)公交調(diào)度和GPS數(shù)據(jù)情況下,通過(guò)上車(chē)站點(diǎn)標(biāo)注和行駛方向標(biāo)注子算法,將刷卡記錄與實(shí)際公交站點(diǎn)進(jìn)行匹配。同時(shí),將全局公交數(shù)據(jù)補(bǔ)全問(wèn)題映射為圖論中的節(jié)點(diǎn)的遍歷問(wèn)題,利用貪心生長(zhǎng)算法和廣度優(yōu)先遍歷策略實(shí)現(xiàn)局部最優(yōu),并在基于公交出行鏈的假設(shè)下挖掘城市居民出行OD矩陣。該算法可高效地完成大規(guī)模OD矩陣推導(dǎo),為交通需求分析提供理論依據(jù)。(4)設(shè)計(jì)并實(shí)現(xiàn)了一個(gè)輕量級(jí)微觀交通仿真原型系統(tǒng)。為了驗(yàn)證查詢(xún)算法的效率和換道模型的精度,設(shè)計(jì)并實(shí)現(xiàn)了一個(gè)微觀交通仿真原型系統(tǒng)。該系統(tǒng)采用基于公交IC卡數(shù)據(jù)的OD矩陣設(shè)置,通過(guò)真實(shí)數(shù)據(jù)初始化仿真環(huán)境,實(shí)現(xiàn)了局部索引的近鄰車(chē)輛查詢(xún)算法和加速度自適應(yīng)的安全換道模型。仿真結(jié)果顯示該近鄰查詢(xún)算法可有效提高仿真系統(tǒng)的查詢(xún)效率;而該換道模型能提供更準(zhǔn)確的安全換道距離。綜上,本文對(duì)微觀交通仿真技術(shù)走向?qū)嶋H應(yīng)用時(shí)面臨的幾類(lèi)重點(diǎn)挑戰(zhàn)性問(wèn)題進(jìn)行了針對(duì)性研究,為微觀交通仿真技術(shù)的推廣應(yīng)用提供了一個(gè)高效可行的解決方案。本文的研究成果能有效地提高微觀交通仿真系統(tǒng)的仿真性能和精度,并為微觀交通仿真系統(tǒng)的研究和應(yīng)用提供了理論和技術(shù)支持,具有良好的可擴(kuò)展性,能夠推廣到更廣泛的交通仿真分析應(yīng)用場(chǎng)景。
[Abstract]:Traffic congestion has become a worldwide problem. Traffic congestion not only causes the increase of transportation costs, travel delays, and air quality, but also causes enormous ecological environment pollution, waste of resources and increase of road accident rate to the whole society. As the main tool for optimizing design, traffic simulation passes through the road. The design of the network, the control of traffic flow, the control of the signal light and so on are used to simulate the urban traffic conditions, evaluate and optimize the traffic plan. It provides the theoretical basis and decision support for the purpose of improving the utilization of urban roads and alleviating the traffic congestion of the city. With the increasing demand for precision, efficiency, scale and accuracy of traffic simulation, it has become a key technology for analyzing traffic flow characteristics. It has attracted much attention of researchers and became a hot spot in recent years. Facing the efficiency of nearest neighbor vehicle query in micro traffic simulation, the longitudinal acceleration adaptive in the security change model is adaptive. The problem of change and the derivation of large scale OD matrix based on bus IC card data have become a problem of practical application. In this paper, based on the analysis of the existing micro traffic simulation technology, the scalability and efficiency of the nearest neighbor vehicle query algorithm for microscopic traffic simulation, and the vehicle safety change under the adaptive adjustment of the longitudinal acceleration degree The distance problem, and the large-scale OD matrix derivation problem based on the bus IC card data are deeply studied. The main achievements of this paper are as follows: (1) a near neighbor query algorithm based on local index is proposed for microscopic traffic simulation. A neighbor vehicle query algorithm based on local index. Based on the B+ tree, the algorithm maintains the advantages of the B+ tree and the linear method by maintaining the local location index of the simulation unit. The analysis results of the time complexity and the expected query length of the algorithm show that the algorithm can satisfy the large-scale and congestion micro traffic simulation. In order to improve the simulation efficiency of the simulation system, the efficiency of the simulation system is improved. (2) a new model of the acceleration adaptive path change of the new micro traffic simulation is proposed. The critical collision time node divides the process into four stages, and combines the influence of the acceleration change and the model parameters on the critical collision time node and the safe change distance, so that it can more truly characterize the vehicle lane change. The model has a high precision and can effectively simulate the acceleration change of the vehicle changing process. The calculation of the safety change distance is more accurate. (3) a large-scale OD matrix derivation algorithm based on the bus IC card data complementation is proposed. A large-scale OD matrix derivation algorithm based on the bus IC card data complementation is proposed for the large-scale OD matrix derivation of urban public transport. This algorithm is not related to the bus scheduling and the GPS data. In the case, the card records are matched with the actual bus stations through the tagging and driving direction annotation algorithm, and the problem of the global bus data complement is mapped to the traversal problem of nodes in the graph theory. The local optimal is realized by the greedy growth algorithm and the breadth priority traversal strategy, and the bus travel chain is based on the bus travel chain. On the assumption that the urban resident travel OD matrix is excavated, the algorithm can efficiently complete the large-scale OD matrix derivation and provide the theoretical basis for the traffic demand analysis. (4) a lightweight microscopic traffic simulation prototype system is designed and implemented. In order to verify the efficiency of the query algorithm and the accuracy of the change model, a microscopic traffic imitation is designed and realized. The system uses the OD matrix set based on the bus IC card data, initializes the simulation environment through real data, realizes the local index nearest neighbor vehicle query algorithm and the acceleration adaptive security change path model. The simulation results show that the nearest neighbor query algorithm can effectively improve the query efficiency of the simulation system. The model can provide more accurate distance of safe channel change. In this paper, this paper studies several key challenges faced by the micro traffic simulation technology to practical application, and provides a efficient and feasible solution for the popularization and application of micro traffic simulation technology. The research results of this paper can effectively improve the micro level. The simulation performance and precision of the traffic simulation system provide theoretical and technical support for the research and application of the micro traffic simulation system. It has good extensibility and can be extended to a wider range of traffic simulation and analysis applications.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：U495

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 劉艷玲;熊輝;;基于運(yùn)動(dòng)學(xué)的換道安全間距研究[J];交通標(biāo)準(zhǔn)化;2014年04期

2 樓大成;;車(chē)輛換道過(guò)程中目標(biāo)車(chē)輛與周?chē)?chē)輛的安全距離[J];硅谷;2014年05期

3 楊建國(guó),王金梅,李慶豐,王兆安;微觀仿真中車(chē)輛換道的行為分析和建模[J];公路交通科技;2004年11期

4 楊小寶;張寧;;任意性換道模型的比較與選擇[J];交通運(yùn)輸系統(tǒng)工程與信息;2006年04期

5 劉小明;鄭淑暉;蔣新春;;基于動(dòng)態(tài)重復(fù)博弈的車(chē)輛換道模型[J];公路交通科技;2008年06期

6 楊小寶;;考慮實(shí)施過(guò)程的車(chē)輛換道模型及其應(yīng)用[J];物理學(xué)報(bào);2009年02期

7 金立生;Bartvan Arem;楊雙賓;Mascha van der Voort;Martijn Tideman;;高速公路汽車(chē)輔助駕駛安全換道模型[J];吉林大學(xué)學(xué)報(bào)(工學(xué)版);2009年03期

8 李瑋;高德芝;段建民;;智能車(chē)輛自由換道模型研究[J];公路交通科技;2010年02期

9 王崇倫;李振龍;陳陽(yáng)舟;代桂平;;考慮換道約束空間的車(chē)輛換道模型研究[J];公路交通科技;2012年01期

10 付靜靜;孫浩;杜春臣;;基于駕駛?cè)藫Q道行為的換道決策輔助系統(tǒng)預(yù)警時(shí)間研究[J];北京汽車(chē);2012年04期

相關(guān)會(huì)議論文 前3條

1 張安英;;基于預(yù)判概率的換道決策模型研究[A];第八屆中國(guó)智能交通年會(huì)優(yōu)秀論文集——智能交通與安全[C];2013年

2 李瑋;段建民;龔建偉;;障礙物條件下智能車(chē)輛換道路徑規(guī)劃的近優(yōu)解[A];2011年中國(guó)智能自動(dòng)化學(xué)術(shù)會(huì)議論文集（第一分冊(cè)）[C];2011年

3 楊曉光;孫劍;;面向ITS的交通仿真實(shí)驗(yàn)系統(tǒng)研究與開(kāi)發(fā)[A];第一屆中國(guó)智能交通年會(huì)論文集[C];2005年

相關(guān)重要報(bào)紙文章 前3條

1 本報(bào)記者 李龍俊;換道超車(chē)，才有機(jī)會(huì)后來(lái)居上[N];四川日?qǐng)?bào);2014年

2 記者 徐景明;車(chē)一進(jìn)隧道就不允許換道[N];廈門(mén)日?qǐng)?bào);2010年

3 聞天;安全駕車(chē)十二訣[N];華夏時(shí)報(bào);2004年

相關(guān)博士學(xué)位論文 前10條

1 宋竹;微觀交通仿真查詢(xún)算法與換道模型研究[D];電子科技大學(xué);2015年

2 彭金栓;基于視覺(jué)特性與車(chē)輛相對(duì)運(yùn)動(dòng)的駕駛?cè)藫Q道意圖識(shí)別方法[D];長(zhǎng)安大學(xué);2012年

3 王暢;車(chē)輛換道預(yù)警的若干關(guān)鍵問(wèn)題研究[D];長(zhǎng)安大學(xué);2012年

4 侯海晶;高速公路駕駛?cè)藫Q道意圖識(shí)別方法研究[D];吉林大學(xué);2013年

5 黨睿娜;具有換道輔助功能的車(chē)輛自適應(yīng)巡航控制[D];清華大學(xué);2013年

6 羅強(qiáng);面向高速公路行車(chē)安全預(yù)警的車(chē)道偏離及換道模型研究[D];華南理工大學(xué);2014年

7 漆巍巍;城市道路擁堵?tīng)顟B(tài)下駕駛?cè)松砑皳Q道特性研究[D];哈爾濱工業(yè)大學(xué);2014年

8 朱愿;基于視覺(jué)和雷達(dá)的智能車(chē)輛自主換道決策機(jī)制與控制研究[D];中國(guó)人民解放軍軍事醫(yī)學(xué)科學(xué)院;2014年

9 周立軍;基于駕駛員信息處理特性的跟馳及換道模型研究[D];吉林大學(xué);2008年

10 游峰;智能車(chē)輛自動(dòng)換道與自動(dòng)超車(chē)控制方法的研究[D];吉林大學(xué);2005年

相關(guān)碩士學(xué)位論文 前10條

1 吳杭哲;基于最小安全距離的車(chē)輛換道控制研究[D];哈爾濱工業(yè)大學(xué);2015年

2 楊雙賓;高速公路車(chē)輛行駛安全輔助換道預(yù)警系統(tǒng)研究[D];吉林大學(xué);2008年

3 曹珊;城市道路車(chē)輛換道模型及換道影響研究[D];華中科技大學(xué);2009年

4 杜毓皓;基于駕駛?cè)酥饔^判斷的換道安全界限時(shí)刻研究[D];長(zhǎng)安大學(xué);2013年

5 鄭楚清;車(chē)輛換道預(yù)警系統(tǒng)的越線時(shí)間預(yù)測(cè)方法研究[D];長(zhǎng)安大學(xué);2013年

6 鄭華榮;考慮周邊車(chē)輛駕駛意圖的換道危險(xiǎn)預(yù)警研究[D];武漢理工大學(xué);2013年

7 毛錦;考慮駕駛風(fēng)格的換道預(yù)警方法[D];長(zhǎng)安大學(xué);2012年

8 常浩;車(chē)路協(xié)同下的車(chē)輛換道駕駛輔助方法研究[D];北京交通大學(xué);2015年

9 王彩霞;交通仿真中的換道模型研究[D];吉林大學(xué);2007年

10 秦加合;用于換道仿真的車(chē)輛運(yùn)動(dòng)控制與動(dòng)力學(xué)模型研究[D];長(zhǎng)安大學(xué);2013年

，

本文編號(hào)：2172153