摘要
隨著城市人口不斷膨脹，城市化和機(jī)動(dòng)化快速發(fā)展，城市交通擁堵問(wèn)題日益凸現(xiàn)。大力發(fā)展公共交通已成為緩解這一矛盾的共識(shí)，公交優(yōu)先成為我國(guó)許多城市解決交通問(wèn)題的必然選擇。 全文共分為五章，其中第二、三、四章是論文的核心部分。文章以路網(wǎng)公交車(chē)流作為研究對(duì)象，一是針對(duì)常規(guī)公交系統(tǒng)和快速公交系統(tǒng)分別提出了其相應(yīng)的控制方法，較詳盡的闡述了各種公交信號(hào)優(yōu)先方法；二是對(duì)于常規(guī)公交系統(tǒng)的信號(hào)優(yōu)先，利用人工神經(jīng)網(wǎng)絡(luò)方法預(yù)測(cè)公交車(chē)的行程時(shí)間，能較準(zhǔn)確預(yù)測(cè)公交車(chē)行駛到交叉口的相位，并根據(jù)延誤理論對(duì)多個(gè)相位申請(qǐng)公交信號(hào)優(yōu)先進(jìn)行判別，在前人研究的基礎(chǔ)上進(jìn)一步深化了常規(guī)公交信號(hào)優(yōu)先的研究，使信號(hào)優(yōu)先控制模型的準(zhǔn)確性更高；三是對(duì)于快速公交系統(tǒng)的信號(hào)優(yōu)先，根據(jù)有無(wú)常規(guī)公交車(chē)提出了不同的控制方法和控制參數(shù)計(jì)算方法，與實(shí)際情況相符；四是利用VISSIM仿真軟件，以交叉口人均延誤作為評(píng)判指標(biāo)對(duì)本文研究的算法進(jìn)行了仿真驗(yàn)證，得出了各種控制方法適用的情況以及各種控制方式下交叉口特性的變化規(guī)律。 關(guān)鍵詞 城市交通；公交優(yōu)先；信號(hào)交叉口；人均延誤；VISSIM仿真




































Abstract
Due to the rapid growth of population, the rapid development of urbanization and motorization, the urban traffic problem is getting worse. Vigorously develop public transportation has become the consensus of mitigating this contradiction, bus priority in many cities become the inevitable choice of solving traffic problem.
The essay is divided into five chapters, chapter 2, 3 and 4 are core parts. This paper put traffic flow of road network as research object. Firstly, according to public traffic system and bus rapid transit (BRT), it provides corresponding control methods and describes various methods of bus signal priority in detail. Secondly, aim at the signal priority of public traffic system, it use Artificial Neural Networks (ANNs) to predict the bus travel time and Accurate phase of bus drives to the intersection. According to delay theory, it discriminate signal priority that many phases apply for. Based on the previous studies, it further deepens the research of public traffic system’s signal priority and make signal priority control model more reasonable. Thirdly, for signal priority of BRT, different control methods and calculation method is proposed based on the certain or no groovy bus, they are coincident with the actual facts. Finally, it carries out simulation verifications which are judged by per capita delay time to demonstrate the validity of the algorithm researched in the paper, obtained the suitable condition and regular changes of intersection’s properties which matched all kinds of control methods.

Keywords Urban traffic; Bus priority; Signalized intersection; Per capita delay; VISSIM simulation






目錄
摘 要 I
Abstract III
第1章 緒論 1
1.1 研究背景及意義 1
1.2 研究現(xiàn)狀 2
1.2.1 國(guó)外研究現(xiàn)狀 2
1.2.2 國(guó)內(nèi)研究現(xiàn)狀 4
1.3 研究?jī)?nèi)容 6
1.3.1 相關(guān)的基本理論知識(shí) 7
1.3.2 常規(guī)公交系統(tǒng)公交信號(hào)優(yōu)先控制 7
1.3.3 快速公交系統(tǒng)公交信號(hào)優(yōu)先控制 7
第2章 相關(guān)基本理論知識(shí) 8
2.1 公交信號(hào)優(yōu)先控制的基本理論 8
2.1.1 公交信號(hào)優(yōu)先控制的涵義 8
2.1.2 公交信號(hào)優(yōu)先控制的模型 8
2.1.3 公交信號(hào)優(yōu)先控制的控制方式 9
2.1.4 公交信號(hào)優(yōu)先控制的數(shù)據(jù)流程 12
2.1.5 公交信號(hào)優(yōu)先控制的硬件結(jié)構(gòu) 13
2.2 神經(jīng)網(wǎng)絡(luò)的基礎(chǔ)理論 15
2.2.1 人工神經(jīng)網(wǎng)絡(luò)的概念 15
2.2.2 人工神經(jīng)網(wǎng)絡(luò)的模型 16
2.3 VISSIM仿真軟件簡(jiǎn)介 19
2.3.1 VISSIM仿真軟件的核心 19
2.3.2 VISSIM仿真軟件的主要特點(diǎn) 19
2.3.3 VISSIM系統(tǒng)的構(gòu)成模塊 20
2.4 本章小結(jié) 22
第3章 常規(guī)公交系統(tǒng)公交信號(hào)優(yōu)先控制 23
3.1 公交信號(hào)優(yōu)先控制思想 23
3.2 公交信號(hào)優(yōu)先控制條件 24
3.3 公交信號(hào)優(yōu)先控制目標(biāo) 24
3.4 公交信號(hào)優(yōu)先控制算法 25
3.5 公交信號(hào)優(yōu)先控制參數(shù)計(jì)算 28
3.5.1 基于神經(jīng)網(wǎng)絡(luò)的公交車(chē)到達(dá)時(shí)刻預(yù)測(cè) 28
3.5.1.1問(wèn)題定義 29
3.5.1.2 交通流模型選擇 30
3.5.1.3 交通模型的人工神經(jīng)網(wǎng)絡(luò)法 31
3.5.1.4 測(cè)試效果 33
3.5.1.5 求解時(shí)間 36
3.5.2 優(yōu)先權(quán)判別計(jì)算 36
3.5.3 信號(hào)控制參數(shù)優(yōu)化計(jì)算 40
3.6 公交信號(hào)優(yōu)先控制仿真 43
3.6.1 仿真環(huán)境介紹 43
3.6.2 仿真方案制定 44
3.6.3 仿真結(jié)果分析 44
3.7 本章小結(jié) 50
第4章 快速公交系統(tǒng)公交信號(hào)優(yōu)先控制 51
4.1 公交信號(hào)優(yōu)先控制的控制條件 51
4.2 公交信號(hào)優(yōu)先控制的控制思想 51
4.3 公交信號(hào)優(yōu)先控制的控制算法 53
4.3.1 無(wú)常規(guī)公交車(chē)的快速公交系統(tǒng)信號(hào)優(yōu)先控制算法 53
4.3.2 有常規(guī)公交車(chē)的快速公交系統(tǒng)信號(hào)優(yōu)先控制算法 56
4.4 公交信號(hào)優(yōu)先控制的控制參數(shù)計(jì)算 59
4.4.1 綠燈壓縮模型 59
4.4.2 綠燈延長(zhǎng)模型 59
4.4.3 快速公交插入相位模型 61
4.5 公交信號(hào)優(yōu)先控制仿真 63
4.6 本章小結(jié) 64
第5章 總結(jié)與展望 65
5.1 論文主要研究成果 65
5.2 后續(xù)研究工作展望 65
參考文獻(xiàn) 67