基于ALINEA的城市高架快速路入口匝道控制优化研究

发布时间：2018-07-09 11:49

本文选题：入口匝道控制 + 多车道　；参考：《西南交通大学》2017年硕士论文

【摘要】：我国城市高架快速路多呈现高架快速路与地面快速路相结合的形式,在建设初期对区域交通状况存在短期改善作用。但随着运营时间的增长,在车辆保有量逐年增加、高架快速路诱增交通量等影响下,城市高架快速路拥挤日趋严重。匝道控制作为能有效缓解城市快速路拥挤的交通控制方法之一,研究并应用匝道控制策略对降低合流冲突、改善主线运行状况等存在重要意义。ALINEA作为应用较为广泛、控制效果较优的经典入口匝道控制方法,本文在大量查阅ALINEA控制策略相关文献基础上,概括了经典ALINEA应用中存在的缺陷以及可能改进方向,并将ALINEA扩展算法划分为基于固定参数、基于参数调整和基于协调控制三类。继而采用基于快速路交通录像资料的交通流模型参数测量方法,对成都市二环高架路进行了交通流特性调查,基于视频资料提取的车速-车头时距数据,重点分析了二环高架路主线交通流运行特征以及内外侧车道的交通流运行特征差异。进而依据交通流运行特征差异分析的结果,基于宏观交通流模型META与METANET进行了考虑多车道的交通流模型简化研究,建立了城市高架快速路密度动态方程与排队长度动态方程,基于动态方程推导了密度微分方程与排队长度微分方程。为解决经典ALINEA在调节率确定过程中未区分考虑内外侧车道的缺陷,对经典ALINEA算法展开多车道优化研究,提出了基于多车道的ALINEA优化控制模型(ML-ALINEA),建立了匝道调节率折减系数的实时调整算法。将减小入口匝道密度、凸显高架快速路各车道间的交通流特性差异综合考虑至控制策略目标的制定中,设计了对应动态方程与微分方程的误差函数和闭环系统,基于动态方程提出了基于密度动态方程的多车道入口匝道控制算法;基于微分方程提出了基于密度微分方程的多车道入口匝道控制算法。最后为验证考虑多车道的入口匝道优化控制策略的有效性以及控制效果,设计了对应的仿真试验场景,基于参数标定和VissimVAP、COM接口实现了各场景的仿真,利用评价指标对比各场景的控制效果,结果表明各控制策略均优于经典ALINEA。
[Abstract]:Most of the urban elevated freeways in China take the form of the combination of elevated freeway and ground expressway, which can improve the regional traffic condition in the early stage of construction. However, with the increase of operation time, the traffic congestion of urban elevated expressway is becoming more and more serious under the influence of the increase of vehicle ownership and the induced traffic volume of elevated freeway. Ramp control is one of the traffic control methods that can effectively alleviate the congestion of urban expressway. It is important to study and apply ramp control strategy to reduce the confluence conflict and improve the main line operation. The classical on-ramp control method with better control effect is discussed in this paper. On the basis of consulting a lot of literature about ALINEA control strategy, this paper summarizes the defects in the application of classical ALINEA and its possible direction of improvement. The extended AlinEA algorithm is divided into three categories: fixed parameter based on parameter adjustment and coordination based control. Then the traffic flow characteristics of the second Ring Viaduct in Chengdu are investigated by using the traffic flow model parameter measurement method based on the traffic video data of the expressway, and the velocity-front time distance data are extracted based on the video data. The traffic flow characteristics of the main line of the second Ring Viaduct and the traffic flow characteristics of the inner and outer driveway are analyzed. Based on the results of traffic flow characteristic difference analysis and based on the macroscopic traffic flow model meta and Meta net, the simplified traffic flow model considering multi-lane is studied, and the dynamic equations of urban elevated expressway density and queue length are established. Based on the dynamic equation, the density differential equation and the queue length differential equation are derived. In order to solve the problem that the classical ALINEA did not distinguish between the inner and outer lanes in the process of determining the adjustment rate, the multi-lane optimization study was carried out on the classical ALINEA algorithm. A multi-lane ALINEA optimal control model (ML-ALINEA) is proposed, and a real-time adjustment algorithm of ramp adjustment rate reduction coefficient is established. In order to reduce the on-ramp density and highlight the difference of traffic flow characteristics between different lanes of elevated freeway, the error function and closed-loop system corresponding to dynamic equation and differential equation are designed. Based on the dynamic equation, the multi-lane on-ramp control algorithm based on the density dynamic equation is proposed, and the multi-lane on-ramp control algorithm based on the density differential equation is proposed based on the differential equation. Finally, in order to verify the effectiveness and control effect of the multi-lane on-ramp optimal control strategy, a corresponding simulation test scenario is designed. The simulation of each scenario is realized based on parameter calibration and VissimVAPC com interface. The results show that each control strategy is superior to the classical ALINEA.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491

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