基于低碳交通的信号交叉口优化控制研究

发布时间：2018-03-21 04:48

  本文选题：信号交叉口　切入点：多目标规划　出处：《湖南大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着城市私人小汽车保有量的迅速增加，道路交通拥堵现象日益严重，环境污染问题越来越受到人们的广泛关注。信号交叉口的通行效率对整个交通系统的运行起着至关重要的作用。以往的信控交叉口控制研究方法大多只考虑交通运行效率指标，很少将减排问题考虑在内，因此，提出一个兼顾交通流情况和尾气排放情况的交叉口信号优化方法具有重要的理论意义和实用价值。 本文在既有研究成果的基础上，分析信号交叉口配时研究的内涵和意义，选取车辆在信号交叉口的延误、通行能力和CO排放量作为综合评价交叉口效率和进行信号配时的基础，将模糊折中规划多目标理论引入到信号配时模型构建中，并通过构造模糊偏好矩阵计算三个隶属度函数的权重，将其转为无量纲的单目标函数，建立了基于低碳交通的信号交叉口优化控制模型。将改进的粒子群算法和基于低碳交通的信号交叉口优化控制模型相结合，设计了模型的求解步骤。在实地调查交通数据的基础上，选取清远市典型交叉口进行配时模型的案例分析，采用动态加速常数协同惯性权重粒子群优化算法（WCPSO）对单目标函数进行求解，分别得到了单目标函数在p=1、p=2、p=+∞三种情况下的各相位的有效绿灯时间，并通过已构建的信号配时模型获取交叉口的延误、通行能力和CO排放量数值，同时基于上述三个影响因素分析比较得出最佳的信号配时方案。 本研究运用美国微观交通仿真软件TSIS对案例交叉口进行交通仿真以验证优化模型的有效性。仿真结果表明，，优化配时方案后的交叉口的每车延误比现状配时下的延误减少了9.7%，排队长度减少了15%，CO排放量减少10%，平均车速提高5.8%，交叉口服务水平得到显著提高。优化方案缩短了信号周期时间，重新分配了绿信比，使得车辆在交叉口的等待时间相应缩短，避免了原来所形成的冲突点，使车辆运行状态有所改善，整个交叉口的交通运行状况得到极大的提高。
[Abstract]:With the rapid increase in the number of private cars in urban areas, the traffic congestion on the roads is becoming more and more serious. More and more people pay attention to the problem of environmental pollution. The traffic efficiency of signalized intersections plays an important role in the operation of the whole traffic system. The problem of emission reduction is rarely taken into account, so it is of great theoretical significance and practical value to propose a method of intersection signal optimization which takes traffic flow and exhaust emission into account. On the basis of the existing research results, this paper analyzes the connotation and significance of the timing research at signalized intersections, and selects the delay of vehicles at signalized intersections. Traffic capacity and CO emissions are the basis of comprehensive evaluation of intersection efficiency and signal timing. Fuzzy compromise planning multi-objective theory is introduced into signal timing model construction. The weight of three membership functions is calculated by constructing fuzzy preference matrix, which is transformed into a dimensionless single-objective function. The optimal control model of signalized intersection based on low carbon traffic is established, and the improved particle swarm optimization algorithm is combined with the optimal control model of signalized intersection based on low carbon traffic. Based on the field investigation of traffic data, the typical intersection in Qingyuan City is selected to carry out the case study of time matching model. The dynamic acceleration constant cooperative inertial weight particle swarm optimization (WCPSO) algorithm is used to solve the single objective function. The effective green time of each phase of the single objective function is obtained in the case of p1 / p1 / 2 / 2 ~ (2) p = 鈭

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