基于交通诱导与公交优先协同控制的信号配时方法研究

发布时间：2019-06-29 18:43

【摘要】：摘要：随着社会的进步以及经济的快速发展,汽车的保有量不断创下新高,大量机动车的出现造成严重的交通拥挤,同时也引起了严重的空气污染和噪声污染。为有效解决城市交通问题,满足日益增大的交通需求和保护环境的需要,必须在有限的资源约束下,坚持“公交优先”战略和“绿色交通”战略,利用先进科学技术及管理方法,多层次、多目标、多角度的解决交通问题。因此,本研究在借鉴国内外先进成果的基础上,对如何在交通诱导下实现“公交优先”、“绿色交通”展开了研究,主要工作总结如下： (1)设计了包括排放因素和延误因素的双目标公交优先信号配时模型。模型构建中选取人均延误和人均排放最小作为目标函数,并提出了相应约束条件。 (2)对公交优先策略、交通诱导、信号配时控制三者协同作用的机理进行分析。通过设立效用函数、路径补偿系数及选择规则等方法,构建出流量依据路网状态实时更新、动态变化的模型。 (3)分析双环相位的组合及切换形式,设计合理的双环相位形式。通过分析交叉口流量数据,比较各进口道之间流量关系,从而确定合理的双环相位形式并进行信号配时求解。 (4)改进传统遗传算法,采用不满足约束个体直接死亡、构建适应度函数、以饱和度作为惩罚函数以及每代严格保优等方法,达到满足基本约束下同时优化信号周期和绿信比的目的。 (5)利用改进遗传算法,对上述模型进行求解,并将结果比较分析。结果表明,本文提出的协同控制模型,不仅能很好的协调延误和排放这两个目标之间的关系,同时各个目标均能取得较为理想的结果,人总延误和车总延误较传统信号配时模型分别降低了4.4%和2.8%。。双环相位能较大的降低车总延误,降低幅度为22.4%,同时排放指标也能控制在较为理想的范围内,降低幅度为4.1%。
[Abstract]:Absrtact: with the progress of society and the rapid development of economy, the ownership of cars continues to reach a new high, the emergence of a large number of motor vehicles cause serious traffic congestion, but also cause serious air pollution and noise pollution. In order to effectively solve the urban traffic problems and meet the increasing traffic demand and the need to protect the environment, we must adhere to the strategy of "public transport priority" and "green traffic" under the constraint of limited resources, make use of advanced science and technology and management methods, multi-level, multi-objective and multi-angle to solve the traffic problems. Therefore, on the basis of drawing lessons from the advanced achievements at home and abroad, this study studies how to realize "bus priority" and "green traffic" under traffic guidance. The main work is summarized as follows: (1) A two-objective bus priority signal timing model including emission factors and delay factors is designed. In the model construction, the per capita delay and the minimum per capita emission are selected as the objective function, and the corresponding constraints are put forward. (2) the mechanism of synergy among bus priority strategy, traffic guidance and signal timing control is analyzed. By setting up utility function, path compensation coefficient and selection rules, a model of real-time updating and dynamic change of flow according to the state of road network is constructed. (3) the combination and switching form of double loop phase are analyzed, and a reasonable double loop phase form is designed. By analyzing the traffic data of intersection, the flow relationship between the inlet roads is compared, and the reasonable double loop phase form is determined and the signal timing is solved. (4) the traditional genetic algorithm is improved, which adopts the direct death of individuals who do not satisfy the constraints, constructs the fitness function, takes saturation as the penalty function and each generation strictly preserves the best, so as to optimize the signal period and green signal ratio at the same time under the basic constraints. (5) the improved genetic algorithm is used to solve the above model, and the results are compared and analyzed. The results show that the cooperative control model proposed in this paper can not only coordinate the relationship between delay and emission, but also achieve satisfactory results. The total human delay and total vehicle delay are reduced by 4.4% and 2.8%, respectively, compared with the traditional signal timing model. The double loop phase can greatly reduce the total vehicle delay by 22.4%. At the same time, the emission index can also be controlled in the ideal range, the reduction range is 4.1%.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491.54

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