The invention relates to an intersection modeling and signal lamp control optimization method based on a fuzzy neural Petri network, and belongs to the technical field of traffic signal lamp control. The method comprises the following steps: performing read-only arc and suppression arc attribute extension on directed arc basic attributes of a continuous Petri network, and constructing an intersection traffic flow and road section model and an intersection signal lamp model by using the extended continuous Petri network; secondly, introducing a fuzzy Petri network, expanding the basic attribute of the change of the fuzzy Petri network, and constructing an intersection signal lamp fuzzy control model by using the expanded fuzzy Petri network; thirdly, an adaptive control intersection model based on a continuous Petri network and a fuzzy Petri network is constructed through replacement operation, and signal lamp adaptive control is achieved. Compared with a fixed timing scheme and an optimization scheme which only considers the vehicle queuing length, the evaluation indexes such as the average time loss, the average waiting time and the total number of vehicles in the phase time have the advantage of improving the traffic capacity of the intersection.
本发明涉及一种基于模糊神经Petri网的交叉口建模与信号灯控制优化方法,属于交通信号灯控制技术领域。本发明使用对连续Petri网有向弧基础属性进行只读弧和抑止弧属性扩展,利用扩展后的连续Petri网构建交叉口交通流与路段模型和交叉口信号灯模型;其次,引入模糊Petri网,并扩展模糊Petri网变迁的基础属性,并利用扩展后的模糊Petri网构建交叉口信号灯模糊控制模型;再次,通过替换运算构建基于连续Petri网和模糊Petri网的自适应控制交叉口模型,实现信号灯自适应控制。本发明与固定配时方案和仅考虑车辆排队长度的优化方案相比,相位时间内平均时间损失、平均等待时间和车辆总数等评价指标,对提高交叉口通行能力存在优势。
Intersection modeling and signal lamp control optimization method based on fuzzy neural Petri network
一种基于模糊神经Petri网的交叉口建模与信号灯控制优化方法
2024-12-27
Patent
Electronic Resource
Chinese
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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