[1]钟馥声,王安麟,姜涛.城市交通信号自组织控制中信号相位建模的优化方法[J].长安大学学报(自然科学版),2020,40(4):91-100.
 ZHONG Fu sheng,WANG An lin,JIANG Tao.Optimization method of modeling signal phase of urban trafficsignal selforganizing control[J].Journal of Chang’an University (Natural Science Edition),2020,40(4):91-100.
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城市交通信号自组织控制中信号相位建模的优化方法()
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长安大学学报(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
第40卷
期数:
2020年4期
页码:
91-100
栏目:
交通工程
出版日期:
2020-07-15

文章信息/Info

Title:
Optimization method of modeling signal phase of urban trafficsignal selforganizing control
作者:
钟馥声王安麟姜涛
(同济大学 机械与能源工程学院,上海 201804)
Author(s):
ZHONG Fusheng WANG Anlin JIANG Tao
(School of Mechanical Engineering, Tongji University, Shanghai 201804, China)
关键词:
交通工程信号控制自组织控制信号相位建模流量分配
Keywords:
traffic engineering signal control selforganizing control modeling signal phase traffic assignment
文献标志码:
A
摘要:
针对城市交通信号自组织控制中信号相位的建模方式下,在交叉口进入拥堵路况后各个信号相位绿灯损失时间不断增加的问题,提出了一种城市交通信号自组织控制中信号相位建模的优化方法。城市交通信号自组织系统以交叉口内各车道交通拥挤程度为决策信息,以其实时交互与协调的相邻交叉口为自组织单元,根据流体力学建立城市交通信号切换的确定规则集合。通过建立流量分配原则与期望的绿灯时间对控制策略进行更新,解决传统城市交通信号自组织控制中滚动步长的信号建模方法在面向系统每个自组织单元由道路组成、交叉口间联结方式以及交通流随机性等带来的复杂性问题。在传统方法的基础上,首先,对交叉口内各信号相位添加状态约束以提高控制规则的合理性,在完成自身参数优化的基础上,为相邻交叉口间通行效率的协调提供基础。其次,利用元胞传输模型模拟微观交通流传递,预测队列在交叉口处连续传递的运行方式,确定该交叉口放行需求的同时,建立了基于信号相位的上下游流量分配规则。最后,综合从上游交叉口驶出的不同车流量大小,依据下游交叉口当前最大允许驶入的车流量,并按计算得到的放行需求进行动态分配,以此放行车辆需求为基础,确定期望绿灯时间,完成信号相位建模的优化方法。仿真结果表明:优化后的建模方法不仅能同时提高自组织控制在拥堵与非拥堵路况下的通行效率,还能有效减少各交叉口处于拥堵状态的整体时间,使得交叉口群间整体通行能力得到提升,实现一种单点控制与小规模区域控制的同步优化。
Abstract:
To solve the problem that the green light loss time was increasing under the situation that the green light duration of each signal phase was gradually reduced after entering the congested road condition at intersections, which was caused by the modeling method of signal phase in urban traffic signal selforganizing control, an optimization method of modeling signal phase of urban traffic signal selforganizing control was proposed. The traffic congestion degree of each lane of the intersection was taken as the decision information of the signal selforganization system under urban traffic, the selforganization unit was composed of the interactive and coordinated adjacent intersections under the realtime situation, and the selforganization decision rule set for signal switching under urban traffic was established by the hydrodynamics. The modeling of the signal phase in a rolling step way was chosen in the traditional urban traffic signal selforganizing control, the control strategy was updated by establishing both the assignment rules of traffic flow and the expected green time, this update was used to dealing with the complexity of each selforganizing unit in the system, such as road composition, intersection connection and traffic flow randomness. On the basis of the traditional strategy, first, state constraints were added to improve the rationality of rules at the intersections under each signal phase, the basis for the coordination of traffic efficiency between adjacent intersections was provided after the optimization of its own parameters infected by the state constraints. Then, the transmitting of the microscopic traffic flow was simulated through cellular transfer model, and the continuous transmission way of queues at intersections was calculated by this simulation, so that the release requirements for the intersection and the flow distribution rules could be both established based at the same time under the signal phase between the upstream and downstream. Lastly, the signal phases were dynamically allocated under the calculated release requirements, the allocation was constrained by the different traffic volume from upstream intersection and the current maximum allowed traffic flow at the downstream intersection, based on the release requirements, the expected green time was calculated after allocation, so that the optimization method of signal phase modeling could be completed. The results show that the optimized modeling method can not only improve the traffic efficiency of selforganizing control in congested and noncongested road conditions, but also effectively reduce the overall time of each intersection in congested state, so that the overall traffic capacity of the intersection groups can be improved, which is also the way to realize a synchronous optimization of single point control and smallscale area control. 13 figs, 27 refs.

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更新日期/Last Update: 2020-07-31