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摘要: 为研究城市主干道交通信号协调优化问题, 建立了包括交叉口交通信号显示模块与信号相位转换模块的时延Petri网模型与基于变速度连续Petri网的交通流模型, 设计了由监控、判别和通行相位选择3个子系统构成的交通信号控制系统, 并给出了具体的控制步骤。根据连续Petri网中各参数间的关系, 以车辆排队长度、上游路段车流速度和下游路段畅通度为输入变量, 以相位优先指数为输出变量, 确定下一通行相位, 采用模糊Petri网确定当前相位的最佳绿灯时间, 并进行了仿真计算。仿真结果表明: 采用Petri网与模糊控制相结合的方法后, 由西向东与由东向西方向车流的行程时间分别缩短了7.1%、7.6%, 交叉口排队长度的改进率分别为11.9%、11.2%, 4个相位的交叉口平均延误分别由9.7、10.3、11.8、13.2 s下降到8.2、9.1、11.4、11.4 s。可见, 主干道信号协调优化方法可以较好地实现干线信号协调控制。Abstract: To study the traffic signal coordinated optimization of urban arterial road, a timed Petri net model with a traffic signal display module and a signal phase transition module, and a traffic flow model based on continuous Petri net with variable speeds were established.A traffic signal control system composed of 3 subsystems for monitoring, discriminating and current phase selecting was designed, and concrete control steps were presented. Considering the relationship of parameters in continuous Petri net, next green phase was determined by taking vehicle queue length, traffic flow velocity at upstream section and open degree at downstream section as input variables, and phase priority indexes as output variables.The superior green time of current phase was determined by using fuzzy Petri net, and a simulation calculation was carried out. Simulation result indicates that by combining Petri net with fuzzy control, travel times respectively shorten by 7.1% and 7.6% for west-to-east and east-to-west traffic flow, and the improvement rates of queue length at intersection are 11.9% and 11.2% respectively. The average delays of four phases at intersection decrease from 9.7, 10.3, 11.8, 13.2 s to 8.2, 9.1, 11.4, 11.4 s respectively. So, traffic signal coordinated control on urban arterial road is better realized by using traffic signal coordinated optimization method.
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Key words:
- traffic signal control /
- coordinated optimization /
- fuzzy control /
- Petri net /
- priority index
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图 2 交叉口交通流连续Petri网模型
Figure 2. Continuous Petri net model of traffic flow at intersection
图 3 子区段交通流连续Petri网模型
Figure 3. Continuous Petri net model of traffic flow at road section
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