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摘要: 提出一种基于模糊逻辑控制的交叉路口群信号控制器, 通过收集由交叉路口检测器获得的车流量信息制定模糊控制规则, 给出交叉路口绿灯相位和相位转换次序, 以控制路口信号, 并与相邻路口的信号进行协调。仿真结果表明, 该控制器能适应多个路口的车流变化, 减少车辆平均延误。Abstract: This paper presented a fuzzy logic controller and made a comparison of its performance with other controllers. The fuzzy rules was established by gathering the traffic flow information from the detectors placed in different intersections, and the green phase and the phase sequences at an intersection were obtained to control its traffic signals and cooperated with its neighbors. Simulation results show that the presented controller can adapt to the conditions of traffic flow well, and decrease the average delay time at multi-intersections.
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Key words:
- urban traffic control system /
- fuzzy logic controller /
- intersections group /
- signal
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表 1 输入输出变量的隶属度函数
Table 1. Fuzzy set of input/output variables
输入输出变量 隶属度函数 基本论域 输入变量 绿灯相位车辆数gflow 无, 少, 中, 多, 很多 [0, 40] 红灯相位等待车辆数rwait 无, 少, 较少, 中, 偏多, 多, 很多 [0, 56] 红灯相位等待时间rtime 无, 少, 中, 长, 很长 [0, 40] 输出变量 绿灯相位延长时间gextend 无, 少, 中, 长, 很长 [1, 10] 绿灯相位状态gstate 维持, 改变 {1, 0} 表 2 部分模糊规则
Table 2. Some rules of fuzzy controller
gflow Rwait rtime gextend gstate 规则1 无 较少 中 改变 无 规则2 少 较少 少 维持 少 规则3 中 无 中 维持 很多 规则4 多 偏多 长 改变 无 …… …… …… …… …… …… 表 3 两种模糊控制的仿真结果比较
Table 3. Simulation results of three groups under two controller
交叉路口群1 交叉路口群2 交叉路口群3 本文方法车辆延误/s 39.16 49.75 74.15 文献[6]中方法车辆延误/s 39.36 50.15 75.27 结果比较/% 5.08 7.97 14.87 -
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