首页> 外文会议>Intelligent Vehicles Symposium, 1996., Proceedings of the 1996 IEEE >Determination of optimal successor function in phase-based control using neural network
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Determination of optimal successor function in phase-based control using neural network

机译:使用神经网络确定基于相位的控制中的最佳后继函数

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A phase-based method for fixed-time signal control of traffic improves significantly the junction performance over conventional stage-based method of control due to the higher flexibility in specification of signal timings, where the control variables comprise the start and duration of green phases and the cycle time at which the junction is operated. The cycle-structure is specified by a successor function, a combination of 0 and 1 for all incompatible pairs of phases, which indicates the order of phases in a cycle. Normal procedure optimises the timings for each of these successor functions to determine the best timing plan. The computing time is found to be approximately proportional the number of such functions. To reduce the computational requirement, and hence enhance its applicability to real-time actuated control, a neural network is employed to help identify the optimal successor function for further optimisation of timings. Encouraging results were obtained.
机译:与传统的基于阶段的控制方法相比,基于阶段的流量固定时间信号控制方法显着提高了结点性能,这是因为信号时序规范具有更高的灵活性,其中控制变量包括绿色阶段的开始和持续时间,以及结点操作的周期时间。循环结构由后继函数指定,对于所有不兼容的相对,0和1的组合表示循环中的相序。正常程序会为这些后继功能中的每一个功能优化时序,以确定最佳时序计划。发现计算时间与这些函数的数量大致成比例。为了减少计算需求,从而提高其在实时执行控制中的适用性,采用了神经网络来帮助识别最佳后继函数,以进一步优化时序。获得了令人鼓舞的结果。

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