基于遗传算法的地铁列车自动驾驶控制算法研究

轨道交通列车运行曲线的控制是轨道交通列车自动化的核心技术。通过提出改进的遗传算法来设计列车ATO（列车自动驾驶）控制算法，使用某城市地铁列车参数建模，编制实用的遗传算法生成列车时分控制曲线的程序，并进行计算机仿真，仿真的结果达到了：输出时间与给定的定时值完全一致；能耗比节时模式降低56%；停车点精度｜x｜=14cm，小于规定值（25cm）；最大速度小于规定值；具有较高的全局适应度。表明算法效果良好、性能优越。

Research on the GA-based ATO control algorithm

Abstract： The controlling of train’s operation curve is the key technique for automation of rail train. An improved genetic algorithm is applied to design the controlling algorithm of ATO travel interval. Constructing model and programming is done for the controlling of train’s operation curve with the subway train operation parameter of a given city’s demand. Through the simulation results we can get that： output time is completely the same as the expected time; energy consumption is reduced by 56 % as compared to that of the mode of time-saving; the parking accuracy ｜x｜=14cm, which is smaller than specified value （25cm）; the maximum speed is smaller than specified value; the global optimization performance evaluated by fitness function is excellent. The method is effective and of good performance.