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中文摘要：
为寻求计算高速公路主线车辆最佳行驶速度的有效方法,将影响速度的因素进行了分析处理,给出了具有多层模糊决策的最佳速度模糊逻辑,应用神经网络记忆和学习模糊规则,同时对神经网络的初始权值采用遗传算法进行标定,避免陷入局部极值,加快收敛.仿真结果表明：该方法能够针对高速公路的交通流实际状况,充分利用与速度有关的因素来确定高速公路主线最佳行驶速度,克服了传统算法依靠历史数据或建模困难的缺陷,得到的最佳行驶速度值具有实时性好、准确度高.
英文摘要：
Seeking to calculate the best driving speed on the mainline of freeway,factors affecting the speed have been analyzed and proceed.Multi-layer fuzzy decision system with the best speed of fuzzy logic has been put forward.Then,neural network is adopted to memory and learn the fuzzy rules after the initial weights of neural network had been calibrated by the genetic algorithm in order to speed up the convergence and avoid falling into local minimum.The simulation results show that the method can address the actual situation of traffic flow and make full use of speed-related factors to determine the best driving speed on the mainline.The method can overcome the traditional method excessively reling on historical data and modeling difficulty.The best driving speed has the character of real-time and high accuracy which provide a reliable method for variable speed limit control on freeway.
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