百度无人驾驶apollo项目驾驶行为决策模块深度神经网络算法模型

apollo这一快没提供，可以使用以下的算法模型

learning_rate = 1e-4

activation_relu = ‘relu’

model = Sequential()

model.add(Lambda(lambda x: x / 127.5 – 1.0, input_shape=(64, 64, 3)))

model.add(Convolution2D(24, 5, 5, border_mode=‘same’, subsample=(2, 2)))

model.add(Activation(activation_relu))

model.add(MaxPooling2D(pool_size=(2, 2), strides=(1, 1)))

model.add(Convolution2D(36, 5, 5, border_mode=‘same’, subsample=(2, 2)))

model.add(Activation(activation_relu))

model.add(MaxPooling2D(pool_size=(2, 2), strides=(1, 1)))

model.add(Convolution2D(48, 5, 5, border_mode=‘same’, subsample=(2, 2)))

model.add(Activation(activation_relu))

model.add(MaxPooling2D(pool_size=(2, 2), strides=(1, 1)))

model.add(Convolution2D(64, 3, 3, border_mode=‘same’, subsample=(1, 1)))

model.add(Activation(activation_relu))

model.add(MaxPooling2D(pool_size=(2, 2), strides=(1, 1)))

model.add(Convolution2D(64, 3, 3, border_mode=‘same’, subsample=(1, 1)))

model.add(Activation(activation_relu))

model.add(MaxPooling2D(pool_size=(2, 2), strides=(1, 1)))

model.add(Flatten())

model.add(Dense(1164))

model.add(Activation(activation_relu))

model.add(Dense(100))

model.add(Activation(activation_relu))

model.add(Dense(50))

model.add(Activation(activation_relu))

model.add(Dense(10))

model.add(Activation(activation_relu))

model.add(Dense(1))

model.summary()

model.compile(optimizer=Adam(learning_rate), loss=“mse”, )

模型基于keras,后台使用tensorflow