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Due to the increase of the recognition depth, the inner data of the braking intention of the unmanned vehicle will expand excessively, which leads to the low integrity of the data collection and the poor recognition accuracy. Based on densenet, a recognition method of brake diagram of unmanned vehicle is proposed. Select the deep data collection system, collect the internal data of the unmanned vehicle braking intention, combine the battery protection model to deeply decompose the energy consumption of the internal operation process of the vehicle, integrate the identification data of the unmanned vehicle braking intention based on the initial internal data collected, split and integrate the data to prevent the excessive expansion of the data. Using densenet's high learning degree and self-adaptive learning ability, weighting and equalizing the internal data calibration function, setting a group of basis functions, selecting the corresponding densenet to copy the internal data function, self-adaptive analyzing the copied data, and completing the brake intention recognition. The experimental results show that the integrity of brake intention data collection is improved by 15.21%, and the recognition accuracy is improved by 23.68%.