Under the influence of different external environment and its own factors, many drivers are prone to operate mistakes, which would lead to accidents. Thus, The main purpose of this paper is to analyze the driver's driving state by detecting the driver's heart rate fluctuation parameters. Firstly, wavelet transform was used to denoise the ECG signal of the driver when a driver was in the process of driving simulation. Then, the characteristic value of ECG signal was extracted. Heart rate fluctuations (HRF) analysis from two different angles showed that the fluctuation of heart rate parameters could be obtained directly from the ECG signal, which was related to driving status. Through the comprehensive analysis of the ECG signal, the driving position was redefined as the relative position value of the vehicle to the road centerline during driving, and it was represented by a cloud model. The standard one-dimensional cloud model of drive state was obtained through Python programming. It was found that the expectations and variances of the one-dimensional cloud model may also be related to fluctuations in heart rate parameters. Lastly, the mapping relationship between them was obtained.

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