Analysis and evaluation of driving ability based on dynamic personality and ECG signal

In this paper, we carried out the dynamic quantitative analysis and evaluation of driving ability from three-dimensional aspects, including electrocardiogram (ECG) signal, personality, states, and driving behavior. Three kinds of simulated scenarios triggered by the pedestrian crossing the street were established using a virtual reality driving simulator. Fifty licensed drivers completed the driving experiments and filled out the Neuroticism Extraversion Openness Five-Factor Inventory (NEO-FFI) questionnaire to measure the driver's personality baseline. Seven kinds of driving ability evaluation indexes were extracted, and the Analytic Network Process (ANP) was used to establish the driving ability evaluation model. Combined with the theory of dynamic personality, the benchmark driving ability thresholds based on the five personality states were finally obtained. The results showed that the driver's personality state was correlated with the benchmark driving ability. Extroverted and conscientious personality states have higher benchmark driving ability, while neuroticism has the lowest. Besides, the dynamic volatility of driving ability was higher in the high-risk situation. This paper put forward a novel idea for the analysis of driving ability, and the research results provide a personalized database for the driver's real-time driving ability evaluation and correction.