A Decision-making Model for Electric Vehicle Operators Charging Considering Time Perception and Risk Preference

The decision-making behavior of electric vehicle owners is co-determined by both objective factors and subjective preferences, which has irrational characteristics. To describe this irrational charging decision behavior more accurately, a decision-making model for electric vehicles charging was established with three factors taken into account: earnings, time, and risk. Firstly, the risk evaluation was incorporated into the decision-making process of heuristic inter-temporal decision-making, establishing an improved inter-temporal decision-making model that incorporates risk preferences. Secondly, the historical data of mileage and individual customer revenue during different time periods throughout the day were fitted, obtaining the income curve of typical electric vehicle operators. With the typical electric vehicle operator as the reference, a time perception model was established based on Doppler time dilation and contraction, so as to describe the subjective perception of time by electric vehicle operators. Finally, the decision-making of the electric vehicle operator charging was conducted by considering earnings, time, and risk comprehensively. Through simulation analysis of the charging decision made by electric vehicle operators in Shenzhen, it is observed that compared to conventional inter-temporal decision-making models, the model developed in this study exhibits distinct risk preference characteristics in the decision-making process of electric vehicle operators. Moreover, the preference of electric vehicle operators for immediate or delayed charging options varies with their emotional states. The results indicate that the proposed model offers a more precise depiction of the irrational decision behavior of electric vehicle operators from the perspective of time perception and risk preferences. It aligns with empirical regularities and provides insights for investigating the charging behavior of large-scale electric vehicles.