Electric vehicle (EV) users' traveling and charging willingness tends to be affected by many certain and uncertain factors. An experimental economics (EE) based simulation method can reflect the game behaviors of participants. It demands enormous resources of qualified human participants, and the comparability among behaviors in a series of repeated experiments. However these 2 conditions are not easy to be satisfied. In order to solve these problems, this paper presents a multi-agent model to describe the respondents' behaviors, which is based on the extraction of multidimensional probabilistic information from their questionnaires. Based on the model, a series of agent-based Monte Carlo simulations have been run repeatedly, which enables the sensitivity analysis. The contribution degrees of EV features on the traveling willingness of the respondents are therefore compared quantitatively such as travel distance, range anxiety, and the number of charge times, etc.