Ensuring passenger safety in metro stations is paramount. This research investigates emergency evacuation events and evaluate station evacuation efficiency under various passenger behavioral decisions. We establish an improved social force model incorporating these behavioral decisions. By employing advanced AnyLogic simulation techniques, this research comprehensively deconstructs metro station emergency evacuation dynamics, revealing that passenger behavioral decisions, emotional contagion, and spatial configurations significantly influence evacuation efficiency. It includes various scenarios such as normal conditions, phototaxis behavior, following guidance and exit failures. Compared with the normal conditions, the growth rate of evacuation time under the influence of phototaxis, taking into account the panic psychology, has reached 19.71%. When different exits fail, the evacuation time growth rates of Exit 3 and Exit 4 are the most significant. Considering the panic psychology, their evacuation time growth rates are 53.93% and 28.59% respectively. The study's innovative social force model integrates psychological profiles and spatial factors, providing transportation planners with a nuanced framework for understanding crowd behavior during crisis scenarios. By quantitatively mapping individual psychological characteristics to evacuation performance, the research offers actionable insights into designing more effective emergency response strategies, ultimately enhancing passenger safety in high-density urban transit environments.