According to the personnel evacuation characteristics of highway tunnel, simulation was conducted to analyze the evacuation pattern of different crowds under the mixed behavior mode by using a renovated cellular automaton model (CA). Research on intelligent evacuation system was based on the basic principle of safety evacuation, the installation location of intelligent evacuation direction system, the tunnel space structure and typical fire scenarios, with comprehensive consideration of factors such as path length, exit width, population density and distribution of evacuated people. The effects of visual induction, auditory induction and dual induction on the evacuation process of intelligent evacuation guidance system were studied by changing the range of guidance signals to population evacuation, and a method for intelligent dynamic identification evacuation path based on multi-parameter was obtained. The results of the simulation show that the intelligent evacuation guidance system can offer a dynamic evacuation route via the real-time control of the guidance signals, such as the sound and light indicators, and instruct the people under the fire to choose the most feasible behavior pattern so as to enhance the efficiency of evacuation. Under the different behavior patterns, it would be possible to effectively reduce the evacuation time via the dual induction mechanism of the sound and the light if a crowd manages to choose the appropriate number, location and direction of the induction signals, and enlarge the impact range of those signals. In addition, based on the intelligent dynamic identification algorithm, the evacuation efficiency can be expected to be raised by controlling the working status of induction signals to provide people with dynamic evacuation route.