To identify the primary types and distribution patterns of risky driving behaviors at the entrance and exit of the highway tunnel, a risk driving behavior spectrum was constructed based on trajectory data. Firstly, trajectory data were collected through continuous video surveillance of Liupan Mountain Tunnel in Ningxia. Vehicle traffic characteristics at tunnel entrance and exit were analyzed and four categories of risky driving behaviors were selected, including rapid speed change, serpentine driving, dangerous following, and dangerous lane changing. Then, the measurement of risk method was applied to quantify four types of risky driving behaviors, and quartile deviation and criteria importance though intercriteria correlation (CRITIC) were used to determine the threshold values of risky driving behavior characteristics and weights, and the characteristic values of drivers' risky driving behavior spectrum were calculated. Finally, driving behavior scores were compared with characteristic thresholds, and the spatial distribution of hazard points for typical risky behaviors of dangerous drivers was statistically analyzed. The results of the study show that high-risk drivers in the entrance/exit sections of the tunnel mainly show the behaviors of rapid speed change or serpentine driving, in which the rapid speed change behavior has the most significant effect on the total score of the risky behavioral spectrum of the drivers. Vehicles have large speed variations at both the inside the tunnel entrance and outside the exit from 0 to 50 meters. Moreover, larger speed changes are observed at the exit section (0-50 m) compared to the entrance section, and risk points for rapid speed change behavior of dangerous drivers are also more concentrated in that segment. The lateral offset values outside the tunnel entrance/exit are larger than those inside the tunnel, and the risk points for serpentine driving behavior of dangerous drivers are mainly distributed in the range of 0-50 meters outside the tunnel entrance and exit. Risky driving behavior spectrum based on trajectory data can assess and quantify the risk level of drivers in the tunnel entrance/exit sections, facilitating precise identification of high-risk drivers.