## 2 Literature Review
collected continuous lateral acceleration data from 83 drivers and developed a model supported by support vector regression to assess the lateral acceleration of vehicles on interchange ramps [20]. [PERSON] et al. developed the Driving Style Diagram (DSD) model by overlapping the driving experience zone with the friction circle under constraints to obtain the G-G diagram [21], which is used to assess the safety of driving behavior. Longitudinal acceleration is the rate of change in vehicle speed in the longitudinal direction and reflects vehicle speed variation and driving performance. Many studies have combined analyses of vehicle lateral and longitudinal acceleration data to provide a more comprehensive evaluation and quantification of acceleration characteristics and their relationships. [PERSON] et al. quantified the variations in the instantaneous longitudinal and lateral accelerations in basic safety messages [22]. [PERSON] et al. analyzed and quantified the impact of driver age, sex, vehicle class, and location on longitudinal and lateral acceleration [23]. [PERSON] et al. proposed a method to describe the relationship between lateral acceleration, longitudinal acceleration, and speed, and used it to assess driving behavior safety [24]. A model for the rate of change in lateral acceleration considering the horizontal, vertical, and lateral directions was established by [PERSON], and the comfort and safety of vehicles were analyzed [25]. [PERSON] et al. analyzed the operational characteristics and driving risks of interchange ramps based on vehicle lateral and longitudinal acceleration data [26]. In the distinctive environment of underground roadways, acceleration also exhibits certain characteristics. [PERSON] et al. [27] analyzed the operating characteristics of vehicles on urban underground spiral ramps based on vehicle acceleration value, and found that drivers' deceleration value during cornering on continuous downhill sections is higher than acceleration. [PERSON] et al. [28] found that lateral acceleration at curves in underground roadways increases during the entry phase of a curve, remains relatively stable in the middle of the curve, and decreases during the exit phase. When vehicles travel on curved roads, they are subject to lateral forces. These forces, combined with limited visibility for the driver, cause the stability of the vehicle during driving to be inferior to that on straight roads. Consequently, the incidence of traffic accidents on curved roads is generally higher than that on straight roads [29]. Investigating the characteristics and influencing factors of accidents on curved roads helps improve the safety of these curves. [PERSON] et al. explored the relationship between the radii of horizontal curves and accident rates and found an inverse relationship between radius size and accident rate [30]. [PERSON] et al. analyzed the severity of accidents on curved roads using Bayesian networks [31]. Many researchers have also developed statistical models related to curve acceleration and speed. [PERSON] et al. proposed a reverse horizontal curve lateral acceleration model using vehicle dynamics modeling and multivariate modeling methods [32]. [PERSON] et al. analyzed the relationship between vehicle speed and curve radius on curved roads and developed a predictive model for the speed-radius relationship [33]. Considering the relationship between the geometric alignment of curves and the driver speed, [PERSON] et al. assessed the impact of the horizontal geometry and desired travel speed on driver speed and acceleration behavior on curved highways [34]. [PERSON] et al. found that the curve radius has the greatest influence on V85 speed [35]. [PERSON] et al. discovered that the horizontal curve radius in highway tunnels is significantly lower than that on open roads, and the difference increases with higher design speeds [36].