## 2 Literature Review
### Studies on Vehicle Skidding Based on the Data-Driven Method  
Research efforts and crashes data showed that more than 90% of crashes were related to risky driving behaviors, the more common ones being speeding, improper braking, and steering [6]. [PERSON] et al. [42] proposed an LSTM + Transformer model to analyze risky driving behaviors by using a Transformer for spatial-temporal feature extraction and an LSTM for learning traffic flow patterns. Their empirical analysis on a Chinese freeway revealed that increased frequency, duration, and acceleration of risky braking behaviors heighten crash risks by affecting more vehicles. [PERSON] et al. [43] integrated crash data experienced over a four-year period with three months of microscale driving behavioral data and detected a high propensity of drivers to decelerate at high rates (4 m/s\({}^{2}\) or more) on the segments with high crash rates. In a study by [PERSON] [44], driver behaviors (speeding, acceleration, and braking) and their correlation with crash risk were examined using data collected from an in-vehicle device equipped with GPS and on-board diagnostics. It was found that drivers involved in skidding crashes showed significant acceleration and deceleration activities. Similarly, [PERSON] et al. [45] used a high-fidelity driving simulator to investigate the effects of situational urgency on drivers' collision avoidance behaviors and observed that drivers quickly released the accelerator and applied maximum braking force with increasing situational urgency. In addition, vehicle characteristics, especially the braking-system performance and tire properties have been shown to affect skidding [23; 40]. An analysis of crashes in Florida revealed a reduction in skidding-related crashes by 6% and 8% for ABS-equipped passenger cars and trucks, respectively [23]. Modern vehicles, including both passenger cars and trucks, are typically equipped with an anticlock braking system (ABS) to prevent wheel lock during hard braking or mitigate crash damage. The skid resistance of tires on pavement surfaces, influenced by tire type, inflation pressure, deformation, slip ratio, and slip angle, plays a significant role in vehicle skidding [39; 40; 46]. The data showed that the crash rate associated with skidding in wet weather is significantly higher than that in dry weather [39; 40]. [PERSON] et al. [47] developed a fuzzy-logic model for predicting the risk of crashes that occur on wet pavements by using crash data and the corresponding traffic data collected from 123 sections of highway in Pennsylvania from 1984 to 1986. While the existing studies have contributed to our understanding of the relationship between braking maneuvers and skidding, there are still several gaps that need to be addressed:  
1. Braking maneuvers are closely related to the crash rate, but this relationship has not been quantified. 2. The data-driven method can't explain the underlying mechanisms of the effect of braking maneuvers on vehicle skidding. 3. The data-driven method has its own characteristics. This method demonstrates significant advantages in exploring the microcharacteristics of driver braking behavior. In summary, through the literature review, the following gaps are found:  
* The road geometric design based on the point mass model cannot reflect the truck attributes, nor does it account for the effect of braking maneuvers on truck skidding. * Researchers have proposed the utilization of the bicycle model to analyze the influence of braking on skid safety in flat curved road segments. However, it still remains a challenge of incorporating the dynamic effects induced by braking into the model without making it unsolvable. * A relatively comprehensive and uncomplicated model is needed to describe the road-vehicle interaction. When developing this model, it is crucial to consider dynamic changes in brake force distribution, vertical tire load, as well as longitudinal and lateral friction during braking.