## 1 Introduction  
Autonomous vehicles (AVs) and advanced driver assistance systems (ADASs) have the potential to decrease the likelihood of accidents. Lidar and camera technology, among others, are currently used by AVs and ADASs to detect roadway geometry designs and the surrounding environment. The free-flowing traffic environment of the freeway is a crucial application scenario for both AVs and ADASs. In this scenario, the geometric design of the roadway plays a key role in ensuring driver safety and comfort, especially considering the absence of surrounding vehicles. For example, when driving around a curve, human drivers tend to feel uncomfortable if the AV or ADAS regulates the level of speed beyond what they would expect. Additionally, if the AVs are too close to the lane boundary in a curve, the human driver would experience discomfort. These problems arise from the insufficient analysis of drivers' micro-driving behavior and habits. Understanding how roads' geometric design impactson drivers' behavior is essential for enhancing human-like automated driving from the perspectives of safety and comfort. And, it can provide a basis for improving the control strategies of AVs and optimizing ADASs [1; 2]. Particularly for combined curves (combining the horizontal and vertical curves), previous research indicates that there is a greater risk of accidents on combined curves compared to single horizontal and vertical curves [3; 4]. When approaching combined curves, drivers tend to be more cautious and alert. They control the vehicle's speed and trajectory in a more complex way and adjust the driving process more frequently. AVs and ADASs will help drivers reduce driving risks in combined curves. Improving these systems requires a thorough understanding of human drivers' micro-driving behavior and habits in combined curves, as well as comprehension of how the geometric design of combined curves affects human micro-driving behavior. Micro-driving behavior is typically quantified through indicators such as vehicle speed, trajectory, acceleration, and deceleration, which can reveal the driver's cognitive and perceptive abilities, as well as their capacity to navigate the road safely. Ensuring both lateral and longitudinal safety is crucial when driving. In this study, both the lateral micro-driving behavior and the longitudinal micro-driving behavior in the combined curve are focused on. Drivers' speed change is a crucial metric for evaluating the feasibility of a proposed design because it is a key predictor of both operational efficiency and safety [5; 6]. When the geometric design calls for speed variations beyond safe limits, drivers may engage in unsafe maneuvers. Given the relatively high speeds on highways, such maneuvers may result in severe accidents. Some studies, however, have neglected the increase in speed [5; 7], which poses a more significant danger than driving at slower speeds. Consequently, this study places significant emphasis on analyzing substantial speed increases. Lane departure, which occurs when a vehicle moves out of its current lane is a critical surrogate measure for evaluating road safety. On divided roadways, lane departure can cause rear-end and side-swipe collisions, while on undivided roadways, it can result in head-on crashes. Lane departure is the primary cause of single-vehicle crashes [8]. The Louisiana Department of Transportation and Development's accident database shows a total of 83,843 accidents on Louisiana's R2L highways from 2008 to 2017. These accidents were mainly caused by lane departure, which accounts for about 65%. The Louisiana Strategic Highway Safety Plan (SHSP) has identified lane departure as one of the five key areas to address [9]. In China, approximately 42% of traffic crashes over the past 15 years have been linked to lane departure [10]. Nonetheless, the correlation between lane departure behavior and combined curve geometric design remains uncertain. Previous studies have investigated the relationship between combined curve design and micro-driving behavior.