# Biform Game Approach to Strategy Optimization of Autonomous Vehicle Lane Changes on Highway Ramps
## 1 Introduction
These studies utilizing non-cooperative games have addressed the lane-changing problems of vehicles with competitive tendencies and provided effective solutions and technical means. Similarly, many scholars have researched traffic problems based on cooperative games. [PERSON] et al. [28] proposed a coordination method based on cooperative game theory for the conflict risk in highway merging areas, considering factors such as vehicle type, time demand, and driving intentions, achieving a vehicle adjustment strategy with the lowest virtual payment cost. [PERSON] et al. [29] applied differential games to predict the driving behavior of autonomous vehicles in lane-changing problems, considering factors such as cooperative merging, safe overtaking, and safe distances, ultimately deriving the optimal lane-changing strategy. [PERSON] et al. [30] considered the interaction among multiple vehicles by adopting the extensive-form game theory. They utilized the Nash equilibrium of the generalized game theory, as well as uncertain factors such as estimation and prediction, to conduct prediction and planning. [PERSON] et al. [31] proposed a game-theory-based lane-changing model, which imitates human behavior by interacting with the surrounding drivers through the use of turn signals and lateral movement. In the research on driving models under the Internet of Vehicles (connected vehicle) technology, game theory has played a crucial role. Connected vehicle technology enables vehicles to interact with the outside world, presenting new opportunities for traffic development. Meanwhile, game theory effectively analyzes drivers' behavioral decisions. Non-cooperative game theory has been widely applied in highway lane-changing. [PERSON] et al. [24] proposed a driving decision-making model based on non-cooperativegames. Their model focuses on how individual drivers make decisions in lane-changing scenarios, considering the competition among vehicles. For example, in a multi-vehicle lane-changing situation on the highway, each vehicle tries to maximize its own benefits without considering cooperation with others. This kind of non-cooperative approach helps to understand the basic decision-making mechanisms of drivers in competitive traffic environments. [PERSON] et al. [25] further introduced a dynamic game model. This model can simulate the real-time decision-making adjustment process of drivers during highway lane-changing. Since the traffic situation changes constantly, such as the speed and distance of surrounding vehicles, drivers need to adjust their lane-changing decisions. The dynamic game model captures this dynamic nature, making the analysis more in line with actual driving situations. On the other hand, cooperative game theory also has its applications in highway lane-changing. [PERSON] et al. [28] proposed a strategy based on cooperative games for vehicle-related problems. In the context of highway lane-changing, cooperation among vehicles can improve traffic efficiency and safety. For instance, when multiple vehicles need to change lanes in a congested highway section, they can form a coalition through cooperation. By sharing information and coordinating their actions, they can achieve a more efficient lane-changing process. This is different from non-cooperative games where each vehicle acts independently. In addition to the above, [PERSON] et al. [26] considered drivers' risk preferences in their game-theoretic model. They analyzed the differences in decision-making of drivers with different risk preferences during highway lane-changing in a connected vehicle environment. Risk-averse drivers may be more cautious when changing lanes, while risk-seeking drivers might take more aggressive actions. This research provides a new perspective for understanding personalized driving behaviors during lane-changing.