# Characteristic Analysis and Decision Model of Lane-Changing Game for Intelligent Connected Vehicles
## 1 Introduction  
Vehicle following and lane changing are the two most important research directions in road traffic, though vehicle lane changing has more complex traffic characteristics than vehicle-following behavior, reflecting the competition between vehicles in adjacent lanes for the right of way in time and space [1]. The application of IoT technology has promoted the development of the autonomous driving industry and facilitated the safety and reliability of vehicles [2]. With the application and popularity of IoT devices, information sharing between urban road facilities and vehicles or other facilities is achieved through IoT technology, laying the foundation for the future development of intelligent transportation [3]. Assisted driving or autonomous driving technology has also been developed rapidly as a result, and more and more vehicles are equipped with advanced assisted driving systems to help drivers reduce the driving burden and improve vehicle safety. Vehicle lane changing is a topical and difficult problem in autonomous driving technology. Vehicle lane changes can usually be divided into free lane changes and mandatory lane changes, and the vehicle in the free lane-change scenario usually pursues a higher driving speed or driving comfort, while the mandatory lane change is lane-change behavior made by the vehicle due to the limitation of road conditions, and the process reflects the best decision made by the driver after perceiving the change of information of the surrounding traffic environment and weighing up the gains and losses. Vehicle decision making is one of the core modules of autonomous vehicles and a process that integrates vehicle travel efficiency and safety [4]. Existing research on vehicle lane changes usually focuses on lane-change model control, trajectory prediction, etc. However, the study of vehicle lane-change interaction characteristics and the study of lane-change game mechanisms have not received sufficient attention. Although many game theory-based vehicle lane-changing models have high decision accuracy and reliability, researchers usually apply thegame results directly to the control aspects of the model and lack a deeper analysis of the lane-changing game mechanism. The objective of this paper is to propose an evolutionary game-based vehicle lane-changing decision model, to study and analyze the characteristics of vehicle lane-change interactions, the convergence direction of decision combinations, and the impact of the evolutionary game lane-change decision on vehicle safety. The evolutionary game is a theoretical approach to analyzing the rationality of decision making through dynamic evolutionary equations, which can consider the limited rationality of decision makers and reduce the assumptions of the model compared with other game models. At present, the research on vehicle lane changes mostly focuses on the highway [5; 6; 7] and intersection scenarios [8; 9], because these scenarios belong to traffic bottleneck sections, and vehicle lane changing in bottleneck sections is a difficult problem. In this paper, taking the urban intersection road as an example, the forced lane-change interaction characteristics of connected autonomous vehicles are analyzed; the convergence process of vehicle lane-change decisions is dynamically analyzed by an evolutionary game model, and sensitivity analysis of the main factors is conducted to explore the influence of road traffic environment changes on vehicle lane changes; and the vehicle trajectory and output collision time are simulated by SUMO to analyze the collision risk of vehicles; and, finally, further research is summarized and extended. The organization of this paper is as follows: Section 1 introduces the research on lane changing for autonomous vehicles. Section 2 reviews the relevant studies on the vehicle lane-change game. Section 3 analyzes the game characteristics of vehicle lane changes with the example of an intersection roadway.