# Queue Spillover Management in a Connected Vehicle Environment
## 1 Introduction
Connected vehicle refers to a new generation of vehicle which is equipped with advanced on-board sensors and integrates modern communication and network technology, to realize intelligent information exchange and sharing between the vehicle and X (car, road, person, cloud, etc.). In the connected vehicle environment, vehicle information can be obtained in real time through V2I, and the traffic signal controller can control the traffic signal with massive and high-precision data from the Internet of vehicles. Connected vehicle (CV) allows vehicles to transfer data to each other, V2V and V2I. The roadside infrastructure can use the obtained data from V2I to set the traffic signal, corresponding to the traffic demand in real time. Scholars in China and abroad, have made a lot of efforts and contributions to research on the traffic algorithm of intersections based on the Internet of vehicles, and have provided a lot of experience. Researchers at the University of California, riverside, have designed a speed planning algorithm based on traffic lights to allow vehicles to pass through a single crossing. [PERSON] et al. proposed an inductive control method using the Internet of vehicles as the sensor. Through the Internet of vehicles, the relevant information on vehicles was obtained, the time of vehicle arrival at the intersection was predicted, and the green time of behavior was dynamically allocated [10]. [PERSON] et al. assumed that the vehicle roads were all connected with the Internet of vehicles and proposed the control idea of vehicle automatic driving through intersections. The relevant information about vehicles was collected, and a solution to avoid potential conflicts when crossing intersections was provided. However, they did not propose specific models and solutions [11]. [PERSON] et al. proposed a method to realize autonomous driving in the context of the Internet of vehicles and used a genetic algorithm to search the optimal vehicle form speed. However, due to the randomness of genetic algorithms and the limitation of solving large-scale problems, this method was only suitable for intersections with small traffic volumes [12]. [PERSON] et al. used traffic simulation software to open multiple simulation Windows, to simulate the actual road network and predict the traffic status online, and they obtained the optimal signal timing schemes [13]. Scholars have done a lot of research on vehicle to internet. From the perspective of the driver, [PERSON] et al. expounds the internet of vehicles and proposes how to obtain information from the driver in the vehicle cloud system [14]. They also issues such as privacy, service costs, and supply delays [15]. Currently in the field of communications, vehicle to internet is forcused on the management of vehicle and drive service needs, and solve the problem by building a model [16; 17; 18; 19; 20; 21]. Another research hotspot is traffic flow control based on the internet of vehicles. [PERSON] et al. presented a cumulative travel-time responsive (CTR) real-time intersection-controlled algorithm, under the environment of connected vehicles. Using this algorithm, the traffic efficiency and average speed of vehicles at intersections are improved [22]. [PERSON] et al. used the information from connected vehicles to optimize the efficiency of the intersection [23]. Compared with the previous method of calculating the minimum green time and the maximum green time using the deterministic model, [PERSON] et al. used stochastic optimization theory which established a stochastic model to calculate these parameters in real time [24]. [PERSON] et al. used the technology of connected vehicles to solve the Queue length of the traffic flow, and through the VISSIM simulation, the algorithm was proved to be effective [25]. [PERSON] et al. realized the dissipation of the queue, by adjusting the inflow and outflow of the intersection. Three evaluation criteria for queue length were proposed [26]. Queue length is traditionally estimated by using data collected from loop detectors.