# Queue Spillover Management in a Connected Vehicle Environment
## 1 Introduction  
With the continued increase of vehicle ownership, traffic congestion has become a major issue in urban areas, particularly at major intersections, where large numbers of vehicles are lined up at the intersection, especially in the morning and evening rush hours. In view of unreasonable traffic signal control settings, it is very easy to cause traffic jams, and when the queues accumulate, serious problems of traffic congestion in the area will be caused. Studying methods and measures to prevent spillovers at intersections, has always been an important part of urban traffic control. At present, there are two main types of methods in solving traffic congestion: (1) Vehicles and traffic signals are independent individuals, and scholars only focus on the traffic signals. (2) Vehicles and traffic signals are no longer split, but are related through a certain communication mode, that is, the Internet of Things; vehicles and traffic signal controllers can realize information traffic. To solve the aforementioned problems, many alternative methods have been considered over the years. The prevention of overflow at intersections is generally divided into two steps: (1) It is necessary to judge whether there is an overflow at an intersection or there is an overflow trend. (2) Make corresponding decisions according to the judgment results. The method to identify spillovers as described in Reference [1] is relatively complex, and it is developed with the assumption that the residual queue length at the beginning of red signal phase is known. Meanwhile, the three break points described in References [2; 3] which indicate a change in traffic state, are difficult to identify when the bus ratio to the traffic flow is high. [PERSON], proposed a red-band control strategy to ease traffic congestion [4]. With the control of the red band and the green band, a coordinated controlstrategy was proposed by [PERSON] [5]. Based on the cellular transmission model, [PERSON], suggested highly random and dynamic characteristics of the spatial and temporal distribution of the evacuation traffic flow [6]. A fast-predictive control model (MPC) was developed to solve the highway congestion problem [7]. [PERSON] proposed a new method, called the Cellular Automated Route Network Model, based on [PERSON], [PERSON], and [PERSON] to reduce the probability of traffic jam by predicting it in advance [8]. [PERSON] used the EPS (Elimination Pairing System) system to optimize the traffic signal timing at the intersection of supersaturated points. This method is superior to the traditional Webster method [9]. In recent years, with the rise of new technologies such as the Internet of Things, big data, and \"Internet +\", the intelligent transportation system has also made great progress in intelligent network connection and vehicle networking. V2X (Vehicle to Everything) network communication technology will become an important technical support for the development of intelligent driving in the future and it will become the basis of the connected vehicle. V2X network connection, is a wireless communication technology based on the Internet of things. It uses D2D (Device to Device) and information communication technology to connect vehicles to the outside world. V2X network communication integrates V2N (Vehicle to Network, vehicle-internet), V2V (Vehicle to Vehicle), V2I (Vehicle to Infrastructure), and V2P (Vehicle to Pedestrian). (1) V2N connects vehicles to the cloud server mainly through the Network, and it can use functions such as entertainment navigation on the cloud server; (2) V2V refers to information exchange with different vehicles; (3) V2I mainly includes the communication between vehicles and Infrastructure, such as road traffic light barriers, and is used to obtain road management information, such as the timing sequence of traffic signals and the location of road obstacles; (4) V2P refers to the interaction between vehicles and pedestrians or non-motor vehicles, mainly providing safety warnings.