# An Intersection Signal Control Mechanism Assisted by Vehicular Ad Hoc Networks
## 1 Introduction  
An efficient traffic management system is the base and essential prerequisite for economic and social development. Intersection management is one of the most challenging issues in urban transportation. The area ratio of intersections in urban road networks is too small; however, according to statistics, 64.31% of urban road traffic accidents in China occur at intersections and their vicinity [1], and the time lost in vehicle trips at intersections accounts for the largest part of the total time lost. A sophisticated and reliable intersection management mechanism can greatly increase the urban transportation efficiency and ensure people's travel safety. The research on intersection signal control has been developing and evolving in recent years. In terms of the control range, it has gradually evolved from a single intersection to multiple intersections and an urban region [2; 3]. In terms of control methods, it has developed from the traditional fixed period timing to the full induction and adaptive control methods [4; 5; 6]. [PERSON] et al. [7] proposed a signal control optimization model for urban multi-intersections using three-phase theory and information-exchanging. [PERSON] et al. [8] proposed a group-based signal optimization model that considers both the safety and delay for the intersections with mixed traffic flows. [PERSON] et al. [9] designed an optimization approach in which a particle swarm optimizer (PSO) can find successful traffic light cycle programs. A multi-stage decision model to minimize the waiting time is proposed in [PERSON] et al. [10]. The model takes advantages of the structure of the minimum green and red time, which significantly reducesthe model scale by properly choosing the system states and control actions. In order to alleviate its traffic pressure effectively, a coordinated arterial traffic type-2 fuzzy logic control (FLC) method [11] is proposed. The method allocates green time according to the traffic situation of each intersection; meanwhile it adjusts each intersection's green time based on the vehicles between the intersection and the downstream intersections for the purpose of enlarging the green wave band. [PERSON] et al. [12] proposed an optimization model for network progression coordinated control that enables the phase time and phase sequence of each intersection to be freely valued within the solution space, and realizes the comprehensive optimization of the phase time, as well as a common signal cycle, phase sequence, and offset. [PERSON] et al. [13] proposed an adaption of RED (random early detection) by incorporating an active queue management technique inherited from data networks into vehicle traffic management at the signalized intersections. A vehicular ad hoc network [14] (VANET) is based on the concept of an Internet of Vehicles (IoV) [15] in the category of network forming. As a special type of mobile ad hoc network (MANET), VANET has unique characteristics, such as a high mobility of nodes, restricted forwarding directions, and many influencing factors. The vehicle to vehicle (V2V) communication and the communication between vehicles and the infrastructure (V2I) provide guarantees for the accurate, real-time, and comprehensive information acquisition and dissemination in an intelligent transportation system (ITS) [16; 17; 18; 19; 20]. It plays an active role in improving the quality of urban transportation services. [PERSON] et al. [21] proposed a framework for the real-time distributed classification of congestion into its components on a heterogeneous urban road network using a VANET. [PERSON] et al. [22] synthesized and studied methods that are used to optimally group autonomously controlled vehicles so they can travel along a highway in platoons. Vehicular formations are structured to yield an effective autonomous mobility operation and to realize high-performance multihop dissemination of multiclass messaging flows. [PERSON] et al.