## 4 Discussion  
The macroscopic characteristics of traffic flow are essentially the overall expression of the microscopic behavior of individual vehicles in the system. The application of the V2X technology to the traffic system significantly enhanced the information perception ability of drivers and, thus, affects their car-following behavior, which will cause differences in the characteristics of traffic flow. The impacts of various connected information on drivers' car-following behavior and traffic flow have been explored in the previous research [19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32], and the car-following behavior as well as the stability characteristics of traffic flow affected by various connected information have been studied. However, quantitative analysis of the operating characteristics of traffic flow affected by the GPV information in the V2X environment is still absent. The influence of connected technology on the traffic system has attracted more and more attention, and many achievements have been reported [38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74]. The impacts of V2X and other connected technologies on the traffic system have been discussed based on various theories and methods in the previous research. However, there are some limitations for these efforts to answer the question of the impacts of GPV information on traffic flow in a quantitative way, including the continuous medium models [38; 39; 40; 41; 42; 43] as well as its limitations mentioned in the previous section. In addition to the continuous medium models, the research [70; 71; 72; 73; 74] based on the Intelligent Driver Model as well as other related methods is another research hotpot in the field. These efforts focus on the impacts of the cooperative adaptive cruise control (CACC) system  
Figure 10: The operation of traffic flow in the unconnected environment: (**a**) Before exerting the disturbance; (**b**) After exerting the disturbance. equipped on the traffic flow, and the impacts of various connected information, especially the GPV information, on the traffic flow are not explored in those efforts. Moreover, there are many difficulties in employing the models as well as the methods used in these efforts to explore the impacts of various information on the traffic flow. On the one hand, the CACC system is a longitudinal driving assistance system that assists the driver to manipulate the vehicle to follow the preceding vehicle (fleet) in the current lane. The preceding vehicles in the adjacent lanes are not considered in the system, with the result that the corresponding efforts cannot be used in the exploration on the impacts of GPV information on traffic flow. On the other hand, as a driving assistance system, the CACC system can automatically respond to the motion of the preceding vehicles in the current lane, with the result that the corresponding efforts cannot be used in the exploration of the impacts of difference attention degree of the connected information on traffic flow. In summary, the previous achievements are not suitable for answering the question of the impacts of GPV information on traffic flow in the V2X environment. Motivated by this, we proposed a simulation framework (the TFSF) based on the car-following model and the CA, then employed the TFSF in the quantitative analysis of traffic flow affected by the GPV information in the V2X environment. The research results suggest that there is a significant positive influence of the GPV information on the traffic flow in the V2X environment. As shown in Figures 5-8, the traffic flow affected by the GPV information could maintain the free-flow state under the condition of a much higher density of vehicles, and the maximal volume of the traffic flow at the free-flow state is much higher than that in the unconnected environment.