Abstract
With the application of vehicles to everything (V2X) technologies, drivers can obtain massive traffic information and adjust their car-following behavior according to the information. The macro-characteristics of traffic flow are essentially the overall expression of the micro-behavior of drivers. There are some shortcomings in the previous researches on traffic flow in the V2X environment, which result in difficulties to employ the related models or methods in exploring the characteristics of traffic flow affected by the information of generalized preceding vehicles (GPV). Aiming at this, a simulation framework based on the car-following model and the cellular automata (CA) is proposed in this work, then the traffic flow affected by the information of GPV is simulated and analyzed utilizing this framework. The research results suggest that the traffic flow, which is affected by the information of GPV in the V2X environment, would operate with a higher value of velocity, volume as well as jamming density and can maintain the free flow state with a much higher density of vehicles. The simulation framework constructed in this work can provide a reference for further research on the characteristics of traffic flow affected by various information in the V2X environment.
Highlights
In the last few years, the informatization degree of traffic system has been substantially increasing with the application of intelligent and connected technologies
We propose a simulation framework based on the car-following model and cellular automata (CA) in this work to quantitatively analyze the traffic flow affected by generalized preceding vehicles (GPV) information in the V2X environment by employing velocity, volume and density as indicators
We proposed a simulation framework based on the car-following model and the CA, employed the TFSF in the quantitative analysis of traffic flow affected by the GPV information in the V2X environment
Summary
In the last few years, the informatization degree of traffic system has been substantially increasing with the application of intelligent and connected technologies. In the vehicles to everything (V2X) environment, drivers can obtain massive traffic information with the technologies mentioned above and, according to the information, adjust their car-following behavior, which will further influence the characteristics of traffic flow [16,17,18]. The impacts of individual motion state information of vehicles, including headway, velocity and acceleration, on car-following behavior and traffic flow were explored in [19,20,21,22,23,24,25,26,27]. Results of the above research suggest that individual as well as overall motion state information of preceding vehicles in the current lane can assist drivers to optimize their car-following behavior and, stabilize the traffic flow to a different extent.
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