Abstract:

This paper proposes an improved cellular automata model that takes into account the physical characteristics of vehicles, such as the amplitude of acceleration and deceleration, relative speed, and safety distance, etc., in order to investigate the effects of electric vehicles on the traffic flow characteristics of traditional fuel vehicles. Based on the sensitivity analysis of the randomization probability, combined with the actual data, the model parameters are quantified to simulate the electric-fuel vehicle mixed traffic flow. Through numerical simulation, the results show that compared with NS (Nagel–Schreckenberg) model and VE(Velocity Effect) model, the improved model can reproduce rich traffic phenomena and is closer to the measured data. With the increase of electric vehicle permeability, the flow rate and speed are increased, the congestion near the critical density is reduced and the traffic safety is improved. At high density, the congestion shows a trend of decreasing first, then increasing and then decreasing again, and the safety is lower than that of homogeneous traffic flow. The speed fluctuation of fuel vehicles is enlarged, and the speed of the overall traffic flow shows an upward trend. In addition, it is found that the TIT curve can identify the state change of traffic flow, and electric vehicles in high-density mixed flow cause greater disturbance to the speed of traffic flow and reduces traffic safety. The results of this paper can provide a basis for further research of electric-fuel vehicle hybrid traffic flow.