Driver's attention effect in car-following model with passing under V2V environment

As vehicles become more autonomous, there is a greater need for reliable and accurate information about neighbouring vehicles. In the V2V environment, information about nearby vehicles plays a significant role in predicting traffic flow behavior and this information becomes more effective during passing. To better understand how a driver's attention can impact the average velocity of their vehicle and those around them, an improved car-following model has been developed with a passing effect. The stability condition of the model is obtained via linear stability analysis, moreover, nonlinear analysis is used to determine the mKdV equation, which describes the evolution properties of the traffic density wave in the jammed region. The numerical and analytical results are discussed for smaller as well as larger rates of passing. It is found that for a smaller rate of passing, the phase transition occurs between the kink jam and the free flow. In the kink jam region, the initial perturbations are evolved in the form of a kink-antikink wave which moves in a backward direction and the amplitude of the headway profile decreases with an increase in the value of the driver's attention coefficient. While for the higher rate of passing, the phase change is between the uniform to the kink jam zone through the chaotic jam zone. In the chaotic region, the behavior of the headway waves is chaotic which band with one another, break up and propagate in the backward direction. Moreover, it has been observed that with the driver's increased attention on the average speed of any nearby vehicles, the unstable region is reduced for any rate of passing. Also, numerical findings are in accordance with theoretical results and noticed that this model is successful in increasing the efficiency of vehicle movement, reducing congestion, and improving safety on roads. To reduce collision accidents, the improved model can be implemented as active safety technology.