Abstract
We developed a new car-following model to investigate the effects of driver anticipation and driver memory on traffic flow. The changes of headway, relative velocity, and driver memory to the vehicle in front are introduced as factors of driver’s anticipation behavior. Linear and nonlinear stability analyses are both applied to study the linear and nonlinear stability conditions of the new model. Through nonlinear analysis a modified Korteweg-de Vries (mKdV) equation was constructed to describe traffic flow near the traffic near the critical point. Numerical simulation shows that the stability of traffic flow can be effectively enhanced by the effect of driver anticipation and memory. The starting and breaking process of vehicles passing through the signalized intersection considering anticipation and driver memory are presented. All results demonstrate that the AMD model exhibit a greater stability as compared to existing car-following models.
Highlights
How, two successive vehicles interact with each other on a road, has been studied since the 1950s
Milestone carfollowing models include the rst version of linear models [1], the rst version of nonlinear models [2,3,4], the carfollowing model based on space headway [5], intelligent driver models (IDM) and its extensions considering both the optimal velocity and space headway [6,7,8,9,10], and some other models [11,12,13,14,15,16,17,18,19,20,21,22,23,24]
It means that the driver starts up earlier when the tra c light changes to green without having a higher acceleration due to considering space headway at moment and previous vehicle motion. at is, vehicles behaving according to the AMD model accelerate more quickly than the anticipation driving (AD) model, but do not generate an unrealistic high acceleration observed in the Optimal Velocity (OV) model
Summary
Two successive vehicles interact with each other on a road, has been studied since the 1950s. Several other extensions of the OV model have been suggested to depict more characteristics of tra c ow by considering the relative velocity between the leading and following vehicles [27,28,29,30]. Yu and Shi [41] derived an improved car-following model to study the e ects of multiple velocity di erence changes with short-term driver memory on the stability and fuel economy of tra c ow based on FVD model as an e ective factor on driver’s anticipation behavior. In this study we propose a new model, namely, the driver’s anticipation and memory driving (AMD) car-following model to consider the e ect of both driver memory and driver anticipation.
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