A car following model considering driver memory effect in intelligent transportation environment

This paper builds a car following model in an intelligent transportation environment in order to thoroughly consider the driver's own characteristics and the impact of the environment on the stability of the traffic flow, taking into account the driver's memory effect and multi-vehicle information. According to the model's stability analysis and numerical simulation findings, the stability zone will grow as the driver memory effect lessens and more vehicle data is taken into account, while the amplitude of traffic flow density will steadily decrease. This implies that traffic congestion can be reduced while the consistency of traffic flow would be enhanced.