Modeling and Simulation of Traffic Flow Considering Driver Perception Error Effect

Abstract

Driver’s perception error plays a significant role in determining the dynamical properties of a platoon of vehicles driving on a straight road. Therefore, we attempt to understand the role of driver’s perception errors for vehicle motion state information in affecting traffic flow oscillations in this study. A real vehicle test experiment indicates that the drivers have different levels of perception errors for velocity and headway of the preceding vehicle in the car-following process. Based on this, an extended full velocity difference (EFVD) model is used to investigate the effects from the driver’s perception errors of the preceding vehicle’s velocity and headway changes on a road without lane-changing. We incorporated the perception errors of velocity and headway into the EFVD model, and constructed a new EFVD model considering the driver’s perception error (EFVDDPE). Moreover, the confidence levels of perception errors for velocity and headway are introduced. Results from numerical experiments illustrate that the increase of the interval of the confidence levels is not conducive to smooth traffic flow in those cases. In order to eliminate the impact of stochastic fluctuation of the confidence levels on traffic flow stability and car-following safety, a delayed feedback control is proposed. Numerical simulations are also carried out to verify its effectiveness in improving the stability of the stochastic EFVDDPE model. These results are useful in setting an effective control method for adaptive cruise control (ACC) or intelligence driver systems to stabilize traffic flow in the platoon when perception errors exist in the vehicle-mounted sensors.