Modeling of Double Lane Change Maneuver of Vehicles

Lane change maneuver is one of most riskiest driving tasks. In order to increase the safety level of the vehicles during this maneuver, design of lane change assist systems which are based on dynamics behavior of driver-vehicle unit is necessary. Therefore, modeling of the maneuver is the first step to design the driver assistance system. In this paper, a novel method for modeling of lateral motion of vehicles in the standard double-lane-change (DLC) maneuver is proposed. A neuro-fuzzy model is suggested consisting of both the vehicle orientation and its lateral position. The inputs of the model are the current orientation, lateral position and steering wheel angle, while the predicted lateral position and orientation of the vehicle are the outputs. The efficiency of the proposed method is verified using both simulation results and experimental tests. The simulation and experimental maneuvers are performed in different velocities. It is shown that the proposed method can effectively reduce the undesirable effects of environmental disturbances and is significantly more accurate in comparisons with the results in the recent available papers. This method can be used to personalize the advanced driver assistance systems.