曹 文静

This paper has proposed a gap selection and path generation method during merging maneuver of automobile. In this method the merging problem of one merging vehicle and multiple main lane vehicles is formulated using a model predictive control method. Lanes of a motor way are approximated with proposed smooth lines. Assuming that the main lane vehicles run on the centerline of the main lane, an appropriate path of the merging vehicle can be simply designed and modified according to the motions of the main lane vehicles. To generate mild merging, accelerations of all the relevant vehicles are constrained. Effectiveness of the proposed method is validated by computer simulations of the merging maneuvers of one merging vehicle and two main lane vehicles in different conditions. An example of actual cooperative merging maneuver is generated by the proposed method. Further the collision avoidance ability and the initial condition dependent property of the proposed method are tested.

To ensure safety and simplicity in merging path generation for a realistic reliable and mild merging, this paper proposes a merging path generation method. In the proposed method, the merging problem is considered in two-dimensional space and formulated into a one-dimensional space optimization problem by relating the longitudinal motion of the merging vehicle to the lateral motion of it. In this way the optimization problem would be much simpler and therefore the computational time could be shorter than formulating it into a two-dimensional problem. Moreover, the parameters are chosen appropriately so that the variation of the acceleration of the main lane vehicle is less severe than that of the merging vehicle, which is consistent with the practice. To realize mild merging, the merging path is optimized while the accelerations of the relevant vehicles are optimized through the model predictive control (MPC) method. With the proposed method, the merging vehicle can merge smoothly and realistically in cooperative with the main lane vehicle. The effectiveness of this method is verified by a computer simulation of the motions of one merging vehicle and one main lane vehicle. The initial conditions of the merging are set realistically according to the data drawn from actual merging scenes. The results proved that, with the proposed method the merging vehicle can merge mildly in cooperation with the main lane vehicle. © 2013 IEEE.

In this paper, a merging path generation method based on model predictive control (MPC) method is proposed to optimize the merging point, and the merging path of the merging vehicle, while the motion of the main lane vehicle is optimized at the same time. To simplify the optimization problem which is used to generate the merging trajectory, the longitudinal movement of the merging vehicle is related to the lateral movement of it. To reproduce and make full use of the cooperative driving behavior in merging, the motions of the two relevant vehicles are optimized at the same time. A variable which enables the translation of the merging trajectory of the merging vehicle is introduced into the state of the system. So that when it is necessary to translate the merging trajectory of the merging vehicle for some reason, for example, keeping safe distance, the merging trajectory would be translated and thus the merging point can be optimized. In consideration of the upper bounds of the accelerations and lower bounds of the decelerations that actual vehicles can produce, during merging the accelerations and decelerations of both the relevant vehicles are restricted to appropriate ranges. A computer simulation of three typical merging cases, whose initial conditions are set according to the data drawn from actual merging scene, was conducted on a personal computer to verify the effectiveness of the proposed method. It is shown that the computer simulation results for all the three cases are reasonable. The computational time for all of the three cases is much shorter compare to the time step therefore the proposed method is quite probable to be implemented on actual vehicles.

A merging path generation method for automated vehicle merging is proposed. This method can make the relevant vehicles cooperate with each other with constraint accelerations, keep the vehicles in their lanes and generate collision free merging path. The merging problem is considered in the two-dimensional space. We set up the mathematic model of the system, formulate the two-dimensional merging problem as an optimization problem and solve it by model predictive control (MPC). To compare the simulation results with the practice, three typical cases were researched. In order to be more practical, the initial conditions of the cases were set according to the data obtained through analyzing the helicopter-shot video. The results represent that the MPC-controlled merging maneuver carried out safely and smoothly, and the relative positions after merging is also the same with the practical results in all the three representative conditions considered. The absolute values of the accelerations of the vehicles are all kept below a practical value 3 m/s2. The importance of cooperation in merging maneuver can also be noticed in the simulation results. By letting the relevant vehicles cooperate, this control algorithm would generate collision free merging path even in the very severe condition. The computational time for the three cases is also short enough for the method to be implemented in actual situation. © 2012 ISAROB.

In this research, the merging problem is considered in the two-dimensional space instead of the one-dimensional space. In this paper, we set up the mathematic model of the system, formulate the two-dimensional merging problem as an optimization problem and solve it by model predictive control (MPC). To compare the simulation results with the practical situation, three typical cases were researched. In order to be more practical, the initial conditions of the cases were set according to the data obtained through analyzing the helicopter-shot video. The results represent that the MPC-controlled merging maneuver carried out safely and smoothly, and the relative positions after merging is also the same with the practical results in all the three representative conditions considered in this research. The absolute values of the accelerations of the vehicles are all below 3m/s(2), which are quite practical as well. The simulation results also represented the importance of the adjustment in driving during merging. By adjusting these vehicles, this control algorithm would generate the merging path that could avoid merging accident even in the very severe condition.