Hikaru Nishira

An optimal path generator using a receding horizon control scheme for intelligent automobiles

It is expected that more and more information are brought into automobiles through various sensing and communication devices. To make such information useful for effective driving assistance, it must be appropriately transformed into intuitively understandable symbols, because human recognition ability is limited. A real-time algorithm for calculating the desirable longitudinal and lateral maneuvers (optimal path for a driver to track) from surrounding information is developed based on a receding horizon control framework. Simulation results show that the proposed algorithm generates reasonable maneuvers.

Road friction estimation using adaptive observer with periodical /spl sigma/-modification

We propose an adaptive observer for estimation of a road friction coefficient, which is important for vehicle control. The observer needs the driving torque and wheel speeds of the driven and non-driven wheels as inputs. The road friction coefficient is assumed to be represented by a product of a known function and an unknown parameter to be estimated by an adaptive law. It is shown that non-robust adaptive law can obtain the true value, if there are no disturbances. However, it diverges when disturbances are added. Periodical /spl sigma/-modification is proposed here as a robust adaptive law. The estimation robustness against disturbances can be improved with the law. Numerical simulation results are presented to show the effectiveness of the adaptive law.

Automotive longitudinal speed pattern generation with acceleration constraints aiming at mild merging using model predictive control method

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.

On Vehicle Path Generation Method for Collision Avoidance using Mixed Integer Programming

This paper considers an optimal path generation problem that generates a path without a collision between an automobile and obstacles.The problem is formulated as mixed integer programming. In the problem the obstacles and environments around the automobile can be represent as inequality conditions. The dynamics of the obstacle is described as variation of a prohibited region. According to model predictive control we solve the optimal path generation problem a each time step then apply the first element of the optimal input. The method proposed in this paper can deal an explicit representation of the dynamics of the obstacle and provides no collision between the automobile and the obstacle.

Mild merging path generation method with optimal merging point based on MPC

Abstract 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.

Merging trajectory generation for vehicle on a motor way using receding horizon control framework consideration of its applications

This paper describes a selection of a merging point and a trajectory generation method for a merging maneuver of vehicles on a motor way which is possible to be used in a centralized merging control system as well as in a stand-alone merging control system. The merging problem is formulated into an optimization problem using receding horizon control framework. An appropriate path to merge is designed for the merging vehicle, which is modified according to the motion of the main lane vehicles. Appropriate constraints are set for the vehicles so that the vehicle can move smoothly in the specified range. The possibility of the method to be used in a centralized motion control system for vehicles during merging and a standalone motion control system for the merging vehicle is examined by computer simulation.