Lane changing trajectory planning and tracking control for intelligent vehicle on curved road

نویسندگان

  • Lukun Wang
  • Xiaoying Zhao
  • Hao Su
  • Gongyou Tang
چکیده

This paper explores lane changing trajectory planning and tracking control for intelligent vehicle on curved road. A novel arcs trajectory is planned for the desired lane changing trajectory. A kinematic controller and a dynamics controller are designed to implement the trajectory tracking control. Firstly, the kinematic model and dynamics model of intelligent vehicle with non-holonomic constraint are established. Secondly, two constraints of lane changing on curved road in practice (LCCP) are proposed. Thirdly, two arcs with same curvature are constructed for the desired lane changing trajectory. According to the geometrical characteristics of arcs trajectory, equations of desired state can be calculated. Finally, the backstepping method is employed to design a kinematic trajectory tracking controller. Then the sliding-mode dynamics controller is designed to ensure that the motion of the intelligent vehicle can follow the desired velocity generated by kinematic controller. The stability of control system is proved by Lyapunov theory. Computer simulation demonstrates that the desired arcs trajectory and state curves with B-spline optimization can meet the requirements of LCCP constraints and the proposed control schemes can make tracking errors to converge uniformly.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Motion Trajectory Planning Method of Lane Change for Intelligent Vehicle

The motion planning method of lane change for intelligent vehicle is an important component in the autonomous vehicle field. In order to make the intelligent vehicle drive on the urban environmental road smoothly when there is a barrier in the front, a new curvature-continuous obstacle avoidance trajectory planning method was introduced. The trajectory planning method based B-spline curves and ...

متن کامل

Adaptive fuzzy sliding mode and indirect radial-basis-function neural network controller for trajectory tracking control of a car-like robot

The ever-growing use of various vehicles for transportation, on the one hand, and the statistics ofsoaring road accidents resulting from human error, on the other hand, reminds us of the necessity toconduct more extensive research on the design, manufacturing and control of driver-less intelligentvehicles. For the automatic control of an autonomous vehicle, we need its dynamic...

متن کامل

Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks

During recent years there has been growing interest in unmanned aerial vehicles (UAVs). Moreover, the necessity to control and navigate these vehicles has attracted much attention from researchers in this field. This is mostly due to the fact that the interactions between turbulent airflows apply complex aerodynamic forces to the system. Since the dynamics of a quadrotor are non-linear and the ...

متن کامل

Multi-Agent Based Microscopic Simulation Modeling for Urban Traffic Flow

Traffic simulation plays an important role in the evaluation of traffic decisions. The movement of vehicles essentially is the operating process of drivers, in order to reproduce the urban traffic flow from the micro-aspect on computer, this paper establishes an urban traffic flow microscopic simulation system (UTFSim) based on multi-agent. The system is seen as an intelligent virtual environme...

متن کامل

Preceding Vehicle Trajectory Prediction by Multi-Cue Integration

In this paper we describe an approach to detect and predict the driving trajectory of a preceding vehicle on highway. In particular, we focus on detecting and predicting the changing lane intention and action of the preceding vehicle. Our algorithm employs SVM for driving pattern recognition by integrating two different cues: motion cue and appearance cue, which is trained on two class feature ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 5  شماره 

صفحات  -

تاریخ انتشار 2016