.png){kind=icon}
.png){kind=icon}
Return
A Predictive Controller for Autonomous Vehicle Path Tracking
.png){kind=icon}
PRE
AI
DOI：10.1109/TITS.2008.2011697.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper presents a model predictive controller (MPC) structure for solving the path-tracking problem of terrestrial autonomous vehicles. To achieve the desired performance during high-speed driving, the controller architecture considers both the kinematic and the dynamic control in a cascade structure. Our study contains a comparative study between two kinematic linear predictive control strategies: The first strategy is based on the successive linearization concept, and the other strategy combines a local reference frame with an approaching path strategy. Our goal is to search for the strategy that best comprises the performance and hardware-cost criteria. For the dynamic controller, a decentralized predictive controller based on a linearized model of the vehicle is used. Practical experiments obtained using an autonomous Mini-Baja vehicle equipped with an embedded computing system are presented. These results confirm that the proposed MPC structure is the solution that better matches the target criteria.
Keywords:
Autonomous vehicle
path following
predictive control
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.4
Papers:
9.5K
Citations:
6.3W