Affiliation:
1. School of Engineering, RMIT University, Melbourne, Victoria, Australia
Abstract
The assimilation of path planning and motion control is a crucial capability for autonomous vehicles. Pure pursuit controllers are a prevalent class of path tracking algorithms for front wheel steering cars. Nonetheless, their performance is rather limited to relatively low speeds. In this paper, we propose a model predictive active yaw control implementation of pure pursuit path tracking that accommodates the vehicle’s steady state lateral dynamics to improve tracking performance at high speeds. A comparative numerical analysis was under taken between the proposed strategy and the traditional pure pursuit controller scheme. Tests were conducted for three different paths at iteratively increasing speeds from 1 m/s up to 20 m/s. The traditional pure pursuit controller was incapable of maintaining the vehicle stable at speeds upwards of 5m/s. The results show that implementing receding horizon strategy for pure pursuit tracking improves their performance. The contribution is apparent by preserving a relatively constant controller effort and consequently maintaining vehicle stability for speeds up to 100Km/h in different scenarios. A Matlab implementation of the proposed controller and datasets of the experimental paths are provided to supplement this work.
Subject
Mechanical Engineering,Mechanics of Materials,Aerospace Engineering,Automotive Engineering,General Materials Science
Cited by
68 articles.
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