Coordinated Path-Following Control for Multiple Autonomous Vehicles With Communication Time Delays

2020 ◽  
Vol 28 (5) ◽  
pp. 2005-2012 ◽  
Author(s):  
Dong-Liang Chen ◽  
Guo-Ping Liu
Author(s):  
Yixiao Liang ◽  
Yinong Li ◽  
Ling Zheng ◽  
Yinghong Yu ◽  
Yue Ren

The path-following problem for four-wheel independent driving and four-wheel independent steering electric autonomous vehicles is investigated in this paper. Owing to the over-actuated characters of four-wheel independent driving and four-wheel independent steering autonomous vehicles, a novel yaw rate tracking-based path-following controller is proposed. First, according to the kinematic relationships between vehicle and the reference path, the yaw rate generator is designed by linear matrix inequality theory, with the ability to minimize the disturbances caused by vehicle side slip and varying curvature of path. Considering that the path-following objective and dynamics stability are in conflict with each other in some extreme path-following conditions, a coordinating mechanism based on yaw rate prediction is proposed to satisfy the two conflicting objectives. Then, according to the desired yaw rate and longitudinal velocity, a hierarchical structure is introduced for motion control. The upper-level controller calculates the generalized tracking forces while the allocation layer optimally distributes the generalized forces to tires considering tire vertical load and adhesive utilization. Finally, simulation results indicate that the proposed method can achieve excellent path-following performances in different driving conditions, while both path-following objective and dynamics stability can be satisfied.


Author(s):  
Javad Ahmadi ◽  
Efstathios Velenis ◽  
Heimoud El Vagha ◽  
Chenhui Lin ◽  
Boyuan Li ◽  
...  

Author(s):  
Jinghua Guo ◽  
Jin Wang ◽  
Ping Hu ◽  
Linhui Li

This paper deals with the problem of automatic path-following control for a class of autonomous vehicle systems with parametric uncertainties and external disturbances in cross-country conditions. In the unstructured environments, the unevenness, the discontinuity and the variability of the terrain greatly increase the parametric uncertainties and the external perturbations of autonomous vehicles. To overcome these difficulties, a novel automatic path-following control scheme of vision-based autonomous vehicles is presented by utilizing the guaranteed-cost control theory. First, a new road detection algorithm used for segmenting and extracting the traversable path in unstructured terrains is achieved by using a combination consisting of multiple sensors, and the local relative position information between the vehicles and the desired trajectories can be acquired by the proposed detected algorithm in real time. Then, an optimal guaranteed-cost path-following control system is proposed, which can deal with the parametric uncertainties of autonomous vehicles and ensure the stability of the closed-loop control system. Finally, both simulation tests and experimental results demonstrate that the proposed control scheme can guarantee high path-tracking accuracy irrespective of the parametric uncertainties.


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