Open AccessIterative learning of an unknown road path through cooperative driving of vehicles
Author(s) -
Yang Lin,
Li Yanan,
Huang Deqing,
Xia Jingkang
Publication year - 2020
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2019.0411
Subject(s) - iterative learning control , controller (irrigation) , path (computing) , computer science , control theory (sociology) , task (project management) , track (disk drive) , advanced driver assistance systems , vehicle dynamics , control (management) , control engineering , engineering , simulation , artificial intelligence , automotive engineering , systems engineering , agronomy , biology , programming language , operating system
This study proposes a method for a vehicle controller to learn human driving behaviours through iterative interactions. In particular, the vehicle controller and the human driver jointly control a vehicle along a path only known to the human driver. Through repeated cooperative driving, the vehicle controller estimates the hidden desired path of the driver by minimising the control input. Eventually, semi‐autonomous driving is realised since the vehicle controller is able to automatically track the target path and release the human driver from the driving task. The iterative learning of the human target path on the basis of the proposed algorithm is in the spatial domain, and is effective in the presence of uncertain human driving speeds. The validity of the proposed method is proved by rigorous analysis and demonstrated by numerical simulations.