TY - GEN
T1 - Achieving Driving Comfort of AVs by Combined Longitudinal and Lateral Motion Control
AU - Wei, Chongfeng
AU - Romano, Richard
AU - Merat, Natasha
AU - Hajiseyedjavadi, Foroogh
AU - Solernou, Albert
AU - Paschalidis, Evangelos
AU - Boer, Erwin R.
PY - 2020
Y1 - 2020
N2 - As automated vehicles (AVs) are moving closer to practical reality, one of the problems that needs to be resolved is how to achieve an acceptable and natural risk management behaviour for the on-board users. Cautious automated driving behaviour is normally demonstrated during the AV testing, by which the safety issue between the AV and other road users or other static risk elements can be guaranteed. However, excessive cautiousness of the AVs may lead to traffic congestion and strange behaviour that will not be accepted by drivers and other road users. Human-like automated driving, as an emerging technique, has been concentrated on mimicking a human driver’s behaviour in order that the behaviour of the AVs can provide an acceptable behaviour for both the drivers (and passengers) and the other road users. The human drivers’ behaviour was obtained through simulator based driving and this study developed a nonlinear model predictive control to optimise risk management behaviour of AVs by taking into account human-driven vehicles’ behaviour, in both longitudinal and lateral directions.
AB - As automated vehicles (AVs) are moving closer to practical reality, one of the problems that needs to be resolved is how to achieve an acceptable and natural risk management behaviour for the on-board users. Cautious automated driving behaviour is normally demonstrated during the AV testing, by which the safety issue between the AV and other road users or other static risk elements can be guaranteed. However, excessive cautiousness of the AVs may lead to traffic congestion and strange behaviour that will not be accepted by drivers and other road users. Human-like automated driving, as an emerging technique, has been concentrated on mimicking a human driver’s behaviour in order that the behaviour of the AVs can provide an acceptable behaviour for both the drivers (and passengers) and the other road users. The human drivers’ behaviour was obtained through simulator based driving and this study developed a nonlinear model predictive control to optimise risk management behaviour of AVs by taking into account human-driven vehicles’ behaviour, in both longitudinal and lateral directions.
KW - Automated vehicle
KW - Vehicle motion control
KW - Human-mimicked control
KW - Human-like control
UR - https://www.scopus.com/pages/publications/85081564234
U2 - 10.1007/978-3-030-38077-9_129
DO - 10.1007/978-3-030-38077-9_129
M3 - Conference contribution
SN - 9783030380762
T3 - Lecture Notes in Mechanical Engineering
SP - 1107
EP - 1113
BT - Advances in Dynamics of Vehicles on Roads and Tracks
A2 - Klomp, Matthijs
A2 - Bruzelius, Fredrik
A2 - Nielsen, Jens
A2 - Hillemyr, Angela
PB - Springer
T2 - The 26th IAVSD Symposium on Dynamics of Vehicles on Roads and Tracks
Y2 - 11 August 2019 through 16 August 2019
ER -