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 driverâs 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 driversâ 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 vehiclesâ behaviour, in both longitudinal and lateral directions.
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