Optimal-Control-Based Adas for Driver Warning and Autonomous Intervention Using Manoeuvre Jerks for Risk Assessment

In this research work, two ADAS have been proposed, both based on optimal control and manoeuvre jerks as parameters for threat assessment. The first is named “Codriver”, and is a system for driver warning. The second is a sort of completion of the first, since it is designed for autonomous vehicle intervention if the driver does not react to the warnings. The Codriver has been developed by the Mechatronics Group of the University of Trento, which the author is part of, in the framework of the European Project “interactIVe”, to warn the driver for all-around threats safety. It has been then implemented on a real vehicle of Centro Ricerche Fiat, which has been widely tested at the end of the project. On the other hand, for the second system only the main components have been developed by the author during a research period at the University of Tokyo, Japan, and its application is restricted to autonomous obstacle avoidance. In particular, a motion planning algorithm has been used together with a control loop de- signed to execute the planned trajectories. Both systems exploit Optimal Control (OC) for motion planning: the Codriver uses OC to plan real-time ma- noeuvres with humanlike criteria, so that they can be compared to what the driver is doing in order to infer his/her intentions, and warn him if these are not safe; the second system uses OC instead to plan emergency manoeuvres, i.e. neglecting driver actuation limitations and pushing the vehicle towards its physical limits. The initial longitudinal and lateral jerks of the planned manoeuvres are used by both the systems as parameters for risk assessment. Manoeuvre jerks are proportional to pedal and steering wheel velocities, and their initial values thus describe the entity of the correction needed by the driver to achieve a given goal. Since human drivers plan and act with minimum jerk criteria, and are jerk-limited, more and more severe manoeuvres at a given point are not reachable anymore by a human driver, since they require too high initial jerks: initial jerks can be thus considered proportional to the risk level of current situation. For this reason, when the manoeuvres to handle current scenario require jerks beyond a given threshold, the Codriver outputs a warning. This threshold must be lower than driver limits, so that he/she will be able to react to the warning and still have the chance to perform a safe manoeuvre. When the required jerks exceed drivers’ actuation limits, the risk level raises to an upper step, where driver warning would be not effective and autonomous vehicle intervention should be enabled. In obstacle avoidance scenarios, it was demonstrated during driving simulator tests that manoeuvre jerks are more robust parameters for risk assessment than for example time headways, since they are less affected by driver’s age and gender