Volvo Truck Corporation

Volvo Autonomous Solutions Ab

Emil Klintberg

Linus Hagvall

Fredrik Sandblom

Oskar Wigström

Leo Laine

Wilhelm Wiberg

Peter Nilsson

Robert Hult

Dandan Ge

Oskar WIGSTRÖM

The present disclosure relates to a control system for selectively controlling a vehicle, ensuring high integrity of decisions taken by the control system when controlling the vehicle. The present disclosure also relates to a corresponding computer implemented method and to a computer program product.

Control system for a vehicle

There is provided mechanisms for compensating for backlash in a steering house of a steering system in a vehicle. A method is performed by a controller of the steering system. The method comprises obtaining a hysteresis model of the backlash in the steering house. The hysteresis model has an inverse. The method comprises obtaining a control signal to be input to an electric motor of the steering system. The control signal defines a desired set point for the steering system. The method comprises determining an adjusted set point for the steering system based on the inverse of the hysteresis model, the desired set point, and a current operating point in the hysteresis model. The adjusted set point defines an adjusted control signal. The method comprises compensating for the backlash in the steering house by providing the adjusted control signal, instead of the control signal, as input to the electric motor.

Handling of backlash in a steering house of a vehicle steering system

A method for validating a model of vehicle dynamics for use in autonomous driving. The method comprising setting a wheel slip limit on an operation of at least one vehicle torque device, obtaining a model of vehicle dynamics based on the set wheel slip limit, and validating the model of vehicle dynamics based on the set wheel slip limit.

Method for validating a model associated with vehicle dynamics

A method for quantifying road user behavior, the method comprising; obtaining samples of road user behavior selecting a subset of the road user behavior samples such that the selected samples follow a pre-determined statistical extreme value distribution, parameterizing the pre-determined statistical extreme value distribution based on the selected samples of road user behavior, and quantifying road user behavior based on the parameterized statistical extreme value distribution.

Method for quantifying extreme traffic behavior

A method for determining if a vehicle control command for controlling a vehicle () associated with a current vehicle state precludes a future situation avoidance maneuver (SAM) by the vehicle. The method comprises obtaining one or more safe sets, wherein each safe set represents a range of vehicle states from which a future SAM can be initialized with prospect for success. The method also comprises obtaining the current vehicle state and the control command and predicting a future vehicle state based on the current vehicle state and on the control command. The method comprises comparing the predicted future vehicle state to the one or more safe sets and determining that the control command precludes the future SAM if the predicted future vehicle state is not comprised in any of the one or more safe sets.

Method for determining if a vehicle control command precludes a future vehicle safety maneuver

A method for quantifying correctness of a vehicle model f(⋅). The method comprises obtaining prediction errors (A) by evaluating the model f(⋅) over a range of input parameters, determining a threshold ζ such that the prediction errors in excess of the threshold ζ, {ε: ε≤ζ}, follow a Generalized Pareto Distribution, GDP, and parameterizing a GDP based on the prediction errors in excess of the threshold ζ {ε: ε≤}. The method then quantifies correctness of the vehicle model f(⋅) based on the parameterized GDP.

Method for quantifying correctness of a vehicle model

A method for quantifying vehicle path following performance, the method comprising; obtaining samples of path following performance (I), selecting a subset of the path following performance samples such that the selected samples follow a pre-determined statistical extreme value distribution, parameterizing the pre-determined statistical extreme value distribution based on the selected samples of path following performance, and quantifying vehicle path following performance based on the parameterized statistical extreme value distribution.

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Torslanda, Sweden

Emil Klintberg