Volvo Truck Corporation

Volvo Autonomous Solutions Ab

Linus Hagvall

Emil Klintberg

Stefan Bergquist

Fredrik Sandblom

Oskar Wigström

Christian Grante

Wilhelm Wiberg

Peter Nilsson

Oskar WIGSTRÖM

A method performed by a control unit for operating an autonomous vehicle is provided. The control unit is arranged to communicate via at least one antenna. The control unit obtains, based on a signal from the at least one antenna, information relating to at least one geographical zone associated with a transponder as the autonomous vehicle moves in proximity of the transponder. Also, the control unit determines an autonomous operating mode of the autonomous vehicle based on the obtained information relating to the at least one geographical zone associated with the transponder. The control unit further operates the autonomous vehicle in accordance with the determined autonomous operating mode.

Control unit and method therein for operating an autonomous vehicle

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

A method of verifying a position of a vehicle using a vehicle-mounted device, the method including generating first position data for the vehicle-mounted device responsive to receiving data from a transponder-based localization system, generating second position data for the vehicle-mounted device responsive to receiving data from another localization system; and reporting verified vehicle position data for the vehicle, based on a comparison of the data from the other localization system with the data from the transponder-based localization system for the vehicle-mounted device.

Vehicle localization system

A method for assessing reliability of a brake assembly of a vehicle. The brake assembly comprises brake system, nominal automation system and safety system. The brake system is adapted to receive a brake request individually from each one of the nominal automation system and the safety system and in response, initiate a braking operation. The method comprises determining an actual braking operation density, the actual braking operation density determined on the basis of at least a subset of occurrences per unit time when a braking operation is initiated by the brake system; in response to detecting that the actual braking operation density is lower than a braking operation reference density, issuing a brake request from the safety system; detecting a response of the brake system to the signal issued from the safety system, and on the basis of at least the detected response, assessing the reliability of the brake assembly.

Method for assessing reliability of a brake assembly of a vehicle

A method performed by a central unit for evaluating a performance of an obstacle detection system comprised in a first object within a set of two or more objects at a confined area. The first object is a vehicle. The central unit obtains pose data from each object in the set and obstacle detection data from at least the first object. The central unit determines a relative pose of the objects using the pose data from each object. The central unit the obstacle detection data from each object in the set to the determined relative pose of the objects. Based on the comparison, the central unit evaluates the performance of the obstacle detection system of the first object.

Method and unit for evaluating a performance of an obstacle detection system

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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Gothenburg, Sweden

Linus Hagvall