Abstract: 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.

Abstract: Confined areas present an opportunity for early deployment of autonomous vehicles due to the absence of non-controlled traffic participants. In this disclosure, two approaches for coordination of multiple AVs in confined sites. Each approach computes speed-profiles for the AVs such that collisions are avoided in cross intersections, merge-split zones and narrow road sections. Specifically, this is done by solving an optimal control problem where the motion of all vehicles is optimized jointly. The order in which the vehicles pass the crossings is determined through the solution of a Mixed Integer Quadratic Program. Through simulation results, the capability of the algorithm is demonstrated in terms of performance and observance of collision avoidance constraints.

Abstract: 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.

Abstract: A method for determining if a vehicle control command for controlling a vehicle (1) 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.

Abstract: 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.

Abstract: 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 ? such that the prediction errors in excess of the threshold ?, {?i:?i??}, follow a Generalized Pareto Distribution, GDP, and parameterizing a GDP based on the prediction errors in excess of the threshold ?{?i:?i?}. The method then quantifies correctness of the vehicle model f(·) based on the parameterized GDP.

Abstract: The present disclosure relates to a computer implemented method for operating an autonomous vehicle based on sensor data representative of an area in a driving direction of and in the vicinity of the vehicle. The vehicle is equipped with a control unit adapted to determine if a plurality of detailed actions to be performed by the vehicle successfully may be used for fulfilling a desired general action plan for the vehicle. The present disclosure also relates to a corresponding control system and to a computer program product.