Abstract: A method performed by an Automated Driving Systems (ADS) development system for supporting proving fulfilment of safety requirements imposed on ADSs. The ADS development system derives a corresponding set of parameter-specific ADS safe driving policies, each safe driving policy exhibiting a respective uncertainty. The ADS development system identifies at least a first parameter-specific ADS safe driving policy inflicted with an uncertainty fulfilling predeterminable criteria, which criteria filters out uncertainties indicating, respectively, that the corresponding operational parameter needs to be further observed in order to relax the ADS's currently allowed safety requirements-fulfilled ADS safe driving policy. The ADS development system identifies at least a first geographical location exhibiting conditions allowing the operational parameter(s) in need of further observance, to be observed.

Abstract: A method of controlling an autonomous vehicle, AV, which is navigable in an environment with at least one prohibited area and at least one calibration station. The AV comprises a state estimation system configured to output an estimated state including an estimated position of the AV, wherein the estimated state has a guaranteed accuracy while the AV is visiting the calibration station. According to an embodiment, the method comprises an assessment, on the basis of the AV's estimated state and the time elapsed since the AV's latest visit at one of the calibration stations, whether the AV is staying outside the prohibited area with a predetermined confidence level ?. If the assessment produces a negative result, a safety-oriented action is taken. The assessment may include an evaluation whether the AV is staying outside the prohibited area by a margin which includes a position uncertainty.

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 computer-implemented method controls a vehicle to have predictable behaviour after an unexpected event occurs even if the event causes there to be no safe trajectories at that particular instant. The method comprises an automated driver system, ADS, of the vehicle determines there are no safe trajectories responsive to the occurrence of the unexpected event, and also responsive to the occurrence of the unexpected event, dynamically re-evaluates whether a current trajectory being followed by the vehicle meets a current set of safety criteria. A decision to follow the current re-evaluated trajectory path is then made possible removing one or more consequences of the occurrence of the event from the safety criteria used to re-evaluate the current trajectory whilst maintaining all other previous safety criteria. This allows the vehicles ADS to maintain the path of the current trajectory whilst possibly changing the behaviour of the vehicle along that path to slow it down.

Abstract: A method for controlling a vehicle based on a quantified objection detection performance. The method includes obtaining samples of objection detection performance pii=1n-1, wherein the objection detection performance comprises a comparison of an estimated object state with a reference object state, selecting a subset of the objection detection 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 objection detection performance, quantifying objection detection performance based on the parameterized statistical extreme value distribution, and controlling the vehicle based on the quantified objection detection performance.

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 invention relates to a method for a lane change of a plurality of vehicles (1-3) on a multi-lane road, the method comprising —controlling the vehicles to travel in a row in a first lane (L1), with a first of the vehicles (1) in front of a second of the vehicles (2), —thereafter controlling the first vehicle (1) so as to change lane to a second lane (L2) adjacent to the first lane (L1), —thereafter positioning the first vehicle (1) in a first position (P1) in the second lane (L2), and positioning the second vehicle (2) in a second position (P2) in the first lane (L1), the first position (P1) being less advanced in the direction of travel (M) than the second position (P2), and —thereafter controlling the second vehicle (2) so as to change lane to the second lane (L2), and thereby move in front of the first vehicle (1).

Abstract: A control system is provided for a vehicle including an autonomous emergency braking system, characterized in that the control system includes: a brake control arrangement adapted to apply a friction-estimating braking when the autonomous emergency braking system has initiated a possible intervention; a brake force capacity estimation arrangement adapted to estimate the brake force capacity of the vehicle as a function of longitudinal wheel slip based on the applied friction-estimating braking; a road information arrangement adapted to obtain information about road curvature ahead of the vehicle; a lateral tyre force prediction arrangement adapted to predict lateral tyre force needed during autonomous emergency braking based on the obtained information about road curvature; and a brake strategy adaptation arrangement configured to adapt the brake strategy of the autonomous emergency braking system based on the estimated brake force capacity and the predicted lateral tyre force needed.

Abstract: A method is provided for vehicle identification, which method includes the steps of: an ego vehicle detecting a communicating vehicle by wireless vehicle to vehicle communication; the ego vehicle detecting a nearby vehicle by a sensor onboard the ego vehicle; the ego vehicle sending an identification request to the communicating vehicle by wireless vehicle to vehicle communication, wherein the identification request instructs the communicating vehicle to perform an action; the ego vehicle determining whether or not the nearby vehicle performed the action based at least on data from the sensor; and if the ego vehicle determines that the nearby vehicle performed the action, the ego vehicle determining that the communicating vehicle and the nearby vehicle are the same vehicle.

Abstract: A device for reversing an articulated vehicle combination that has at least two vehicle units interconnected via at least one articulated join includes an arrangement for recording and storing a plurality of global positions of a local position of the vehicle combination, at least one sensor, mounted on the vehicle combination, for recording data representing a plurality properties of the surroundings, and a control unit arranged to determine, based at least partly on a plurality of dimensions of the vehicle combination, a set of global positions recorded when the vehicle combination is moving forward, and a set of data representing properties of the surroundings recorded during the forward movement, vehicle control input data for control of the vehicle combination during a reverse movement of the vehicle combination.

Abstract: A control system is provided for an articulated vehicle including a towing vehicle, a trailer and an autonomous emergency braking system, wherein the control system includes: a brake control arrangement adapted to apply a friction-estimating braking; a brake force capacity estimation arrangement adapted to estimate the brake force capacity of the vehicle as a function of longitudinal wheel slip based on the applied friction-estimating braking; an axle load estimation arrangement adapted to estimate the normal force on each wheel axle of the vehicle; a friction estimation arrangement adapted to estimate a friction coefficient based on the estimated brake force capacity and at least one of the estimated normal forces; and a brake strategy adaptation arrangement configured to adapt the brake strategy of the autonomous emergency braking system by adjusting the brake force for at least one wheel axle of the Vehicle based on the estimated friction coefficient and the at least one wheel axle's estimated normal force

Abstract: A device for reversing an articulated vehicle combination that has at least two vehicle units interconnected via at least one articulated join includes an arrangement for recording and storing a plurality of global positions of a local position of the vehicle combination, at least one sensor, mounted on the vehicle combination, for recording data representing a plurality properties of the surroundings, and a control unit arranged to determine, based at least partly on a plurality of dimensions of the vehicle combination, a set of global positions recorded when the vehicle combination is moving forward, and a set of data representing properties of the surroundings recorded during the forward movement, vehicle control input data for control of the vehicle combination during a reverse movement of the vehicle combination.

Abstract: An arrangement for determining a vehicle speed behaviour model for a leading vehicle, where the leading vehicle drives along a path in front of a trailing host vehicle and where the determination is done by a control unit in the host vehicle, where the host vehicle includes an arrangement for measuring the time gap to the leading vehicle, an arrangement for measuring the speed of the host vehicle, an arrangement for obtaining external information regarding an upcoming change in a road condition, where the control unit is adapted for monitoring the change in vehicle speed of the leading vehicle, and for determining a vehicle speed behaviour model for the leading vehicle based on the monitored change in vehicle speed of the leading vehicle. The vehicle speed behaviour of a leading vehicle can be used by the host vehicle to optimize the fuel consumption, the comfort and the safety of the host vehicle.

Abstract: A method is provided for vehicle identification, which method includes the steps of: an ego vehicle detecting a communicating vehicle by wireless vehicle to vehicle communication; the ego vehicle detecting a nearby vehicle by a sensor onboard the ego vehicle; the ego vehicle sending an identification request to the communicating vehicle by wireless vehicle to vehicle communication, wherein the identification request instructs the communicating vehicle to perform an action; the ego vehicle determining whether or not the nearby vehicle performed the action based at least on data from the sensor; and if the ego vehicle determines that the nearby vehicle performed the action, the ego vehicle determining that the communicating vehicle and the nearby vehicle are the same vehicle.

Abstract: A control system is provided for a vehicle including an autonomous emergency braking system, characterized in that the control system includes: a brake control arrangement adapted to apply a friction-estimating braking when the autonomous emergency braking system has initiated a possible intervention; a brake force capacity estimation arrangement adapted to estimate the brake force capacity of the vehicle as a function of longitudinal wheel slip based on the applied friction-estimating braking; a road information arrangement adapted to obtain information about road curvature ahead of the vehicle; a lateral tyre force prediction arrangement adapted to predict lateral tyre force needed during autonomous emergency braking based on the obtained information about road curvature; and a brake strategy adaptation arrangement configured to adapt the brake strategy of the autonomous emergency braking system based on the estimated brake force capacity and the predicted lateral tyre force needed.

Abstract: A control system is provided for an articulated vehicle including a towing vehicle, a trailer and an autonomous emergency braking system, wherein the control system includes: a brake control arrangement adapted to apply a friction-estimating braking; a brake force capacity estimation arrangement adapted to estimate the brake force capacity of the vehicle as a function of longitudinal wheel slip based on the applied friction-estimating braking; an axle load estimation arrangement adapted to estimate the normal force on each wheel axle of the vehicle; a friction estimation arrangement adapted to estimate a friction coefficient based on the estimated brake force capacity and at least one of the estimated normal forces; and a brake strategy adaptation arrangement configured to adapt the brake strategy of the autonomous emergency braking system by adjusting the brake force for at least one wheel axle of the Vehicle based on the estimated friction coefficient and the at least one wheel axle's estimated normal force

Abstract: A method for determining an operational state of a driver of a vehicle uses an awareness detection arrangement. The awareness detection arrangement includes at least a first and a second source for generating data relating to the behavior of the driver. The method includes receiving, from the first and the second source, data relating to at least one of physiological data of the driver, the operation of the vehicle, and a model of the driver operating the vehicle, comparing the data from the first and the second source with a driver state model defining a plurality of predefined driver states for each of the first and the second source, respectively, determining based on the comparison, for each of the first and the second source, a state probability for each of the plurality of predefined driver states, and weighing the determined driver states for the first and the second source with each other for determining an overall operational state probability for the driver.