Abstract: A method to determine if a traffic situation comprising a plurality of heavy-duty vehicles following a plurality of guided vehicle trajectories in a defined area will lead to a vehicle deadlock is described. For example, one method includes generating a traffic situation representation for the defined area comprising, for each of the plurality of vehicles, an initial vehicle trajectory segment location and a subsequent deadlock status, inputting the traffic situation representation to a traffic situation deadlock classifier which has been trained to output a traffic situation deadlock classification based on an input representation of a traffic situation in the defined area, and, based on the input traffic situation representation, generating a predicted deadlock classification of a subsequent traffic situation for that input traffic situation representation.

Abstract: A method for controlling a vehicle travelling along a route is provided.

Abstract: A computer implemented method for operating a vehicle, specifically in relation to efficient transporting of a predefined cargo. The present disclosure also relates to a corresponding arrangement and computer program product.

Abstract: A computer-implemented method of assessing vehicle trajectories for deadlock scenarios in a site where multiple vehicles operate by following planned vehicle trajectories is described. The site includes at least one traffic-constrained area via which at least two of the multiple vehicles passes when following their planned trajectories.

Abstract: A computer-implemented traffic planning method controls a plurality of vehicles which are movable among multiple shared resources. The method includes receiving a transport mission; generating a root node representing an initial resource occupancy of the vehicles; generating a search tree from the root node, in which each edge represents a motion command and each node represents a resource occupancy, wherein each node is associated with a score related to the vehicles' fulfilment of the transport mission; identifying a target node with an acceptable score; and deriving a planned sequence of motion commands corresponding to a path to the target node. The score of a node includes a short-term component, which represents a cost of executing all motion commands from the root node to said node, and a long-term component, which is determined by the resource occupancy that the node represents.

Abstract: The present disclosure generally relates to a computer implemented method for operating a vehicle (104, 106, 108), specifically in relation to efficient transporting of a predefined cargo. The present disclosure also relates to a corresponding arrangement and computer program product.

Abstract: The invention provides a method for controlling a plurality of vehicles which are repeating a cycle of driving along a route, which has at least one single vehicle area (SLTA1, . . .

Abstract: An apparatus for forming at least one three-dimensional article through successive fusion of parts of a powder bed, which parts corresponds to successive cross sections of the three-dimensional article, the apparatus comprising: a powder distributor configured for evenly distributing a layer of powder on top of a work table provided inside a build chamber; and at least one high energy beam source emanating at least one high energy beam configured for fusing the powder layer in selected locations corresponding to the cross section of the three-dimensional article, wherein the apparatus further comprising at least one target area arranged spaced apart from the layer of powder for emanating light when irradiated by the at least one high energy beam.

Abstract: The invention relates to a method for determining an operational parameter indicative of the power capability of an energy storage system (ESS) of a vehicle, wherein the method comprises the steps of determining a state temperature of the ESS; determining an acceptable temperature increase of the ESS for a given time period based on the determined state temperature of the ESS and a maximum temperature threshold of ESS, the maximum temperature threshold being indicative of any one of a safety temperature level of the ESS and an operational life time temperature level of the ESS; and determining a maximum operational power level of the ESS for the given time period based on the determined acceptable temperature increase of the ESS.

Abstract: A method of visualizing output data of a traffic planning method for controlling a plurality of vehicles (v1, v2, . . . ), wherein each vehicle occupies one node in a shared set of planning nodes (wp1, wp2, . . . ) and is movable to other nodes along predefined edges between pairs of the nodes, wherein the output data indicates respective planned node occupancies of the vehicles for a sequence of time steps, the method comprising: obtaining a graphical representation of the planning nodes; and in the graphical representation, indicating each vehicle's planned movements between the nodes by linear graphical elements, wherein an appearance parameter of the linear graphical elements has a time variation with respect to the time step, which time variation is common to all vehicles. The appearance parameter may be a line width, line style, color or texture.

Abstract: A method for controlling a plurality of vehicles performing missions along a respective route includes obtaining for each vehicle of the plurality of vehicles, a first value of a balance parameter, indicative of a balance between a cost for operating the respective vehicle along at least a part of the route, and a progress of the respective vehicle along at least a part of the route, establishing, in dependence on the first balance parameter values, a desired number of completed missions as a function of time, after an initial of the missions has started, and before all missions are completed, determining a mission completion deviation comprising a deviation of an actual number of completed missions from the desired number of completed missions, obtaining for each of one or more of the vehicles a second balance parameter value, different from the respective first balance parameter value, the respective second balance parameter value being dependent on the mission completion deviation, and controlling the one

Abstract: The invention relates to a system for and method of determining a model for estimating battery properties in a hybrid or electrical drive system (900) for a vehicle (902), the method comprising: providing (51) a function approximator estimating a battery property as a function of two or more measured battery parameters; providing (52) a stream of measured battery parameter values as a function of time for a predetermined period to a predetermined battery cell model describing the relationship between the measured battery parameter and the battery property; determining (S3) a battery property value using the cell model based on a selected portion of the stream of measured battery parameter values; determining (S4) if a predetermined condition for the selected portion of the stream of measured battery parameter values is fulfilled; and if (S5) the predetermined condition is fulfilled, updating (S6) the function approximator based on the battery property value determined by the cell model.

Abstract: A method and system for estimating the state-of-health of a battery The invention relates to a method for estimating the state-of-health, SoHest, of a battery in a vehicle, the method comprising: determining (100) a first battery property and a battery temperature of a battery in a vehicle; calculating (102) a state-of-health, SoHcalc, of a battery cell based on the determined first battery property using a predetermined model; providing (104) a function f estimating a battery cell degradation rate; updating (106) a state-of health estimated in a previous time step according to SoHest?SoHest+ƒ·dt+K·(SoHcalc?SoHest), where K is a gain factor which is dependent on operating conditions of the vehicle, and wherein K is modified (108) for each time step using a reinforcement learning agent.

Abstract: A method of monitoring a spot quality of an electron beam includes directing the electron beam to a first measurement point in a powder layer a plurality of times, adjusting a focus offset of the electron beam each of the plurality of times the electron beam is directed to the first measurement point, measuring x-ray emissions from the first measurement point each of the plurality of times the electron beam is directed to the first measurement point, and determining a drift in a focus or an intensity of the electron beam based on the measured x-ray emissions.

Abstract: The invention relates to a method (100) for estimating an operating parameter of a battery cell of a battery unit in an electrical propulsion system of a vehicle, the operating parameter being indicative of one of capacity and impedance of the battery cell, the method comprising: selecting (110) at least one battery cell in the battery unit for determining the operating parameter of the battery cell; providing (120) a set of state-of-charge (SOC) estimators, each SOC estimator having a selected operating parameter value for a given time period; and using (130) the set of SOC estimators to determine a value of the operating parameter of the battery cell by performing voltage error minimization.

Abstract: A method for controlling a vehicle travelling along a route is provided.

Abstract: A method of visualizing output data of a traffic planning method for controlling a plurality of vehicles (v1, v2, . . . ), wherein each vehicle occupies one node in a shared set of planning nodes (wp1, wp2, . . . ) and is movable to other nodes along predefined edges between pairs of the nodes, wherein the output data indicates respective planned node occupancies of the vehicles for a sequence of time steps, the method comprising: obtaining a graphical representation of the planning nodes; and in the graphical representation, indicating each vehicle's planned movements between the nodes by linear graphical elements, wherein an appearance parameter of the linear graphical elements has a time variation with respect to the time step, which time variation is common to all vehicles. The appearance parameter may be a line width, line style, color or texture.

Abstract: The present disclosure generally relates to a computer implemented method for operating an autonomous vehicle, specifically in relation to efficient planning of interactions with service providers. The present disclosure also relates to a corresponding control system and computer program product.

Abstract: A traffic planning method for controlling a plurality of vehicles, wherein each vehicle occupies one node in a shared set of planning nodes and is movable to other nodes along predefined edges between pairs of the nodes in accordance with a finite set of motion commands. In the method, initial node occupancies of the vehicles are obtained, and a sequence of motion commands are determined by optimizing a state-action value function which depends on node occupancies s and the motion commands a to be given. The state-action value function includes a command-dependent term, which is updated in each iteration based on a reward function, and a command-independent term, which penalizes node occupancies with too small inter-vehicle gaps and is exempted from said updating.

Abstract: A computer-implemented method of managing a machine-learning, ML, algorithm which is dependent on one or more hyperparameters is described. The method comprises: providing a plurality of instances of the ML algorithm using different values of the hyperparameters; obtaining a plurality of input states; mapping each predefined input to a plurality of outputs using the instances of the ML algorithm; evaluating a predefined quality metric for the outputs; and on the basis of statistics of the quality metric for the outputs, selecting at least one instance of the ML algorithm for continued use. In some embodiments, a technical system is controlled using one primary instance of the ML algorithm. If the selected instance of the ML algorithm is not the primary instance, the primary instance may optionally be replaced by the selected instance.