Abstract: A method for controlling steering of a self-powered steerable dolly vehicle during a maneuver, the method comprising determining an articulation angle associated with a drawbar of the dolly vehicle, determining a longitudinal velocity of the dolly vehicle, and controlling the steering of the dolly vehicle based on the articulation angle and on the longitudinal velocity of the dolly vehicle, wherein the controlling comprises initially steering the dolly vehicle in a direction of the articulation angle direction in case the longitudinal velocity of the dolly vehicle is above a velocity threshold.

Abstract: The invention relates to a method for controlling vehicles (V1-V3) in a mission along a route, comprising—selecting at least two progress control value sets (u, tw), each value set comprising a respective value (u1, u2, u3, tw) of a progress control parameter for at least one of the vehicles, wherein each progress control parameter value influences the rate of progress of the respective vehicle, —determining, for each of the selected progress control value sets, a respective distribution (SoBfut) of the vehicles, if the at least one of the vehicles is controlled based on the respective selected progress control value set (u, tw), so that each progress control value set is correlated to a respective distribution (SoBfut) of the vehicles, —identifying, from the selected progress control value sets, based at least partly on the determinations of the distributions (SOBfut), a progress control value set (u, tw) for controlling the at least one of the vehicles, and—controlling the at least one of the vehicles (V1-V

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: The invention relates to a method of controlling a plurality of vehicles, performing the same mission cycle, comprising mapping a first set of planned degrees of progress (CCP1) to the cycle, controlling the vehicles to start the cycle at respective different points in time, determining deviations of the vehicles from a respective planned degree of progress (CCP1i) of the first set of planned degrees of progress (CCP1), mapping, based on the determined deviations, a second set of planned degrees of progress (CCP2) to the cycle, and controlling the vehicles so as to minimize deviations of the vehicles from a respective planned degree of progress (CCP2i) of the second set of planned degrees of progress (CCP2).

Abstract: The invention relates to a method for controlling vehicles (V1-V3) in a mission along a route, comprising—selecting at least two progress control value sets (u, tw), each value set comprising a respective value (u1, u2, u3, tw) of a progress control parameter for at least one of the vehicles, wherein each progress control parameter value influences the rate of progress of the respective vehicle, —determining, for each of the selected progress control value sets, a respective distribution (SoBfut) of the vehicles, if the at least one of the vehicles is controlled based on the respective selected progress control value set (u, tw), so that each progress control value set is correlated to a respective distribution (SoBfut) of the vehicles, —identifying, from the selected progress control value sets, based at least partly on the determinations of the distributions (SOBfut), a progress control value set (u, tw) for controlling the at least one of the vehicles, and—controlling the at least one of the vehicles (V1-V

Abstract: A method for operating a plurality of vehicles is disclosed. The method comprises receiving (101) a first set of vehicle data and a second set of vehicle data, the vehicle data comprising information about each vehicle of the plurality of vehicles, each vehicle operating along at least one fixed route, receiving (102) a first set of environmental data and a second set of environmental data, the environmental data comprising information about each fixed route, and estimating (103), by means of the global self-learning model and each local-self learning model, a schedule parameter for each vehicle of the plurality of vehicles based on the received first set of vehicle data, the received first set of environmental data, the received second set of vehicle data, the received second set of environmental data, and a predefined interaction model between the global self-learning model and each local-self learning model.