A system and method for classifying a type of interaction between a human user and a mobile communication device within a defined volume, based on multiple sensors. The method may include: determining a position of the mobile communication device relative to a frame of reference of the defined volume, based on: angle of arrival, time of flight, or received intensity of radio frequency (RF) signals transmitted by the mobile communication device and received by a phone location unit located within the defined volume configured to wirelessly communicate with the mobile communication device; obtaining at least one sensor measurement related to the mobile communication device from various non-RF sensors; repeating the obtaining, to yield a time series of sensor readings; and using a computer processor to classify the type of interaction into one of many predefined types of interactions, based on the position and the time series of sensor readings.

According to an aspect, there is provided a computer-implemented method for condition monitoring of a vehicle. The method comprises applying a dynamic model associated with a vehicle (800), the dynamic model having been determined by obtaining status information from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle (200), obtaining, based on vehicle identity information, vehicle dynamics information (202), obtaining map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data (204), analyzing behavior of the vehicle based on the status information and the vehicle dynamics information (206), and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data (208); analyzing historical changes in at least one calibration parameter associated with the dynamic model of the vehicle (802); analyzing effects of the three-dimensional road map associated with the roads and the road characteristics data in at least one position on the behavior of the vehicle (804); and determining, based on the analyzed historical changes and the effects, at least one change in at least one vehicle characteristic (806).

A system and method for classifying a type of calibration or maintenance event of a phone location unit (PLU) within a defined volume, based on at least one sensor, the method comprising: determining a position of the at least one mobile communication device relative to a frame of reference of the defined volume; obtaining at least one sensor measurement related to the at least one mobile communication device, from a sensor located on at least one of: the at least one mobile communication device, within the defined volume, or outside of the defined volume; and using a computer processor to classify the type of calibration or maintenance event of the PLU, into one of a plurality of predefined types of calibration or maintenance event, based on the position and the at least one sensor measurement.

A system and method for classifying a mode of operation of a mobile communication device within a defined volume, based on multiple sensors are provided herein. The method may include the following steps: determining a position of the mobile communication device relative to a frame of reference of the defined volume, based on any of: angle of arrival, time of flight, or received intensity of radio frequency (RF) signals transmitted by the mobile communication device and received by a phone location unit located within the defined volume configured to wirelessly communicate with the at least one mobile communication device; obtaining at least one sensor measurement related to the mobile communication device from various non-RF sensors; and using a computer processor to classify the mobile communication device into one of many predefined modes of operation of the mobile communication device, based on the position and the sensor readings.

A remote driving device configured to remotely operate a vehicle includes a remote operation device, a reaction force unit, a receiver, and a processor. The remote operation device is operated by an operator in order to remotely operate the vehicle. The reaction force unit is configured to generate an operation reaction force to be applied to the remote operation device. The receiver is configured to receive a parameter affecting vehicle characteristics of the vehicle from the vehicle. The processor is configured to control the reaction force unit so as to generate a magnitude of the operation reaction force according to the received parameter.

A remote driving device configured to remotely operate a vehicle includes a remote operation device, a reaction force unit, a receiver, and a processor. The remote operation device is operated by an operator in order to remotely operate the vehicle. The reaction force unit is configured to generate an operation reaction force to be applied to the remote operation device. The receiver is configured to receive a parameter affecting vehicle characteristics of the vehicle from the vehicle. The processor is configured to control the reaction force unit so as to generate a magnitude of the operation reaction force according to the received parameter.

A system and method for classifying a type of interaction between a human user and a mobile communication device within a defined volume, based on multiple sensors. The method may include: determining a position of the mobile communication device relative to a frame of reference of the defined volume, based on: angle of arrival, time of flight, or received intensity of radio frequency (RF) signals transmitted by the mobile communication device and received by a phone location unit located within the defined volume configured to wirelessly communicate with the mobile communication device; obtaining at least one sensor measurement related to the mobile communication device from various non-RF sensors; repeating the obtaining, to yield a time series of sensor readings; and using a computer processor to classify the type of interaction into one of many predefined types of interactions, based on the position and the time series of sensor readings.

According to an aspect, there is provided a computer-implemented method for condition monitoring of a vehicle. The method comprises applying a dynamic model associated with a vehicle (800), the dynamic model having been determined by obtaining status information from at least one information bus of the vehicle, the status information providing real-time status information about the vehicle (200), obtaining, based on vehicle identity information, vehicle dynamics information (202), obtaining map data representing road characteristics of roads of a geographical area, the map data comprising two-dimensional road map data, three-dimensional road map associated with the roads, and road characteristics data (204), analyzing behavior of the vehicle based on the status information and the vehicle dynamics information (206), and computing a dynamic model for the vehicle by comparing the behavior of the vehicle to the map data (208); analyzing historical changes in at least one calibration parameter associated with the dynamic model of the vehicle (802); analyzing effects of the three-dimensional road map associated with the roads and the road characteristics data in at least one position on the behavior of the vehicle (804); and determining, based on the analyzed historical changes and the effects, at least one change in at least one vehicle characteristic (806).

A method of determining at least one drag torque acting on the input side of an automatic transmission, such that prior to the determination a separator clutch located between the transmission and an engine is disengaged. To be able to carry out the determination regardless of the type of transmission concerned, also prior to the determination, the transmission is shifted to neutral and subsequently the drag torque is calculated when the engine is deactivated. For this, a first gradient of a transmission input rotational speed is determined, before an engine rotational speed of the engine falls below the transmission input rotational speed, and a second gradient of the transmission input rotational speed is determined, after the engine rotational speed falls below the transmission input rotational speed. The method is stored as a computer program stored on data carrier of a drive-train control unit of a motor vehicle.

A system and method for classifying a mode of operation of a mobile communication device within a defined volume, based on multiple sensors are provided herein. The method may include the following steps: determining a position of the mobile communication device relative to a frame of reference of the defined volume, based on any of: angle of arrival, time of flight, or received intensity of radio frequency (RF) signals transmitted by the mobile communication device and received by a phone location unit located within the defined volume configured to wirelessly communicate with the at least one mobile communication device; obtaining at least one sensor measurement related to the mobile communication device from various non-RF sensors; and using a computer processor to classify the mobile communication device into one of many predefined modes of operation of the mobile communication device, based on the position and the sensor readings.