A vehicle management apparatus according to the present disclosure includes a memory, and a hardware processor coupled to the memory. The hardware processor is configured to: acquire a degradation state of a battery mounted on a vehicle, and an external variable factor concerning a plurality of districts in which the vehicle is to travel; and generate, based on the degradation state of the battery and the external variable factor, a vehicle deployment plan in which assignment of the vehicle to the plurality of districts is defined.

A method for adapting driving behavior includes inspecting driving behavior of a motor vehicle (1) travelling consecutively with a road user (2). Consecutive travel is detected by at least one sensor of the motor vehicle (1). If the other road user (2) is not detected, the method uses traffic data to predict a position of the other road user (2). If the predicted position of the road user (2) reveals consecutive travel, the method inspects the driving behavior of the motor vehicle (1) as in the case of consecutive travel detected by the at least one sensor. The method adapts a driving behavior while using few sensors to provide a high level of road safety and/or a high level of driving comfort. Optionally, a human-machine interface may display or report back a virtual representation of the road user in the predicted position to the driver of the motor vehicle.

A method for adapting driving behavior includes inspecting driving behavior of a motor vehicle (1) travelling consecutively with a road user (2). Consecutive travel is detected by at least one sensor of the motor vehicle (1). If the other road user (2) is not detected, the method uses traffic data to predict a position of the other road user (2). If the predicted position of the road user (2) reveals consecutive travel, the method inspects the driving behavior of the motor vehicle (1) as in the case of consecutive travel detected by the at least one sensor. The method adapts a driving behavior while using few sensors to provide a high level of road safety and/or a high level of driving comfort. Optionally, a human-machine interface may display or report back a virtual representation of the road user in the predicted position to the driver of the motor vehicle.

A method for monitoring extra off-duty time intervals of a driver includes: obtaining on-duty time intervals and off-duty time intervals of a driver; and scanning the off-duty time intervals to identify extra off-duty time intervals having a length more than a second minimum length and less than a first minimum length, any identified extra off-duty time intervals being subtracted from a predefined threshold. If the threshold is greater than 0, a workshift reset time interval is analyzed and it is determined if the workshift reset time interval includes an extra off-duty time interval, which cannot be used as workshift reset time interval. Subsequently the analyzed extra off-duty time intervals are subtracted from the threshold. If the threshold is greater than 0, the workshift reset time interval is analyzed and, the workshift reset time interval is, at least partly, shifted from today to tomorrow to create extra off-duty time interval today.

A method for monitoring extra off-duty time intervals of a driver includes: obtaining on-duty time intervals and off-duty time intervals of a driver; and scanning the off-duty time intervals to identify extra off-duty time intervals having a length more than a second minimum length and less than a first minimum length, any identified extra off-duty time intervals being subtracted from a predefined threshold. If the threshold is greater than 0, a workshift reset time interval is analyzed and it is determined if the workshift reset time interval includes an extra off-duty time interval, which cannot be used as workshift reset time interval. Subsequently the analyzed extra off-duty time intervals are subtracted from the threshold. If the threshold is greater than 0, the workshift reset time interval is analyzed and, the workshift reset time interval is, at least partly, shifted from today to tomorrow to create extra off-duty time interval today.

The invention relates to a system for determining the tire condition of a vehicle tire in a vehicle, said system comprising a number of sensors, which detect measurement values (m.sub.1, m.sub.2, m.sub.3) relevant to the tire condition, and a device for recording data and transmitting data, said device having a signal connection to the sensors on the input side. According to the invention, the signal output of the device has a preferably wireless signal connection to a readout unit, and the device generates actual tire parameters on the basis of the detected measurement values (m.sub.1, m.sub.2, m.sub.3) and directs said actual tire parameters to the readout unit.

The invention relates to a system for determining the tire condition of a vehicle tire in a vehicle, said system comprising a number of sensors, which detect measurement values (m.sub.1, m.sub.2, m.sub.3) relevant to the tire condition, and a device for recording data and transmitting data, said device having a signal connection to the sensors on the input side. According to the invention, the signal output of the device has a preferably wireless signal connection to a readout unit, and the device generates actual tire parameters on the basis of the detected measurement values (m.sub.1, m.sub.2, m.sub.3) and directs said actual tire parameters to the readout unit.

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).

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 work vehicle includes an engine; at least one continuously variable power source (CVP) configured to operate according to a commanded torque; an output shaft; a transmission positioned operatively between the output shaft and the engine and the CVP such that the output shaft selectively receives power from one or both of the engine and the at least one CVP; and a prognostics system configured to monitor a respective component associated with at least one of the output shaft or the transmission. The prognostics system includes a prognostics controller having a processor and memory architecture, configured to: receive input data, including the commanded torque; generate a usage value for the respective component for a time period as a function of the commanded torque; aggregate the usage value with previous usage values to generate a prognostics value over a life of the respective component; and store the prognostics value.