A vehicle control device includes: a first detection unit that detects a traveling state of a host vehicle; a merging detection unit that detects that the host vehicle approaches within a predetermined area of a merging point when the host vehicle travels on the merging road toward the merging point at which a main road joins with the merging road; a second detection unit that detects a speed of a lane flow by another vehicle that travels on the main road toward the merging point; a position detection unit that obtains a position of a pre-merging point as a virtual point on the main road reaching the merging point when the host vehicle reaches the merging point; and a display control unit that controls a display device to display the position of the host vehicle and the pre-merging point.

A method includes receiving, at a server, first sensor data from a first vehicle. The method includes receiving, at the server, second sensor data from a second vehicle. The second sensor data includes condition data indicating a road condition. The method includes aggregating, at the server, a plurality of sensor readings to generate aggregated sensor data. The plurality of sensor readings include the first sensor data and the second sensor data. The method further includes transmitting a first message based on the aggregated sensor data to the first vehicle, wherein the first message causes the first vehicle to perform a first action, the first action comprising avoiding the road condition, displaying an indicator corresponding to the engine problem, displaying a booked route, or a combination thereof.

A vehicle system includes an electronic control unit. The electronic control unit is configured to execute a first program, a second program, and a third program. The first program is configured to recognize an object present around a vehicle, the second program is configured to store information related to the recognized object as time-series map data, and the third program is configured to predict a future position of the object based on the stored time-series map data. The first program and the third program are configured to be (i) first, individually optimized based on first training data corresponding to output of the first program and second training data corresponding to output of the third program, and (ii) then, collectively optimized based on the second training data corresponding to the output of the third program.

Methods, computer-readable media, software, and apparatuses include collecting, via one or more sensors and during a first window of time, sensor data associated with an acceleration of the vehicle, processing the sensor data to obtain frequency domain sensor data, analyzing the frequency domain sensor data to identify one or more occurrences of a vehicle mass change event, classifying a use of the vehicle for a shared mobility service during one or more time periods of the first window of time based on the one or more occurrences of a vehicle mass change, and transmitting, to a remote computing device, a notification relating to use of the vehicle for the shared mobility service.

The disclosure generally pertains to recommending an alternative off-road track to a driver of a vehicle. In an example method, a processor receives a sensor signal that is generated in response to an operating condition of the vehicle on an off-road track. The operating condition can include, for example, an angular orientation of a chassis portion of the vehicle with respect to a ground surface (yaw, pitch, roll, etc.), steering characteristics, speed characteristics, and/or braking characteristics. The processor evaluates the sensor signal to identify an attribute of the off-road track, such as, for example, a difficulty factor and/or a challenge level. The processor may assign a track score to the off-road track based on the attribute and may provide to the driver, a recommendation for use of another off-road track based on comparing the first track score to a second track score associated with the other off-road track.

In some examples, a controller receives information of a route of a vehicle, and selects a first parameter set from among a plurality of parameter sets based on the route of the vehicle, the plurality of parameter sets corresponding to different conditions of usage of the vehicle, where each parameter set of the plurality of parameter sets includes one or more parameters that control adjustment of one or more respective adjustable elements of the vehicle. The controller causes application of the first parameter set to control a setting of the one or more adjustable elements of the vehicle.

A method and system for estimating surface roughness of a ground for an off-road vehicle to control steering of a vehicle, an implement, or both, comprises detecting motion data of an off-road vehicle traversing a field or work site during a sampling interval. A first sensor is adapted to detect pitch data of the off-road vehicle for the sampling interval to obtain a pitch acceleration. A second sensor is adapted to detect roll data of the off-road vehicle for the sampling interval to obtain a roll acceleration. An electronic data processor or surface roughness index module determines or estimates a surface roughness index based on the detected motion data, pitch data and roll data for the sampling interval. The surface roughness index can be displayed on the graphical display to a user or operator of the vehicle.

An environment detection device for a vehicle is includes a sensor unit for determining environment information of a surrounding area of the vehicle itself, with a temperature measurement unit, configured to measure at least one state temperature of the sensor unit, and with a controller, configured to trigger at least one action for reducing the state temperature if a prescribed temperature warning value is exceeded.

Systems and methods are provided for vehicle navigation. In one implementation, a host vehicle-based sparse map feature harvester system may include at least one processor programmed to receive a plurality of images captured by a camera onboard the host vehicle as the host vehicle travels along a road segment in a first direction, wherein the plurality of images are representative of an environment of the host vehicle; detect one or more semantic features represented in one or more of the plurality of images, the one or more semantic features each being associated with a predetermined object type classification; identify at least one position descriptor associated with each of the detected one or more semantic features; identify three-dimensional feature points associated with one or more detected objects represented in at least one of the plurality of images; receive position information, for each of the plurality of images, wherein the position information is indicative of a position of the camera when each of the plurality of images was captured; and cause transmission of drive information for the road segment to an entity remotely-located relative to the host vehicle, wherein the drive information includes the identified at least one position descriptor associated with each of the detected one or more semantic features, the identified three-dimensional feature points, and the position information.

A vehicle control device for controlling a vehicle with a frictional engagement element provided between a drive source and drive wheels includes a first determination unit configured to determine whether or not a signal of an inhibitor switch indicates a traveling position, a second determination unit configured to determine whether or not an oil path communicating with the frictional engagement element is in a drain state, a temperature estimation unit configured to estimate temperature of the frictional engagement element, and a temperature estimation prohibition unit configured to prohibit temperature estimation of the frictional engagement element by the temperature estimation unit when the signal of the inhibitor switch indicates the traveling position and the oil path is in the drain state.