A vehicle height adjustment control apparatus is provided for compensating for vehicle pulls including a recognition device that recognizes that a vehicle is driven straight, a determination device that determines whether the vehicle pulls of the vehicle occur, in response to recognizing that the vehicle is driven straight, and a controller that generates a warning message and calculates compensation height control information of the vehicle in response to determining that the vehicle pulls occur.

A vehicle includes: recognizing a forward vehicle in response to the processing of image data captured by an image sensor disposed at the vehicle so as to have a field of view of the outside of the vehicle; obtaining a distance from the forward vehicle in response to the processing of detecting data captured by a radar disposed at the vehicle so as to have a detecting area of the outside of the vehicle; obtaining a change amount of vertical movement of the forward vehicle in the image data in response to the distance from the forward vehicle that is equal to or less than a reference distance; obtaining a height of an obstacle on a road surface corresponding to the change amount; obtaining the height of the obstacle on the road surface in the image data in response to the distance from the forward vehicle that exceeds the reference distance; identifying a driving speed of the vehicle; identifying a reference height corresponding to the driving speed of the vehicle; and outputting deceleration guide information in response to the height of the obstacle on the road surface that is greater than or equal to the reference height.

A system, comprising a computer having a processor and a memory storing instructions executable by the processor to identify a height of a curb that is at least one of within or bordering a parking area having a specified length and width. The instructions include instructions to identify a location of the curb. The instructions include instructions to determine a parking position within the parking area based on the height of the curb and the location of the curb. The instructions include instructions to park a vehicle at the parking position within the parking area.

A processor unit (3) is configured for executing an MPC algorithm (13) for model predictive control of a prime mover (8) and of at least one vehicle component influencing energy efficiency of a motor vehicle. The MPC algorithm (13) includes a longitudinal dynamic model (14) of the drive train (7) and of the vehicle component influencing the energy efficiency of the motor vehicle (1) as well as a cost function (15) to be minimized. The cost function (15) includes at least one first term. The processor unit (3) is configured for determining a particular input variable for the prime mover (8) and for the at least one vehicle component influencing the energy efficiency of the motor vehicle (1) by executing the MPC algorithm (13) as a function of a particular term such that the cost function (15) is minimized.

A processor unit (3) is configured for executing an MPC algorithm (13) for model predictive control of a prime mover (8) and of at least one vehicle component influencing energy efficiency of a motor vehicle. The MPC algorithm (13) includes a longitudinal dynamic model (14) of the drive train (7) and of the vehicle component influencing the energy efficiency of the motor vehicle (1) as well as a cost function (15) to be minimized. The cost function (15) includes at least one first term. The processor unit (3) is configured for determining a particular input variable for the prime mover (8) and for the at least one vehicle component influencing the energy efficiency of the motor vehicle (1) by executing the MPC algorithm (13) as a function of a particular term such that the cost function (15) is minimized.

A method of controlling operation of a vehicle includes monitoring at least one of a location and a route of the vehicle when the vehicle is in a first operating state, receiving map data related to an area around at least one of the location and the route, and identifying, based on the map data, one or more map attributes indicative of one or more features of the area. The method also includes comparing the one or more map attributes to at least one reference attribute, and based on the one or more map attributes matching the at least one reference attribute, causing the vehicle to enter a second operating state when the vehicle is in the area.

A method of controlling operation of a vehicle includes monitoring at least one of a location and a route of the vehicle when the vehicle is in a first operating state, receiving map data related to an area around at least one of the location and the route, and identifying, based on the map data, one or more map attributes indicative of one or more features of the area. The method also includes comparing the one or more map attributes to at least one reference attribute, and based on the one or more map attributes matching the at least one reference attribute, causing the vehicle to enter a second operating state when the vehicle is in the area.

The present disclosure relates to a method and an apparatus for controlling an electronic control suspension using a deep learning-based road surface classification model. The method for controlling an electronic control suspension in a vehicle including a camera and a GPS receiver may include collecting location information of the vehicle using the GPS receiver while driving, identifying whether there is a previously generated road surface classification model corresponding to a front obstacle when the front obstacle is detected, determining a first control value based on a first characteristic value corresponding to the road surface classification model when there is the road surface classification model as a result of the identification, controlling the electronic control suspension with the determined first control value when entering the obstacle, and collecting new sensing data through a physical sensor, and correcting the first characteristic value based on the new sensing data.

An apparatus including a capture device and a processor. The capture device may be configured to generate pixel data corresponding to an exterior view from a vehicle. The processor may be configured to generate video frames from the pixel data, perform computer vision operations on the video frames to detect objects in the video frames and determine characteristics of the objects, detect a change in orientation of the vehicle at a first time, analyze the characteristics of the objects at a second time to determine a cause of the change in orientation of the vehicle and generate annotations for the video frames that comprise the objects determined to have caused the change in orientation of the vehicle. The second time may be earlier than the first time.

A human-powered vehicle control device is provided for suitably controlling a rotation state of a wheel of a human-powered vehicle. The human-powered vehicle control device includes a first detector and an electronic controller. The first detector is configured to detect information related to a driving force of the wheel of the human-powered vehicle on a road surface. The electronic controller is configured to change an operation state of a suspension device of the human-powered vehicle in response to a detection result of the first detector.