A vehicle moves through an environment (e.g., a farming, construction, mining, or forestry environment) and performs one or more actions in the environment. Portions of the environment may include moisture, such as puddles or mud patches. A control system associated with the vehicle may include a traversability model or a moisture model to help the vehicle operate in the environment with the moisture. In particular, the control system may employ the traversability model to reduce the likelihood of the vehicle attempting to traverse an untraversable portion of the environment, and the control system may employ the moisture model to reduce the likelihood of the vehicle performing an action that will damage a portion of the environment.

A user-generated graphical representation can be sent into a generative network to generate a synthetic image of an area including a road, the user-generated graphical representation including at least three different colors and each color from the at least three different colors representing a feature from a plurality of features. A determination can be made that a discrimination network fails to distinguish between the synthetic image and a sensor detected image. The synthetic image can be sent, in response to determining that the discrimination network fails to distinguish between the synthetic image and the sensor-detected image, into an object detector to generate a non-user-generated graphical representation. An objective function can be determined based on a comparison between the user-generated graphical representation and the non-user-generated graphical representation. A perception model can be trained using the synthetic image in response to determining that the objective function is within a predetermined acceptable range.

In an apparatus for determining a traveling position of an own vehicle that is an autonomous driving vehicle equipped with the apparatus, a judgment section is configured to judge presence or absence of at least one of a travel history of other vehicles regarding the lane in which the own vehicle is traveling and an object that is located in the vicinity of the own vehicle within the lane in which the own vehicle is traveling and should be avoided coming into contact with. The traveling position is a widthwise position of the own vehicle within a lane in which the own vehicle is traveling. A determination section is configured to determine the traveling position using the travel history in response to the judgment section judging that the travel history exists and using position information of the object in response to the judgment section judging that the object exists.

A system for use in a vehicle for determining an indication of the type of terrain in the vicinity of the vehicle, the system comprising; means configured to receive sensor output data from at least one sensor on the vehicle; means configured to determine a plurality of parameters in dependence on the sensor output data; a neural network algorithm configured to receive the plurality of parameters; and means configured to execute the neural network algorithm to provide a plurality of outputs corresponding to a plurality of different terrain types, the neural network being further configured to associate the plurality of parameters with one of the plurality of outputs, so as to determine an indication of the terrain type.

A traffic light detection device includes: an image capture unit capturing an image of surroundings; a traffic light location estimation unit estimating a location of a traffic light around the vehicle and setting a traffic light search area in which the traffic light is estimated to be present; a traffic light detection unit detecting the traffic light by searching the traffic light search area on the image; and an obstruction estimation unit. When the obstruction estimation unit estimates that a continuous obstruction state where a view of the traffic light is continuously obstructed occurs in the traffic light search area, the traffic light location estimation unit selects the traffic light search area based on the continuous obstruction state.

A device and a method are provided. The device includes a communication module, a memory, and a processor. The processor is configured to acquire position information of a vehicle via the communication module, determine whether high definition (HD) map information corresponding to the position information is acquired, display three-dimensional (3D) navigation information in augmented reality by using the HD map information when the HD map information is acquired, and display two-dimensional (2D) navigation information in augmented reality when the HD map information is not acquired. The 3D navigation information is information in which virtual 3D graphic information for driving guidance is spatially matched to and displayed on an actual object in the real world by using the HD map information, and the 2D navigation information is information in which virtual 2D graphic information for driving guidance is planarly matched to and displayed on an actual object in the real world.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

A demarcation line recognition apparatus (10) is applied to a vehicle in which an imaging apparatus (21) that captures an image of an area ahead of the vehicle is mounted. The demarcation line recognition apparatus (10) includes: a demarcation line recognizing unit (11) that recognizes a traveling demarcation line that demarcates a traveling lane of the vehicle based on an image acquired by the imaging apparatus (21); and a demarcation line estimating unit (12) that estimates a shape of the traveling demarcation line in a range that cannot be recognized by the demarcation line recognizing unit (11), based on the traveling demarcation line recognized by the demarcation line recognizing unit (11). The demarcation line recognition apparatus (10) determines a reliability level of the traveling demarcation line recognized by the demarcation line recognizing unit (11) and invalidates the estimation of the shape of the traveling demarcation line by the demarcation line estimating unit (12) based on the determination result.

Among other things, techniques are described for receiving, from at least one sensor of a vehicle, sensor data associated with a surface along a path to be traveled by a vehicle; using a surface classifier to determine a classification of the surface based on the sensor data; determining, based on the classification of the surface, drivability properties of the surface; planning, based on the drivability properties of the surface, a behavior of the vehicle when driving near the surface or on the surface; and controlling the vehicle based on the planned behavior.

According to various embodiments, a vehicle may be provided. The vehicle may include: a sensor configured to sense a marking, wherein the marking is at least substantially not visible to the human eye under a natural lighting condition; and a localization circuit configured to determine a location of the vehicle based on the sensing of the sensor.