The disclosure relates to a method for operating a hybrid electric vehicle. According to the method, a route information is received in the form of a plurality of parameter sets, each parameter set relating to a segment of a route (S1). Subsequently, a power demand is estimated for each segment (S3) and a portion of an amount of energy being stored in the electric storage device is allocated to at least one of the segments. Alternatively or additionally, an amount of energy to be transferred into the electric storage device is allocated to at least one of the segments (S4). Additionally, at least one reference trajectory describing a state-of-energy of the electric storage device over the route resulting from the energy allocation is derived (S5). The operation of the hybrid electric vehicle is controlled as a function of a slope between a current state-of-energy and an upcoming control point on the reference trajectory (S7). Moreover, a data processing device comprising means for carrying out the method is presented.

A training device includes a storage device that has stored a program, and a hardware processor, in which the hardware processor executes the program stored in the storage device, thereby acquiring a captured image of a road, adding a computer graphic image of an object present on a road to an actually captured image based on the captured image, and training parameters of a model to output a type of the object when an image is input using a type of the added computer graphic image as teacher data.

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 system for controlling platooning by a following vehicle includes a main body of the following vehicle. The system further includes a pressure sensor located in or on the main body and configured to detect a pressure corresponding to a pressure wake from a leading vehicle. The system further includes an electronic control unit (ECU) located in or on the main body, coupled to the pressure sensor, and configured to determine an optimal distance from the following vehicle to the leading vehicle based on the detected pressure. The optimal distance corresponding to a distance at which drag applied to the following vehicle is reduced based on the pressure wake from the leading vehicle.

A non-transitory processor-readable medium stores code representing instructions to be executed by the processor. The code comprises code to cause the processor to receive a first image and a second image from a stereo camera pair disposed with a vehicle. The code causes the processor to detect, using a machine learning model, an object based on the first image, the object located within a pre-defined area within a vicinity of the vehicle. The code causes the processor to determine a distance between the object and the vehicle based on disparity between the first image and the second image. The code causes the processor to determine a longitudinal value of the vehicle based on the distance and a height of the vehicle. The code causes the processor to send an instruction to facilitate driving of the vehicle based on a road profile associated with the longitudinal value.

The technology employs a variable motion control envelope that enables an on-board computing system of a self-driving vehicle to estimate future vehicle driving behavior along an upcoming path, in order to maintain a desired amount of control during autonomous driving. Factors including intrinsic vehicle properties, extrinsic environmental influences and road friction information are evaluated. Such factors can be evaluated to derive an available acceleration model, which defines an envelope of maximum longitudinal and lateral accelerations for the vehicle. This model, which may identify dynamically varying acceleration limits that can be affected by road conditions and road configurations, may be used by the on-board control system (e.g., a planner module of the processing system) to control driving operations of the vehicle in an autonomous driving mode.

An autonomous vehicle and a system and method of operating the autonomous vehicle. The system includes a sensor and a processor. The processor determines an effective observation area of the sensor, the effective observation area being affected by an extrinsic condition. The processor determines an available time for performing a lane change based on the effective observation area and performs the lane change based on the available time.

An object is to provide a vehicle control apparatus capable of enhancing fuel economy when coasting is performed by disconnecting a clutch disposed between an engine and drive wheels of the vehicle. A travel path and a travel pattern of a vehicle are predicted by a vehicle outside information collection device, such as a navigation system. Also, amounts of fuel consumption by normal traveling and coasting are predicted and compared, so that coasting control is performed in a case where an amount of fuel consumption can be reduced by performing the coasting control.

A computer-implemented method is provided that involves determining, based on map data, an approaching merge region comprising an on-ramp merging with a road comprising one or more lanes, wherein a truck is traveling on an initial lane of the road according to a navigation plan. The method involves an indication of movement of a vehicle on the on-ramp, wherein the indication of movement is based on data collected by one or more sensors configured to capture sensor data from an environment surrounding the truck. The method involves determining, for the on-ramp and the one or more lanes, respective avoidance scores indicative of a likelihood of an interaction between the truck and the vehicle based on the approaching merge region. The method involves updating the navigation plan based on the respective avoidance scores. The method also involves controlling the truck to execute a driving strategy based on the updated navigation plan.

A method (400) and a control unit (310) in a vehicle (100) having an ACC system (500) for adjusting a variable time gap (t) to be kept to a preceding vehicle (110), based on a road slope (α). In the method (400): determining (401) geographical position of the vehicle (100); determining (402) driving direction (105) of the vehicle (100); determining (403) the road slope (α) of the road (120) in front of the vehicle (100) in the determined (402) driving direction (105); and adjusting (408) the variable time gap (t) based on the determined (403) road slope (α) of the road (120) in front of the vehicle (100) by: increasing the variable time gap (t) when the road slope (α) is negative, indicating downhill; or decreasing the variable time gap (t) when the road slope (α) is positive, indicating uphill.