A method performed by a control unit for managing energy flows within an energy system of a vehicle is provided. The energy system includes a plurality of energy subsystems connected by converters. The converter can convert energy of one energy form from one energy subsystem to energy of another energy form of another energy subsystem. At least one energy subsystem includes an energy buffer. According to the method performed by a control unit vehicle travel route information is collected for a predefined travel route whereby the travel route can be divided in part routes. By estimating an energy consumption over respective part route for each energy buffer an estimated energy buffer price for respective part route can be calculated by the control unit. The estimated energy buffer price can subsequently be used such that energy can be provided between energy subsystems such that the available energy for a part route can be distributed within the energy system of the vehicle in the most efficient way by the control unit and the usage of respective energy buffer can be optimized.

A method and a device for localizing a vehicle in its surroundings, the vehicle having surround sensors, which at first times detect views of the surroundings using the surround sensors as sensor views and supply these to an evaluation unit, and having a communication interface, via which at second times current surroundings data regarding the current surroundings of the vehicle are transmitted to the evaluation unit, and the localization of the vehicle occurs in that in the evaluation unit the surroundings data, which were detected by the surround sensors at first times, and the temporally corresponding surrounding data, which were transmitted via the communication interface, are superimposed on one another. If it is detected that features in the surroundings data detected by the sensors and/or features in the surroundings data supplied via the communication interface occur multiple times in the data pertaining to one point in time and these represent one or multiple objects, these are transmitted only once to the evaluation device and, for a repeated occurrence of the features in the data pertaining to one point in time, only the positional data of the repeatedly occurring object are transmitted anew.

Technologies and techniques for the at least the partially automated driving of a motor vehicle. A first application and at least one redundant second application provide output data depending on motor vehicle operating data and/or environmental data. Vehicle driving data for the at least partially automated driving of the motor vehicle are determined depending on the output data. Vehicle operating data from another vehicle are received, and, depending on the vehicle operating data, the at least one redundant second application switches from an active state to a standby state in which a computer instance of a computer unit used by the at least one redundant second application is at least executed at a lower frequency than in the active state.

This on-vehicle system is to be mounted in a vehicle and is provided with an electronic control device and an externality recognition sensor. The externality recognition sensor is equipped with a sensing unit for acquiring pre-processing externality information through sensing operations. The on-vehicle system is further equipped with: a condition calculation unit that, on the basis of a vehicle position, a vehicle traveling direction, and map information, calculates a processing condition in which information specifying an area on a map is associated with processing priority of the pre-processing externality information acquired by the externality recognition sensor; and a processing object determination unit that, on the basis of the pre-processing externality information and the processing condition, creates externality information having a smaller amount of information compared with the pre-processing externality information.

Embodiments relate to the detection of edge cases through application of a neural network to predict future vehicle environment data and identifying an edge case when the prediction error exceeds a given threshold. This allows edge cases to be identified based on unexpected vehicle environmental conditions or conditions that otherwise cause the neural network to make inaccurate predictions. These edge cases can then be utilised to better train machine learning systems, for instance, to train autonomous vehicle control systems. Alternatively, the identification of an edge case can highlight the need for remedial action, and can therefore trigger an alert to a vehicle control system to take remedial action. Further methods and systems described herein improve environmental sensing by providing a computationally efficient and accurate means for fusing sensor data and using this fused data to control sensors to focus on areas that would most reduce the uncertainty in the sensing system.

An executing unit is configured to execute at least one of control of operating performance of a plurality of sensors which monitor different regions around a vehicle and predetermined processing for each of a plurality of output values output from the plurality of sensors. A specifying unit is configured to specify a direction of the vehicle with respect to a reference direction set on the basis of a road around the vehicle. A setting unit is configured to set priorities of the plurality of sensors in accordance with the direction of the vehicle specified by the specifying unit. The executing unit changes at least one of ratios of the operating performance of the plurality of sensors and ratios of amounts of processing performed for the plurality of output values on the basis of the priorities.

A control system for a hybrid vehicle which includes an internal combustion engine and an electric motor and whose drive mode is switchable between an electric vehicle mode and a hybrid vehicle mode includes: an on-board learning unit mounted on the hybrid vehicle and configured to perform a learning action; a position determination unit configured to determine whether the hybrid vehicle is located in a low emission area where operation of the internal combustion engine is supposed to be restricted; and a learning control unit configured to at least partially stop the learning action of the on-board learning unit when determination is made that the hybrid vehicle is located in the low emission area.

Systems and methods for determining object prioritization and predicting future object locations for an autonomous vehicle are provided. A method can include obtaining, by a computing system comprising one or more processors, state data descriptive of at least a current or past state of a plurality of objects that are perceived by an autonomous vehicle. The method can further include determining, by the computing system, a priority classification for each object in the plurality of objects based at least in part on the respective state data for each object. The method can further include determining, by the computing system, an order at which the computing system determines a predicted future state for each object based at least in part on the priority classification for each object and determining, by the computing system, the predicted future state for each object based at least in part on the determined order.

A method for reproducing an error that occurs during the driving operation of a vehicle is provided. The vehicle is fixed in position in order to prevent movement relative to a reference surface on which the vehicle is located. A speed profile provided by an engine analyzer is read into a control device of the vehicle and is converted by the control device into a load profile. Subsequently, with the brake activated, the control device in the vehicle automatically runs through the speed profile, the device having converted the speed profile into at least one control parameter of the engine and/or the transmission over time in order to simulate the load profile, when the vehicle is under load as a result of the activation of the brake.

A method of controlling engine on of a hybrid vehicle, may include determining, by a controller, a shift pattern of the vehicle between multiple regions; deriving, by the controller, a shifting possibility of the vehicle from each of the regions; and deriving an engine-on strategy of the vehicle on the basis of the derived shifting possibility, and controlling an engine of the vehicle to be on or off in accordance with the derived engine-on strategy.