A method for analyzing the distribution of energy expenditures of a motor vehicle from data from a communications network and from parameters of the vehicle includes steps in which the energy expenditures of the vehicle over a journey are calculated, the said energy expenditures are analyzed by comparing them with at least one model of the vehicle simulating the same journey, an energy balance report is formulated on the basis of the analysis of the energy expenditures and of the fuel consumption and the said energy balance report is communicated to an external server.

An angular speed acquisition device acquires the angular speed about a road surface perpendicular axis of a leaning vehicle. The leaning vehicle includes a vehicle body frame capable of leaning in a vehicle left-right direction and a steering shaft which steers at least one of a front wheel unit and a rear wheel unit. An angular speed acquisition device, which is mountable on the leaning vehicle, includes a memory and a processor. The memory stores the relationship between the steering angle, which is a rotation angle about the rotational axis of the steering shaft, the vehicle speed of the leaning vehicle, and the angular speed ω about the road surface perpendicular axis.

A vehicle control apparatus includes an inverter controller. The inverter controller holds a plurality of control maps for an inverter. The inverter supplies electric power to a drive motor. The drive motor drives a drive wheel of the vehicle. The inverter controller selects any one of the plurality of control maps on a basis of a notification instruction that instructs to notify a driver of information. The inverter controller controls an operation of the inverter on a basis of the control map selected.

A system comprising a computer including a processor and a memory, the memory including instructions such that the processor is programmed to: determine whether a difference between a friction coefficient label and a determined friction coefficient corresponding to an image depicting a surface is greater than a label threshold; modify the determined friction coefficient to equal the friction coefficient label when the difference is greater than the label threshold; and retrain a neural network using the image and the friction coefficient label.

A method of curve speed adjustment for a road vehicle includes obtaining data on: current ego velocity; distance and curvature of an upcoming road segment, represented by a set of control points to be negotiated; road property of a road comprising the road segment; environmental properties; and driver properties. The obtained data is continuously streamed to a data processing arrangement arranged to perform a translation to target velocities for the respective control points and, for each respective control point, a translation from target velocity for that control point and distance to that control point and obtained current ego velocity, to a target acceleration to reach that control point at its target velocity. The resulting target accelerations are continuously streamed to a control unit of the road vehicle to adjust the road vehicle acceleration to reach each respective control point at its target velocity.

The invention provides a method for controlling a vehicle (1) comprising a drivetrain comprising at least one drive device (2) adapted to generate mechanical power, the method comprising—controlling the vehicle to perform a mission comprising a plurality of stages (MS1-MS12), —collecting operational data relevant to the operation of the drivetrain, wherein the operational data indicate a de-rate of a component of the drivetrain, a fault of a component of the drivetrain, and/or an environmental condition which influences the drivetrain operation, —determining an expected mission stage (MS1-MS12), —determining, in dependence on the operational data, the propulsive capacity (CA1-CA3) in at least two different operational areas (A1-A3) of the drive device (2), —mapping the operational area propulsive capacities (CA1-CA3) to the expected mission stage (MS1-MS12), and—controlling the vehicle (1) in dependence on said mapping.

A system, method, and computer-readable medium having instructions stored thereon to enable an ego vehicle having an autonomous driving function to estimate and traverse a curved segment of highway utilizing radar sensor data. The radar sensor data may comprise stationary reflections and moving reflections. The ego vehicle may utilize other data, such as global positioning system data, for the estimation and traversal. The estimation of the curvature may be refined based upon a lookup table or a deep neural network.

An imaging section 20 images a passenger in a moving body. A boarding state detection section 30 detects a boarding state of the passenger on the basis of a captured image acquired by the imaging section 20. An allowable acceleration setting section 40 sets, for each passenger, individual allowable acceleration on the basis of the boarding state of the passenger detected by the boarding state detection section 30, for example, the lateral spacing between the feet of the passenger, the arrangement angle of the feet with respect to the moving direction of the moving body, and the like. Further, integration is performed on the individual allowable acceleration determined for the respective passengers in the moving body, and the acceleration that is allowable for the moving body is set. The allowable acceleration for the moving body is set according to the boarding state of each passenger, thus preventing the moving body from moving at acceleration at which the passengers may be endangered. This allows the safety of the passengers to be improved.

Enclosed are embodiments for scenario-based behavior specification and validation. In an embodiment, a method comprises: obtaining, using at least one processor, at least one trajectory associated with a driving scenario for an autonomous vehicle system; evaluating, using the at least one processor and at least one rulebook, the at least one trajectories to determine whether the at least one trajectory violates at least one rule in the at least one rulebook, wherein each rule in the rulebook is associated with at least one violation metric that is used to determine a degree to which the rule was satisfied or violated; determining, using the at least one processor and the at least one violation metric, a score for the at least one trajectory; and sending, using the at least one processor, the score to at least one of a software module in a software stack of the autonomous vehicle system, a simulation of the autonomous vehicle system or as a report or in a visual presented through a user interface of a cloud-based platform.

A power distribution control system of a vehicle includes a driving information provider for collecting and providing information required for power distribution control of an engine and a motor in the vehicle; a communication unit for transmitting the information provided by the driving information provider from the vehicle; a cloud server outside the vehicle for selecting and transmitting optimal power distribution control logic data corresponding to a driving situation of the vehicle based on the information provided through the communication unit from the vehicle; and a vehicle controller for performing power distribution control of the engine and the motor based on real-time driving state variable information of the vehicle using the optimal power distribution control logic data received through the communication unit by the vehicle from the cloud server.