Methods and systems are provided for using energy harvesting modules as a means for providing energy to power an electrical load and/or as a means for monitoring an operational state of a component or components to which the energy harvesting module is coupled. In one example, a method includes, via a controller, monitoring an actual amount of energy generated by an energy harvesting module attached to a mounting structure that is used to secure a torque-supplying machine to a frame, comparing the actual amount to an expected amount, and indicating degradation of the mounting structure and/or the torque-supplying machine based on the comparing. In this way, the energy harvesting modules may both power electrical loads and simultaneously serve as a monitor for component degradation.

Systems and methods are provided for estimating travel time and distance. Such method may comprise obtaining a vehicle trip dataset comprising an origin, a destination, a time-of-day, a trip time, and a trip distance associated with each of a plurality of trips, and training a neural network model with the vehicle trip dataset to obtain a trained model. The neural network model may comprise a first module and a second module, the first module may comprise a first number of neuron layers, the first module may be configured to obtain the origin and the destination as first inputs to estimate a travel distance, the second module may comprise a second number of neuron layers, and the second module may be configured to obtain the information of a last layer of the first module and the time-of-day as second inputs to estimate a travel time.

In various examples, sensor data may be adjusted to represent a virtual field of view different from an actual field of view of the sensor, and the sensor data—with or without virtual adjustment—may be applied to a stereographic projection algorithm to generate a projected image. The projected image may then be applied to a machine learning model—such as a deep neural network (DNN)—to detect and/or classify features or objects represented therein.

A transportation vehicle having a navigation system and an operating system connected to the navigation system for data transmission via a bus system. The transportation vehicle has a microphone and includes a phoneme generation module for generating phonemes from an acoustic voice signal or the output signal of the microphone; the phonemes are part of a predefined selection of exclusively monosyllabic phonemes; and a phoneme-to-grapheme module for generating inputs to operate the transportation vehicle based on monosyllabic phonemes generated by the phoneme generation module.

A method for estimating the quality of localization using sensor detection, wherein the vehicle detects dynamic objects on the road and in the direct surroundings of the road and estimates the dimensions of the objects. The movement of these objects in the near future is estimated. The outer casings of these objects are entered into a map of the surroundings. From the perspective of the sensors used to detect the features in the surroundings, the limitations of the fields of view and the predicted temporal development thereof resulting from the movement of the transportation vehicle and the predicted movements of the objects are entered into the map of the surroundings. The surrounding features that have been entered into the map of the surroundings and which may at visible in the near future are determined. An upper limit for a measure of the quality of localization is estimated.

In a mobile station which communicates with a base station corresponding to a serving cell that is a cell in which the mobile station is located, of a plurality of cells, an acquirer is configured to acquire a situation of movement of the mobile station. A changer is configured to change a criterion used to determine whether to switch a communication destination from a first base station corresponding to the serving cell to a second base station corresponding to an adjacent cell neighboring the serving cell, in response to the situation of movement of the mobile station acquired by the acquirer and a positional relationship between the serving cell and the adjacent cell.

The use of multiple horizon optimization for vehicle dynamics and powertrain control of a vehicle is provided. Long horizon optimization for a trip of the vehicle is performed, and an optimal value function is determined. Data is received from powertrain and/or connectivity features from one or more of components of the vehicle. Short horizon optimization for the trip is performed using a rollout algorithm, the optimal value function, and the received data. The operation of the vehicle is adjusted using results of the short horizon optimization.

An information processing apparatus according to an embodiment of the present technology includes a sub-goal arranging unit and a prohibited-area generating unit. The sub-goal arranging unit arranges a sub-goal on the basis of position information of a set destination, map information of a travel environment of a mobile apparatus, and self-position information of the mobile apparatus. The prohibited-area generating unit generates, in at least a portion of a periphery of the destination, a prohibited area where arrangement of the sub-goal is prohibited.

A method for providing data for a driver assistance system of a motor vehicle includes communicating position data concerning a position of the motor vehicle to the driver assistance system, requesting additional information from a server if the driver assistance system requires additional information with respect to the position data, and communicating, in response to the requesting, the additional information from the server to the driver assistance system.

A method for providing data for a driver assistance system of a motor vehicle includes communicating position data concerning a position of the motor vehicle to the driver assistance system, requesting additional information from a server if the driver assistance system requires additional information with respect to the position data, and communicating, in response to the requesting, the additional information from the server to the driver assistance system.