B60W40/064

Determining surface characteristics

A method for determining surface characteristics is disclosed. The method may include transmitting a surface penetrating radar (SPR) signal towards a surface from a SPR system. The method may also include receiving a response signal at the SPR system. The response signal may include, at least in part, a reflection of the SPR signal from a surface region associated with the surface. The method may further include measuring at least one of an intensity and a phase of the response signal. The method my additionally include determining, based at least in part on the at least one of the intensity and the phase of the response signal, a surface characteristic of the surface.

Method and device for determining a quality of a surface in the surroundings of a transportation vehicle

A method for determining a quality of a surface in the surroundings of a transportation vehicle, wherein three-dimensional surface coordinates of the surface are generated using a sensor assembly. In the method, an approximation of the course of the curvature of the surface in at least one direction is obtained based on the surface coordinates and the surface coordinates are classified to characterize the quality of the surface using the course of the curvature and/or vertical distances of the approximation of the course of the curvature from the three-dimensional surface coordinates. A device for carrying out the method.

INFORMATION PROCESSING SYSTEM, PROGRAM, AND INFORMATION PROCESSING METHOD

An information processing system includes one or more vehicles, and a server communicable with the one or more vehicles. The vehicle acquires an image obtained by imaging a road on which a host vehicle is located. The vehicle or the server determines a degree of difficulty in traveling on the road due to snow cover from the image. The server stores the degree of difficulty in traveling for each of one or more roads, and provides information to a client by using the stored degree of difficulty in traveling for each of one or more roads.

INFORMATION PROCESSING SYSTEM, PROGRAM, AND INFORMATION PROCESSING METHOD

An information processing system includes one or more vehicles, and a server communicable with the one or more vehicles. The vehicle acquires an image obtained by imaging a road on which a host vehicle is located. The vehicle or the server determines a degree of difficulty in traveling on the road due to snow cover from the image. The server stores the degree of difficulty in traveling for each of one or more roads, and provides information to a client by using the stored degree of difficulty in traveling for each of one or more roads.

OPERATING A SUPPLY CHAIN USING CAUSAL MODELS

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing operations of a supply chain. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for operating a supply chain, based on a causal model that measures causal relationships between input settings and a measure of success of the supply chain; ii) determining the measure of success of the supply chain operated using the configuration of input settings; and iii) adjusting, based on the measure of success of the supply chain operated using the configuration of input settings, the causal model.

OPERATING A SUPPLY CHAIN USING CAUSAL MODELS

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing operations of a supply chain. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for operating a supply chain, based on a causal model that measures causal relationships between input settings and a measure of success of the supply chain; ii) determining the measure of success of the supply chain operated using the configuration of input settings; and iii) adjusting, based on the measure of success of the supply chain operated using the configuration of input settings, the causal model.

DETERMINING CAUSAL MODELS FOR CONTROLLING ENVIRONMENTS

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes obtaining data specifying baseline probability distributions for each of a plurality of controllable elements; maintaining a causal model; repeatedly performing the following: selecting control settings for the environment based on the causal model and values for a particular internal parameter of the control system that are sampled from a range of possible values; selecting control settings for the environment based on the baseline probability distributions; monitoring environment responses to the control settings selected based on the causal model and the control settings selected based on the baseline probability distributions; determining, for each of the possible values, a measure of a difference between a current system performance and a baseline system performance; and updating how frequently each of the possible values is sampled.

DETERMINING CAUSAL MODELS FOR CONTROLLING ENVIRONMENTS

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes obtaining data specifying baseline probability distributions for each of a plurality of controllable elements; maintaining a causal model; repeatedly performing the following: selecting control settings for the environment based on the causal model and values for a particular internal parameter of the control system that are sampled from a range of possible values; selecting control settings for the environment based on the baseline probability distributions; monitoring environment responses to the control settings selected based on the causal model and the control settings selected based on the baseline probability distributions; determining, for each of the possible values, a measure of a difference between a current system performance and a baseline system performance; and updating how frequently each of the possible values is sampled.

METHOD OF OPTIMIZING CONTROL SIGNALS USED IN OPERATING VEHICLE

A method of optimizing a plurality of control signals used in operating a vehicle is described. The operation has a plurality of associated measurable parameters. The method includes: for each control signal, selecting a plurality of potential optimum values from a predetermined set; operating the vehicle in at least a first sequence of operation iterations, where for each pair of sequential first and second operation iterations in the first sequence of operation iterations, the potential optimum value of one control signal in the first operation iteration is replaced in the second operation iteration with a next potential optimum value of the control signal, while the potential optimum values of the remaining control signals are maintained; for each operation iteration, measuring each parameter in the plurality of measurable parameters; and generating confidence intervals for the control signals to determine causal relationships between the control signals and the measurable parameters.

METHOD OF OPTIMIZING CONTROL SIGNALS USED IN OPERATING VEHICLE

A method of optimizing a plurality of control signals used in operating a vehicle is described. The operation has a plurality of associated measurable parameters. The method includes: for each control signal, selecting a plurality of potential optimum values from a predetermined set; operating the vehicle in at least a first sequence of operation iterations, where for each pair of sequential first and second operation iterations in the first sequence of operation iterations, the potential optimum value of one control signal in the first operation iteration is replaced in the second operation iteration with a next potential optimum value of the control signal, while the potential optimum values of the remaining control signals are maintained; for each operation iteration, measuring each parameter in the plurality of measurable parameters; and generating confidence intervals for the control signals to determine causal relationships between the control signals and the measurable parameters.