Abstract: A system, comprising a computer that includes a processor and a memory, the memory storing instructions executable by the processor to detect and locate an object by processing video camera data with a capsule network, wherein training the capsule network includes determining routing coefficients with a scale-invariant normalization function. The computer can be further programmed to receive the detected and located object.

Abstract: A system, comprising a computer that includes a processor and a memory, the memory storing instructions executable by the processor to detect and locate an object by processing video camera data with a capsule network, wherein training the capsule network includes determining routing coefficients with a scale-invariant normalization function. The computer can be further programmed to receive the detected and located object.

Abstract: A system, comprising a computer that includes a processor and a memory, the memory storing instructions executable by the processor to detect, classify and locate an object by processing video camera data with a capsule network, wherein training the capsule network includes saving routing coefficients. The computer can be further programmed to receive the detected, classified, and located object.

Abstract: Vehicles can be equipped to operate in both autonomous and occupant piloted mode. While operating in either mode, an array of sensors can be used to pilot the vehicle including stereo cameras and 3D sensors. Stereo camera and 3D sensors can also be employed to assist occupants while piloting vehicles. Deep convolutional neural networks can be employed to determine estimated depth maps from stereo images of scenes in real time for vehicles in autonomous and occupant piloted modes.

Abstract: A system is provided with a memory device and a processor. The memory device is adapted to store data representative of a multi-valued decision diagram (MDD) specifying a buildable space of all possible configurations of a vehicle. The processor is in communication with the memory and is programmed to identify an invalid configuration, and to generate a restricted buildable space, including to determine an edit distance of each complete path indicative of a number of features to change the invalid configuration of that path to one of the valid configurations, identify a minimum of the edit distances, and remove configurations having edit distances larger than the minimum. The processor is further programmed to identify at least one feature to change the invalid configuration to at least one valid configuration based on the restricted buildable space; and to generate output indicative of the at least one feature to change.

Abstract: A system is provided with a memory device adapted to store at least one multi-valued decision diagram (MDD) that specifies a total buildable space and a processor that is programmed to identify a partial configuration; generate a restricted buildable space of the total buildable space; and identify families to complete. The processor is further programmed to, for each family to complete in priority order, add any available standard features for the family to a possible set, if the possible set is empty, add a domain space of the family to the possible set, select the highest priority feature of the possible set as a Default feature state, and generate a further restricted buildable space of the total buildable space based on the Default feature state. The processor is also further programmed to generate a complete configuration including features having Default feature states for each family to complete.

Abstract: Vehicles can be equipped to operate in both autonomous and occupant piloted mode. While operating in either mode, an array of sensors can be used to pilot the vehicle including stereo cameras and 3D sensors. Stereo camera and 3D sensors can also be employed to assist occupants while piloting vehicles. Deep convolutional neural networks can be employed to determine estimated depth maps from stereo images of scenes in real time for vehicles in autonomous and occupant piloted modes.

Abstract: A method or system that receives a product definition that includes a feature family having data defining one or more product features. The product definition including one or more corresponding rules defining one or more relationships between one or more product features. The method or system receiving input selecting one or more feature families of interest. The method or system identifying the one or more rules that provide a relationship connecting the one or more feature families to the selected feature families of interest. The method or system converting the identified rules to one or more positive logic rule groups. The method or system generating one or more global representations of the product definition by interacting the one or more positive logic rule groups to produce a result that defines the relationship between the interacted positive logic rule groups and storing the results that are determined as being valid.

Abstract: A method or system that receives a product definition that includes a feature family having data defining one or more product features. The product definition including one or more corresponding rules defining one or more relationships between one or more product features. The method or system receiving input selecting one or more feature families of interest. The method or system identifying the one or more rules that provide a relationship connecting the one or more feature families to the selected feature families of interest. The method or system converting the identified rules to one or more positive logic rule groups. The method or system generating one or more global representations of the product definition by interacting the one or more positive logic rule groups to produce a result that defines the relationship between the interacted positive logic rule groups and storing the results that are determined as being valid.

Abstract: A system is provided with a memory device adapted to store at least one multi-valued decision diagram (MDD) that specifies a total buildable space and a processor that is programmed to identify a partial configuration; generate a restricted buildable space of the total buildable space; and identify families to complete. The processor is further programmed to, for each family to complete in priority order, add any available standard features for the family to a possible set, if the possible set is empty, add a domain space of the family to the possible set, select the highest priority feature of the possible set as a Default feature state, and generate a further restricted buildable space of the total buildable space based on the Default feature state. The processor is also further programmed to generate a complete configuration including features having Default feature states for each family to complete.

Abstract: A system is provided with a memory device and a processor. The memory device is adapted to store data representative of a multi-valued decision diagram (MDD) specifying a buildable space of all possible valid configurations of a vehicle. The processor is in communication with the memory and is programmed to identify an invalid configuration, and to generate a restricted buildable space, including to determine an edit distance of each complete path indicative of a number of features to change the invalid configuration of that path to one of the valid configurations, identify a minimum of the edit distances, and remove configurations having edit distances larger than the minimum. The processor is further programmed to identify at least one feature to change the invalid configuration to at least one valid configuration based on the restricted buildable space; and to generate output indicative of the at least one feature to change.

Abstract: A server comprising a transceiver configured to communicate data with a remote vehicle computer system and a car-reservation system. The server further includes a processor configured to utilize the data to output a car-sharing social-graph, the car-sharing social-graph including a vehicle for sharing, a vehicle-location, a user-location, and a potential parking-spot for sharing the vehicle.

Abstract: A method or system that receives a product definition that includes a feature family having data defining one or more product features. The product definition including one or more corresponding rules defining one or more relationships between one or more product features. The method or system receiving input selecting one or more feature families of interest. The method or system identifying the one or more rules that provide a relationship connecting the one or more feature families to the selected feature families of interest. The method or system converting the identified rules to one or more positive logic rule groups. The method or system generating one or more global representations of the product definition by interacting the one or more positive logic rule groups to produce a result that defines the relationship between the interacted positive logic rule groups and storing the results that are determined as being valid.

Abstract: A computer-implemented method or system that is capable of configuring a product. The computer-implemented method or system receiving a product configuration matrix from a computer storage medium. The computer-implemented method or system also receiving user input defining a user selection of at least one feature or component of the product. The computer-implemented method or system generating a binary representation of the user selection. The computer-implemented method or system deriving a resolution matrix. The method or system comparing the resolution matrix and the binary representation of the user selection to determine whether one or more of the selected product features or components in the user selection are valid for the product. The computer-implemented method or system also generating a validation result that identifies one or more valid product features or components within the user selection.

Abstract: A method or system that receives a product definition that includes a feature family having data defining one or more product features. The product definition including one or more corresponding rules defining one or more relationships between one or more product features. The method or system receiving input selecting one or more feature families of interest. The method or system identifying the one or more rules that provide a relationship connecting the one or more feature families to the selected feature families of interest. The method or system converting the identified rules to one or more positive logic rule groups.

Abstract: A method or system that receives a product definition that includes a feature family having data defining one or more product features. The product definition including one or more corresponding rules defining one or more relationships between one or more product features. The method or system receiving input selecting one or more feature families of interest. The method or system identifying the one or more rules that provide a relationship connecting the one or more feature families to the selected feature families of interest. The method or system converting the identified rules to one or more positive logic rule groups.

Abstract: A method or system that receives a product definition that includes a feature family having data defining one or more product features. The product definition including one or more corresponding rules defining one or more relationships between one or more product features. The method or system receiving input selecting one or more feature families of interest. The method or system identifying the one or more rules that provide a relationship connecting the one or more feature families to the selected feature families of interest. The method or system converting the identified rules to one or more positive logic rule groups. The method or system generating one or more global representations of the product definition by interacting the one or more positive logic rule groups to produce a result that defines the relationship between the interacted positive logic rule groups and storing the results that are determined as being valid.

Abstract: A computer-implemented method or system that is capable of configuring a product. The computer-implemented method or system receiving a product configuration matrix from a computer storage medium. The computer-implemented method or system also receiving user input defining a user selection of at least one feature or component of the product. The computer-implemented method or system generating a binary representation of the user selection. The computer-implemented method or system deriving a resolution matrix. The method or system comparing the resolution matrix and the binary representation of the user selection to determine whether one or more of the selected product features or components in the user selection are valid for the product. The computer-implemented method or system also generating a validation result that identifies one or more valid product features or components within the user selection.

Abstract: A data store includes, for a dealer of interest, a target inventory mix rate for an item having a feature. A computing device is configured to perform an optimization to obtain a recommended feature allocation of the item including the feature by minimizing a difference between a projected inventory mix rate for the feature and the target inventory mix rate for the feature.

Abstract: A computer-implemented method or system that is capable of configuring a product. The computer-implemented method or system receiving a product configuration matrix from a computer storage medium. The computer-implemented method or system also receiving user input defining a user selection of at least one feature or component of the product. The computer-implemented method or system generating a binary representation of the user selection. The computer-implemented method or system deriving a resolution matrix. The method or system comparing the resolution matrix and the binary representation of the user selection to determine whether one or more of the selected product features or components in the user selection are valid for the product. The computer-implemented method or system also generating a validation result that identifies one or more valid product features or components within the user selection.