Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: The present technology can detect potential labeling conflicts made during different labeling tasks when those tasks are checked in to ensure that a map database is free from conflicts that might interrupt publishing of a map. The present technology can determine whether a first labeled version of map portion is based on a most recent version for the map portion that is stored in the map database, and when it is determined that it is not, and there is an intervening version, the present technology can identify differences between the intervening version of the map portion and the first version of the map portion and identify differences between the second version of the map portion and the first version of the map portion. Based on the identified differences, the present technology can determine whether any of those differences are conflicting.

Abstract: Systems and methods for map simulation testing are provided. A method includes receiving, by a computer-implemented system, information associated with an operational design domain (ODD); generating, by the computer-implemented system based at least in part on the information associated with the ODD, a plurality of map test cases for a map representative of a geographical area in the ODD, where each map test case of the plurality of map test cases includes one of a plurality of paths in the geographical area; evaluating a vehicle planning process in navigating through one or more of the plurality of paths corresponding to one or more of the plurality of map test cases; and determining a metric for the map based on the evaluating.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Systems and methods provide for routing an autonomous vehicles based on an assessment of its limitations. The autonomous vehicle can avoid problematic routes by applying a set of rules to a map, where the set of rules are associated with a feature that causes a failure of the autonomous vehicle due to an autonomous vehicle limitation. Based on the application of the set of rules, a portion of a route on the map that is associated with the feature can be identified, and an identifier can be applied to the identified portion of the route associated with the feature on a routing map. The portion of the route can be omitted from a routable graph applied to the routing map, such that the route for the autonomous vehicle is generated in accordance with the routable graph.

Abstract: Systems and methods provide for routing autonomous vehicles by simulating an autonomous vehicle traversing a route on a map representing a physical area. A router flag can be generated at a specific location on the map. A router flag rule that defines a factor that caused a failure of the autonomous vehicle can then be created at the location, and the autonomous vehicle can be simulated traversing the to identify at least one other area on the map where the autonomous vehicle is likely to fail. An identifier can be applied to the other area on the map where the autonomous vehicle is likely to fail according to the router flag rule. The other area with the applied identifier can be omitted from a routable graph applied to the routing map, such that the route for the autonomous vehicle is generated in accordance with the routable graph.

Abstract: The present technology provides a system that can update aspects of an authoritative map portion stored on an autonomous vehicle using low-resolution data from the at least one sensor of the autonomous vehicle, and therefore avoids the need for dispatching the special purpose mapping vehicle for these updates. The captured low-resolution data can be compared with the high-resolution map portion to determine that the sensor data reflects a feature in a way that is inconsistent with how that feature is represented in the authoritative map portion. The sensor data can then be used to relabel the authoritative map portion.

Abstract: The present technology provides a system that can update aspects of an authoritative map portion stored on an autonomous vehicle using low-resolution data from the at least one sensor of the autonomous vehicle, and therefore avoids the need for dispatching the special purpose mapping vehicle for these updates. The captured low-resolution data can be compared with the high-resolution map portion to determine that the sensor data reflects a feature in a way that is inconsistent with how that feature is represented in the authoritative map portion. The sensor data can then be used to relabel the authoritative map portion.

Abstract: The present technology can detect potential labeling conflicts made during different labeling tasks when those tasks are checked in to ensure that a map database is free from conflicts that might interrupt publishing of a map. The present technology can determine whether a first labeled version of map portion is based on a most recent version for the map portion that is stored in the map database, and when it is determined that it is not, and there is an intervening version, the present technology can identify differences between the intervening version of the map portion and the first version of the map portion and identify differences between the second version of the map portion and the first version of the map portion. Based on the identified differences, the present technology can determine whether any of those differences are conflicting.

Abstract: Systems and methods provide for routing autonomous vehicles by simulating an autonomous vehicle traversing a route on a map representing a physical area. A router flag can be generated at a specific location on the map. A router flag rule that defines a factor that caused a failure of the autonomous vehicle can then be created at the location, and the autonomous vehicle can be simulated traversing the to identify at least one other area on the map where the autonomous vehicle is likely to fail. An identifier can be applied to the other area on the map where the autonomous vehicle is likely to fail according to the router flag rule. The other area with the applied identifier can be omitted from a routable graph applied to the routing map, such that the route for the autonomous vehicle is generated in accordance with the routable graph.

Abstract: Systems and methods provide for routing an autonomous vehicles based on an assessment of its limitations. The autonomous vehicle can avoid problematic routes by applying a set of rules to a map, where the set of rules are associated with a feature that causes a failure of the autonomous vehicle due to an autonomous vehicle limitation. Based on the application of the set of rules, a portion of a route on the map that is associated with the feature can be identified, and an identifier can be applied to the identified portion of the route associated with the feature on a routing map. The portion of the route can be omitted from a routable graph applied to the routing map, such that the route for the autonomous vehicle is generated in accordance with the routable graph.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: The present technology provides a system that can update aspects of an authoritative map portion stored on an autonomous vehicle using low-resolution data from the at least one sensor of the autonomous vehicle, and therefore avoids the need for dispatching the special purpose mapping vehicle for these updates. The captured low-resolution data can be compared with the high-resolution map portion to determine that the sensor data reflects a feature in a way that is inconsistent with how that feature is represented in the authoritative map portion. The sensor data can then be used to relabel the authoritative map portion.

Abstract: A heat exchanger assembly and a hot water appliance including a heat exchanger and a burner assembly. The heat exchanger assembly includes a head portion including a water inlet for receiving water at a first temperature, a water outlet for outputting water at a second temperature higher than the first temperature, and a gas inlet port for receiving combustion gases. The heat exchanger assembly also includes a tube bundle including a plurality of combustion chamber tubes positioned about the gas inlet port, and a plurality of condensation chamber tubes positioned adjacent and parallel to the plurality of combustion chamber tubes. Each combustion chamber tube has a first surface shape and each condensation chamber tube has a second surface shape that is different than the first surface shape.

Abstract: A system and method to provide financial products throughout the life of a customer. The present invention determines the life status of a customer. The life status is determined by analyzing the customer information from a variety of sources. This information is filtered or inputted into an algorithmic model to identify appropriate financial products to offer to the customer. In addition, the customer's creditworthiness is used to determine or optimize the financial product offered to the customer.

Abstract: A system and method to provide financial products throughout the life of a customer. The present invention determines the life status of a customer. The life status is determined by analyzing the customer information from a variety of sources. This information is filtered or inputted into an algorithmic model to identify appropriate financial products to offer to the customer. In addition, the customer's creditworthiness is used to determine or optimize the financial product offered to the customer.

Abstract: Defined benefit pension plans wherein an accrued benefit is capable of satisfying accrual rules of Internal Revenue Code Section 411(b)(1) using the 133 ?% rule of subparagraph B, that incorporate particular pension plan design components, and methods for reducing exposure to civil liability based on provisions of the Employee Retirement Income Security Act (ERISA) and/or the Internal Revenue Code (IRC) relating to age discrimination that is associated with funding defined benefit pension plans, including cash balance plans, by employing the novel plan designs.

Abstract: A system and method to provide financial products throughout the life of a customer. The present invention determines the life status of a customer. The life status is determined by analyzing the customer information from a variety of sources. This information is filtered or inputted into an algorithmic model to identify appropriate financial products to offer to the customer. In addition, the customer's creditworthiness is used to determine or optimize the financial product offered to the customer.