Abstract: The disclosure provides a method, a device, an apparatus, and a storage medium for identifying a type of atmospheric aerosol. The method includes: determining a depolarization ratio and an aerosol extinction coefficient of an atmospheric area to be identified according to a lidar signal and a relative humidity profile of the area; identifying a cloud type of the area according to the signal and the profile; and identifying a type of an atmospheric aerosol in the area based on the cloud type, the ratio and the coefficient. Relevant values are calculated based on lidar signals and the profile, clouds are identified first, and then different types of aerosols are further distinguished in combination with the relevant values, and a numerical determination standard is given to synchronously identify different types of aerosols including types of cloud, fog and other particulates in the atmosphere, thereby improving accuracy of identification.

Abstract: Vehicles, methods, and computer readable storage media are provided for providing transportation of a gesturing pedestrian by an autonomous vehicle. The vehicle can be operated by identifying that an individual is interested in receiving a transportation. A second vehicle can then receive information about the individual that is interested in receiving the transportation. The first vehicle is then informed regarding the second vehicle.

Abstract: Apparatuses, methods, and computer readable storage media are provided for autonomously reporting road conditions. The apparatus can be operated by using one or more sensors by a detecting vehicle to detect a road condition. A computer can then identify the road condition using a component and generating a road condition information. The computer can then determine an effect of the road condition on other vehicles and determine a subset of the other vehicles that will be affected by the road condition. The computer can then transmit the road condition information such that the road condition information is receivable by the subset of other vehicles.

Abstract: Location of an autonomous driving vehicle (ADV) is determined with respect to a high definition map. On-boards sensors of the ADV obtain a 3D point cloud of objects surrounding the ADV. The 3D point cloud is organized into an ADV feature space of cells. Each cell has a median intensity value and a variance in elevation. To determine the ADV location, a coarse search of a subset of cells in the ADV feature space performed with respect to the high definition map, using a similarity metric that is based on the median intensity and variance in elevation of the candidate cell. When similarity of the first candidate cell is determined, a lookup table of similarity scores is generated and used for determining the similarity score for subsequent candidate cells. Then a fine search is performed on a small subset of candidate cells surrounding the highest similarity score cell.

Abstract: Vehicles, methods, and computer readable storage media are provided for providing transportation of a gesturing pedestrian by an autonomous vehicle. The vehicle can be operated by identifying that an individual is interested in receiving a transportation. A second vehicle can then receive information about the individual that is interested in receiving the transportation. The first vehicle is then informed regarding the second vehicle.

Abstract: Apparatuses, methods, and computer readable storage media are provided for autonomously reporting road conditions. The apparatus can be operated by using one or more sensors by a detecting vehicle to detect a road condition. A computer can then identify the road condition using a component and generating a road condition information. The computer can then determine an effect of the road condition on other vehicles and determine a subset of the other vehicles that will be affected by the road condition. The computer can then transmit the road condition information such that the road condition information is receivable by the subset of other vehicles.

Abstract: Described is a system that matches a query with a set of sentences. When a query is received, the system may extract features from the query including one or more words as tokens and retrieve a set of candidate sentences as potential results for the query. For example, the query may be in the form of a question, and the candidate sentences may be alternative phrasings of the query that potentially match the user's search intent. The relevant set of candidate sentences may be determined based on using multiple relevancy scores and the system may rank the candidates according to an overall or aggregate score. Accordingly, the set of results to a query may be provided by recognizing the sentence as a whole and, for example when the query is a question, the interrogative intent of the query.

Abstract: Location of an autonomous driving vehicle (ADV) is determined with respect to a high definition map. On-boards sensors of the ADV obtain a 3D point cloud of objects surrounding the ADV. The 3D point cloud is organized into an ADV feature space of cells. Each cell has a median intensity value and a variance in elevation. To determine the ADV location, a coarse search of a subset of cells in the ADV feature space performed with respect to the high definition map, using a similarity metric that is based on the median intensity and variance in elevation of the candidate cell. When similarity of the first candidate cell is determined, a lookup table of similarity scores is generated and used for determining the similarity score for subsequent candidate cells. Then a fine search is performed on a small subset of candidate cells surrounding the highest similarity score cell.

Abstract: Systems and methods are disclosed for question generation to infer the most probable cause from the observable outcome and known Noisy-OR causal relations. In embodiments, the outcomes are sorted by indices according to an order including but not limited to the outcomes' natural frequency order, expert-labeled order, machine-learning derived order, etc. According to their assigned indices, in embodiments, observed outcomes with lower indices are assigned for exact inference while observed outcomes with higher indices are assigned for variational inference. In embodiments, results of exact inference and variational inference are combined to predict the most probable cause. The unique combination of exact inference and variational inference according to outcome indices makes the probable cause inferring process faster.

Abstract: Location of an autonomous driving vehicle (ADV) is determined with respect to a high definition map. On-boards sensors of the ADV obtain a 3D point cloud of objects surrounding the ADV. The 3D point cloud is organized into an ADV feature space of cells. Each cell has a median intensity value and a variance in elevation. To determine the ADV location, a coarse search of a subset of cells in the ADV feature space performed with respect to the high definition map, using a similarity metric that is based on the median intensity and variance in elevation of the candidate cell. When similarity of the first candidate cell is determined, a lookup table of similarity scores is generated and used for determining the similarity score for subsequent candidate cells. Then a fine search is performed on a small subset of candidate cells surrounding the highest similarity score cell.

Abstract: Systems and methods are disclosed for extending and reinforcing a knowledge graph using wiki-like web pages as a source of information. A web crawler parse a wiki-like source and obtain a topic entity from the source. Relationships between the topic entity and sub-topics within the source are identified and a graph is built with the topic and relationships to sub-topics. A candidate topic in the knowledge graph is identified, and a sub-graph of the knowledge graph is either identified or generated. The knowledge sub-graph contains the candidate topic and relationships to sub-topics. A similarity is computed between the source graph and the knowledge sub-graph. If the two graphs are sufficiently similar, then the source topic graph is merged with the knowledge graph.

Abstract: Location of an autonomous driving vehicle (ADV) is determined with respect to a high definition map. On-boards sensors of the ADV obtain a 3D point cloud of objects surrounding the ADV. The 3D point cloud is organized into an ADV feature space of cells. Each cell has a median intensity value and a variance in elevation. To determine the ADV location, a coarse search of a subset of cells in the ADV feature space performed with respect to the high definition map, using a similarity metric that is based on the median intensity and variance in elevation of the candidate cell. When similarity of the first candidate cell is determined, a lookup table of similarity scores is generated and used for determining the similarity score for subsequent candidate cells. Then a fine search is performed on a small subset of candidate cells surrounding the highest similarity score cell.

Abstract: Systems and methods are disclosed for extending and reinforcing a knowledge graph using wiki-like web pages as a source of information. A web crawler parse a wiki-like source and obtain a topic entity from the source. Relationships between the topic entity and sub-topics within the source are identified and a graph is built with the topic and relationships to sub-topics. A candidate topic in the knowledge graph is identified, and a sub-graph of the knowledge graph is either identified or generated. The knowledge sub-graph contains the candidate topic and relationships to sub-topics. A similarity is computed between the source graph and the knowledge sub-graph. If the two graphs are sufficiently similar, then the source topic graph is merged with the knowledge graph.

Abstract: Described is a system that matches a query with a set of sentences. When a query is received, the system may extract features from the query including one or more words as tokens and retrieve a set of candidate sentences as potential results for the query. For example, the query may be in the form of a question, and the candidate sentences may be alternative phrasings of the query that potentially match the user's search intent. The relevant set of candidate sentences may be determined based on using multiple relevancy scores and the system may rank the candidates according to an overall or aggregate score. Accordingly, the set of results to a query may be provided by recognizing the sentence as a whole and, for example when the query is a question, the interrogative intent of the query.

Abstract: Systems and methods are disclosed for question generation to infer the most probable cause from the observable outcome and known Noisy-OR causal relations. In embodiments, the outcomes are sorted by indices according to an order including but not limited to the outcomes' natural frequency order, expert-labeled order, machine-learning derived order, etc. According to their assigned indices, in embodiments, observed outcomes with lower indices are assigned for exact inference while observed outcomes with higher indices are assigned for variational inference. In embodiments, results of exact inference and variational inference are combined to predict the most probable cause. The unique combination of exact inference and variational inference according to outcome indices makes the probable cause inferring process faster.