Abstract: According to one embodiment, an apparatus includes an interface to receive sensor data from a plurality of sensors of an autonomous vehicle. The apparatus also includes processing circuitry to apply a sensor abstraction process to the sensor data to produce abstracted scene data, and to use the abstracted scene data in a perception phase of a control process for the autonomous vehicle. The sensor abstraction process may include one or more of: applying a Sensor data response normalization process to the sensor data, applying a warp process to the sensor data, and applying a filtering process to the sensor data.

Abstract: Sensor data is received from a plurality of sensors, where the plurality of sensors includes a first set of sensors and a second set of sensors, and at least a portion of the plurality of sensors are coupled to a vehicle. Control of the vehicle is automated based on at least a portion of the sensor data generated by the first set of sensors. Passenger attributes of one or more passengers within the autonomous vehicles are determined from sensor data generated by the second set of sensors. Attributes of the vehicle are modified based on the passenger attributes and the sensor data generated by the first set of sensors.

Abstract: Embodiments of the present invention relate to elimination of blocks such as splits in distributed processing systems such as MapReduce systems using the Hadoop Distributed Filing System (HDFS). In one embodiment, a method of and computer program product for optimizing queries in distributed processing systems are provided. A query is received. The query includes at least one predicate. The query refers to data. The data includes a plurality of records. Each record comprises a plurality of values in a plurality of attributes. Each record is located in at least one of a plurality of blocks of a distributed file system. Each block has a unique identifier. For each block of the distributed file system, at least one value cluster is determined for an attribute of the plurality of attributes. Each value cluster has a range. The predicate of the query is compared with the at least one value cluster of each block.

Abstract: Embodiments of the present invention relate to elimination of blocks such as splits in distributed processing systems such as MapReduce systems using the Hadoop Distributed Filing System (HDFS). In one embodiment, a method of and computer program product for optimizing queries in distributed processing systems are provided. A query is received. The query includes at least one predicate. The query refers to data. The data includes a plurality of records. Each record comprises a plurality of values in a plurality of attributes. Each record is located in at least one of a plurality of blocks of a distributed file system. Each block has a unique identifier. For each block of the distributed file system, at least one value cluster is determined for an attribute of the plurality of attributes. Each value cluster has a range. The predicate of the query is compared with the at least one value cluster of each block.

Abstract: Embodiments of the present invention relate to elimination of blocks such as splits in distributed processing systems such as MapReduce systems using the Hadoop Distributed Filing System (HDFS). In one embodiment, a method of and computer program product for optimizing queries in distributed processing systems are provided. A query is received. The query includes at least one predicate. The query refers to data. The data includes a plurality of records. Each record comprises a plurality of values in a plurality of attributes. Each record is located in at least one of a plurality of blocks of a distributed file system. Each block has a unique identifier. For each block of the distributed file system, at least one value cluster is determined for an attribute of the plurality of attributes. Each value cluster has a range. The predicate of the query is compared with the at least one value cluster of each block.

Abstract: Embodiments of the present invention relate to elimination of blocks such as splits in distributed processing systems such as MapReduce systems using the Hadoop Distributed Filing System (HDFS). In one embodiment, a method of and computer program product for optimizing queries in distributed processing systems are provided. A query is received. The query includes at least one predicate. The query refers to data. The data includes a plurality of records. Each record comprises a plurality of values in a plurality of attributes. Each record is located in at least one of a plurality of blocks of a distributed file system. Each block has a unique identifier. For each block of the distributed file system, at least one value cluster is determined for an attribute of the plurality of attributes. Each value cluster has a range. The predicate of the query is compared with the at least one value cluster of each block.