Abstract: In an embodiment, a method includes receiving, at an autonomous vehicle, reported data regarding an object in proximity to the autonomous vehicle. The data is collected by a collecting device external to the autonomous vehicle, and is relayed to the autonomous vehicle via a server. The reported data includes a current location, type, or predicted location of the object. The method further includes determining whether the reported data of the object matches an object in an object list determined by on-board sensors of the autonomous vehicle. If the determination finds a found object in the object list, the method correlates the reported data of the object to the found object in the object list. Otherwise, the method adds the reported data of the object to an object list of objects detected by sensor from on-board sensors of the autonomous vehicle. In embodiments, the collecting device is a mobile device.

Abstract: Previous self-driving car systems can detect objects separately with either vision systems, RADAR systems or LIDAR systems. In an embodiment of the present invention, an object fusion module normalizes sensor output from vision, RADAR, and LIDAR systems into a common format. Then, the system fuses the object-level sensor data across all systems by associating all objects detected and predicting tracks for all objects. The present system improves over previous systems by using the data from all sensors combined to develop a single set of knowledge about the objects around the self-driving car, instead of each sensor operating separately.

Abstract: An architecture for an autonomous vehicle uses a top-down approach to enable fully automated driving. The architecture is modular and compatible with hardware from different manufacturers. Each modular component can be tailored for individual cars, which have different vehicle control subsystems and different sensor subsystems.

Abstract: In an embodiment, a method includes receiving, at an autonomous vehicle, reported data regarding an object in proximity to the autonomous vehicle. The data is collected by a collecting device external to the autonomous vehicle, and is relayed to the autonomous vehicle via a server. The reported data includes a current location, type, or predicted location of the object. The method further includes determining whether the reported data of the object matches an object in an object list determined by on-board sensors of the autonomous vehicle. If the determination finds a found object in the object list, the method correlates the reported data of the object to the found object in the object list. Otherwise, the method adds the reported data of the object to an object list of objects detected by sensor from on-board sensors of the autonomous vehicle. In embodiments, the collecting device is a mobile device.

Abstract: In an embodiment, a method includes receiving, at an autonomous vehicle, reported data regarding an object in proximity to the autonomous vehicle. The data is collected by a collecting device external to the autonomous vehicle, and is relayed to the autonomous vehicle via a server. The reported data includes a current location, type, or predicted location of the object. The method further includes determining whether the reported data of the object matches an object in an object list determined by on-board sensors of the autonomous vehicle. If the determination finds a found object in the object list, the method correlates the reported data of the object to the found object in the object list. Otherwise, the method adds the reported data of the object to an object list of objects detected by sensor from on-board sensors of the autonomous vehicle. In embodiments, the collecting device is a mobile device.

Abstract: In an embodiment, a method includes receiving, at an autonomous vehicle, reported data regarding an object in proximity to the autonomous vehicle. The data is collected by a collecting device external to the autonomous vehicle, and is relayed to the autonomous vehicle via a server. The reported data includes a current location, type, or predicted location of the object. The method further includes determining whether the reported data of the object matches an object in an object list determined by on-board sensors of the autonomous vehicle. If the determination finds a found object in the object list, the method correlates the reported data of the object to the found object in the object list. Otherwise, the method adds the reported data of the object to an object list of objects detected by sensor from on-board sensors of the autonomous vehicle. In embodiments, the collecting device is a mobile device.

Abstract: An architecture for an autonomous vehicle uses a top-down approach to enable fully automated driving. The architecture is modular and compatible with hardware from different manufacturers. Each modular component can be tailored for individual cars, which have different vehicle control subsystems and different sensor subsystems.

Abstract: Previous self-driving car systems can detect objects separately with either vision systems, RADAR systems or LIDAR systems. In an embodiment of the present invention, an object fusion module normalizes sensor output from vision, RADAR, and LIDAR systems into a common format. Then, the system fuses the object-level sensor data across all systems by associating all objects detected and predicting tracks for all objects. The present system improves over previous systems by using the data from all sensors combined to develop a single set of knowledge about the objects around the self-driving car, instead of each sensor operating separately.