Abstract:
A vehicle may receive one or more images of an environment of the vehicle. The vehicle may also receive a map of the environment. The vehicle may also match at least one feature in the one or more images with corresponding one or more features in the map. The vehicle may also identify a given area in the one or more images that corresponds to a a portion of the map that is within a threshold distance to the one or more features. The vehicle may also compress the one or more images to include a lower amount of details in areas of the one or more images other than the given area. The vehicle may also provide the compressed images to a remote system, and responsively receive operation instructions from the remote system.
Abstract:
Example systems and methods enable an autonomous vehicle to request assistance from a remote operator in certain predetermined situations. One example method includes determining a representation of an environment of an autonomous vehicle based on sensor data of the environment. Based on the representation, the method may also include identifying a situation from a predetermined set of situations for which the autonomous vehicle will request remote assistance. The method may further include sending a request for assistance to a remote assistor, the request including the representation of the environment and the identified situation. The method may additionally include receiving a response from the remote assistor indicating an autonomous operation. The method may also include causing the autonomous vehicle to perform the autonomous operation.
Abstract:
Systems and methods are provided that may optimize basic models of an intersection in a roadway with high intensity image data of the intersection of the roadway. More specifically, parameters that define the basic model of the intersection in the roadway may be adjusted to more accurately define the intersection. For example, by comparing a shape of the intersection predicted by the basic model with extracted curbs and lane boundaries from elevation and intensity maps, the intersection parameters can be optimized to match real intersection-features in the environment. Once the optimal intersection parameters have been found, roadgraph features describing the intersection may be extracted.
Abstract:
Systems and methods are provided that may optimize basic models of an intersection in a roadway with high intensity image data of the intersection of the roadway. More specifically, parameters that define the basic model of the intersection in the roadway may be adjusted to more accurately define the intersection. For example, by comparing a shape of the intersection predicted by the basic model with extracted curbs and lane boundaries from elevation and intensity maps, the intersection parameters can be optimized to match real intersection-features in the environment. Once the optimal intersection parameters have been found, roadgraph features describing the intersection may be extracted.
Abstract:
A vehicle may receive one or more images of an environment of the vehicle. The vehicle may also receive a map of the environment. The vehicle may also match at least one feature in the one or more images with corresponding one or more features in the map. The vehicle may also identify a given area in the one or more images that corresponds to a portion of the map that is within a threshold distance to the one or more features. The vehicle may also compress the one or more images to include a lower amount of details in areas of the one or more images other than the given area. The vehicle may also provide the compressed images to a remote system, and responsively receive operation instructions from the remote system.
Abstract:
Disclosed herein are systems and methods for providing supplemental identification abilities to an autonomous vehicle system. The sensor unit of the vehicle may be configured to receive data indicating an environment of the vehicle, while the control system may be configured to operate the vehicle. The vehicle may also include a processing unit configured to analyze the data indicating the environment to determine at least one object having a detection confidence below a threshold. Based on the at least one object having a detection confidence below a threshold, the processor may communicate at least a subset of the data indicating the environment for further processing. The vehicle is also configured to receive an indication of an object confirmation of the subset of the data. Based on the object confirmation of the subset of the data, the processor may alter the control of the vehicle by the control system.