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:
Methods and systems for controlling vehicle lateral lane positioning are described. A computing device may be configured to identify an object in a vicinity of a vehicle on a road. The computing device may be configured to estimate, based on characteristics of the vehicle and respective characteristics of the object, an interval of time during which the vehicle will be laterally adjacent to the object. Based on the characteristics of the vehicle, the computing device may be configured to estimate longitudinal positions of the vehicle on the road during the interval of time. Based on the respective characteristics of the object, the computing device may be configured to determine a lateral distance for the vehicle to maintain between the vehicle and the object during the interval of time at the longitudinal positions of the vehicle, and provide instructions to control the vehicle based on the lateral distance.
Abstract:
Example methods and systems for detecting weather conditions using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle, and the laser data includes a plurality of laser data points. The method also includes associating, by a computing device, laser data points of the plurality of laser data points with one or more objects in the environment, and determining given laser data points of the plurality of laser data points that are unassociated with the one or more objects in the environment as being representative of an untracked object. The method also includes based on one or more untracked objects being determined, identifying by the computing device an indication of a weather condition of the environment.
Abstract:
Methods and systems for detecting weather conditions including fog using vehicle onboard sensors are provided. An example method includes receiving laser data collected from scans of an environment of a vehicle, and associating, by a computing device, laser data points of with one or more objects in the environment. The method also includes comparing laser data points that are unassociated with the one or more objects in the environment with stored laser data points representative of a pattern due to fog, and based on the comparison, identifying by the computing device an indication that a weather condition of the environment of the vehicle includes fog.
Abstract:
An example method may include receiving a first set of points based on detection of an environment of an autonomous vehicle during a first time period, selecting a plurality of points from the first set of points that form a first point cloud representing an object in the environment, receiving a second set of points based on detection of the environment during a second time period which is after the first period, selecting a plurality of points from the second set of points that form a second point cloud representing the object in the environment, determining a transformation between the selected points from the first set of points and the selected points from the second set of points, using the transformation to determine a velocity of the object, and providing instructions to control the autonomous vehicle based at least in part on the velocity of the object.
Abstract:
Methods and systems for controlling vehicle lateral lane positioning are described. A computing device may be configured to identify an object in a vicinity of a vehicle on a road. The computing device may be configured to estimate, based on characteristics of the vehicle and respective characteristics of the object, an interval of time during which the vehicle will be laterally adjacent to the object. Based on the characteristics of the vehicle, the computing device may be configured to estimate longitudinal positions of the vehicle on the road during the interval of time. Based on the respective characteristics of the object, the computing device may be configured to determine a lateral distance for the vehicle to maintain between the vehicle and the object during the interval of time at the longitudinal positions of the vehicle, and provide instructions to control the vehicle based on the lateral distance.
Abstract:
Methods and devices for controlling a vehicle in an autonomous mode are disclosed. In one aspect, an example method is disclosed that includes obtaining lane information that provides an estimated location of a lane of a road on which a vehicle is traveling. The example method further includes determining that the lane information has become unavailable or unreliable and, in response, using a sensor to monitor a first distance and a second distance between the vehicle and a neighboring vehicle, determining first and second relative positions of the neighboring vehicle based on the first and second distances, respectively, and, based on the first and second relative positions, determining an estimated path of the neighboring vehicle. The example method further includes, based on the estimated path, determining an updated estimated location of the lane, and controlling the vehicle based on the updated estimated location of the lane.
Abstract:
Example methods and systems for detecting weather conditions using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle, and the laser data includes a plurality of laser data points. The method also includes associating, by a computing device, laser data points of the plurality of laser data points with one or more objects in the environment, and determining given laser data points of the plurality of laser data points that are unassociated with the one or more objects in the environment as being representative of an untracked object. The method also includes based on one or more untracked objects being determined, identifying by the computing device an indication of a weather condition of the environment.
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:
Methods and systems for predictive reasoning for controlling speed of a vehicle are described. A computing device may be configured to identify a first and second vehicle travelling ahead of an autonomous vehicle and in a same lane as the autonomous vehicle. The computing device may also be configured to determine a first buffer distance behind the first vehicle at which the autonomous vehicle will substantially reach a speed of the first vehicle and a second buffer distance behind the second vehicle at which the first vehicle will substantially reach a speed of the second vehicle. The computing device may further be configured to determine a distance at which to adjust a speed of the autonomous vehicle based on the first and second buffer distances and the speed of the autonomous vehicle, and then provide instructions to adjust the speed of the autonomous vehicle based on the distance.