Abstract: A method for determining a scan pattern according to which a sensor equipped with a scanner scans a field of regard (FOR) is presented. The method comprises obtaining, by processing hardware, a plurality of objective functions, each of the objective functions specifying a cost for a respective property of the scan pattern, expressed in terms of one or more operational parameters of the scanner. The method further includes applying, by the processing hardware, an optimization scheme to the plurality of objective functions to generate the scan pattern. The method further includes scanning the FOR according to the generated scan pattern.

Abstract: A scanning imaging sensor is configured to sense an environment through which a vehicle is moving. A method for determining one or velocities associated with objects in the environment includes generating features from the first set of scan lines and the second set of scan lines, the two sets corresponding to two instances in time. The method further includes generating a collection of candidate velocities based on feature locations and time differences, the features selected pairwise with one from the first set and another from the second set. Furthermore, the method includes analyzing the distribution of candidate velocities, for example, by identifying one or more modes from the collection of the candidate velocities.

Abstract: A system and method are described for assessing accuracy of a virtual horizon generated by a vehicle-based lidar system as the vehicle traverses a route of travel. Travel route topology data is obtained by a vehicle vehicle-mounted global positioning system-assisted inertial measurement unit (GPS/IMU) data. A reference virtual horizon at points along the route of travel is obtained from the GPS/IMU data and is compared with the virtual horizon generated by the lidar system for the same points to assess the accuracy of the virtual horizon generated by the lidar system.

Abstract: An imaging system is described for generating an estimate for the virtual horizon for a moving vehicle. The estimate of the virtual horizon can correspond to lower and higher boundaries of a region within the field of regard, such that the virtual horizon is between the lower and the higher boundaries, in cases where determination of the virtual horizon may be unreliable due to traffic, weather or other road conditions that obscure the visibility in front of the vehicle the imaging system may switch to a static vertical scan density pattern having a broad central focus, which can mitigate the possibility that the system focuses on an incorrect virtual horizon and fails to capture significant objects or conditions in the roadway.

Abstract: An imaging system is described for generating an estimate for a virtual horizon for a moving vehicle. The estimate is based on a lidar point cloud and on pitch rate data from a gyroscope. The lidar point cloud data estimates the horizon based on lidar scans that are updated at a first rate. The gyroscope data is updated at a second rate that is faster than the first rate and therefore can be used to augment the point cloud based horizon estimation to produce a more accurate horizon estimation when the vehicle is pitching at a high rate. The gyroscope data can also be used to correct individual point clouds, which may be distorted if the vehicle is pitching or rolling during an individual scan.

Abstract: A method for tracking a lane on a road is presented. The method comprises receiving, by one or more processors from an imaging system, a set of pixels associated with lane markings. The method further includes generating, by the one or more processors, a predicted spline comprising (i) a first spline and (ii) a predicted extension of the first spline in a direction in which the imaging system is moving. The first spline describes a boundary of a lane and is generated based on the set of pixels. The predicted extension of the first spline is generated based at least in part on a curvature of at least a portion of the first spline.

Abstract: A method for determining a scan pattern according to which a sensor equipped with a scanner scans a field of regard (FOR) is presented. The method comprises obtaining, by processing hardware, a plurality of objective functions, each of the objective functions specifying a cost for a respective property of the scan pattern, expressed in terms of one or more operational parameters of the scanner. The method further includes applying, by the processing hardware, an optimization scheme to the plurality of objective functions to generate the scan pattern. The method further includes scanning the FOR according to the generated scan pattern.

Abstract: A scanning imaging sensor is configured to sense an environment through which a vehicle is moving. A method for determining one or velocities associated with objects in the environment includes generating features from the first set of scan lines and the second set of scan lines, the two sets corresponding to two instances in time. The method further includes generating a collection of candidate velocities based on feature locations and time differences, the features selected pairwise with one from the first set and another from the second set. Furthermore, the method includes analyzing the distribution of candidate velocities, for example, by identifying one or more modes from the collection of the candidate velocities.

Abstract: A method for tracking a lane on a road is presented. The method comprises receiving, by one or more processors from an imaging system, a set of pixels associated with lane markings. The method further includes generating, by the one or more processors, a predicted spline comprising (i) a first spline and (ii) a predicted extension of the first spline in a direction in which the imaging system is moving. The first spline describes a boundary of a lane and is generated based on the set of pixels. The predicted extension of the first spline is generated based at least in part on a curvature of at least a portion of the first spline.

Abstract: A computer-readable medium stores instructions executable by one or more processors to implement a self-driving control architecture for controlling an autonomous vehicle. A perception component receives sensor data and generates signals descriptive of a current state of the environment. Based on those signals, a prediction component generates signals descriptive of one or more predicted future environment states. A motion planner generates decisions for maneuvering the vehicle toward a destination, at least by using the signals descriptive of the current and future environment states to set values of one or more independent variables in an objective equation. The objective equation includes terms corresponding to different driving objectives over a finite time horizon. Values of one or more dependent variables in the objective equation are determined by solving the equation subject to a set of constraints, and values of the dependent variables are used to generate decisions for maneuvering the vehicle.