Abstract: The technology relates to detecting and responding to emergency vehicles. This may include using a plurality of microphones to detect a siren noise corresponding to an emergency vehicle and to estimate a bearing of the emergency vehicle. This estimated bearing is compared to map information to identify a portion of roadway on which the emergency vehicle is traveling. In addition, information identifying a set of objects in the vehicle's environment as well as characteristics of those objects is received from a perception system is used to determine whether one of the set of objects corresponds to the emergency vehicle. How to respond to the emergency vehicle is determined based on the estimated bearing and identified road segments and the determination of whether one of the set of objects corresponds to the emergency vehicle. This determined response is then used to control the vehicle in an autonomous driving mode.

Abstract: Example embodiments relate to multiple operating modes to expand dynamic range. An example embodiment includes a camera system. The camera system may include a first image sensor having a first dynamic range corresponding to a first range of luminance levels in a scene. The system may also include a second image sensor having a second dynamic range corresponding to a second range of luminance levels in the scene. The camera system may further include a processor coupled to the first image sensor and the second image sensor. The processor may be configured to execute instructions to identify objects of a first type in a first image of the scene captured by the first image sensor and identify objects of a second object type in a second image of the scene captured by the second image sensor.

Abstract: The technology relates to detecting and responding to emergency vehicles. This may include using a plurality of microphones to detect a siren noise corresponding to an emergency vehicle and to estimate a bearing of the emergency vehicle. This estimated bearing is compared to map information to identify a portion of roadway on which the emergency vehicle is traveling. In addition, information identifying a set of objects in the vehicle's environment as well as characteristics of those objects is received from a perception system is used to determine whether one of the set of objects corresponds to the emergency vehicle. How to respond to the emergency vehicle is determined based on the estimated bearing and identified road segments and the determination of whether one of the set of objects corresponds to the emergency vehicle. This determined response is then used to control the vehicle in an autonomous driving mode.

Abstract: A method includes determining a target specification map that is associated with a task and that indicates, for each respective region of a plurality of regions around a vehicle equipped with a sensor, a target value of a parameter of the sensor. The method also includes determining a capability specification map that indicates, for each respective region, an attained value of the parameter that the sensor is configured to provide. The method additionally includes comparing the capability specification map to the target specification map to determine, for each respective region, a disparity between the target value and the attained value. The method further includes, based on the comparing, identifying one or more of: a first subset of the plurality of regions where the target value exceeds the attained value or a second subset of the plurality of regions where the attained value meets or exceeds the target value.

Abstract: This technology relates to a system for clearing a sensor cover. The system may be comprised of a first sensor that rotates within a sensor cover, a plurality of second sensors that are fixed relative to the sensor cover, a first wiper that is configured to clear the sensor cover of debris, and a motor. The motor may rotate the first wiper in a first direction at a first predetermined rotation rate defined at least in part by a second predetermined rotation rate of the first sensor.

Abstract: The technology relates to detecting and responding to emergency vehicles. This may include using a plurality of microphones to detect a siren noise corresponding to an emergency vehicle and to estimate a bearing of the emergency vehicle. This estimated bearing is compared to map information to identify a portion of roadway on which the emergency vehicle is traveling. In addition, information identifying a set of objects in the vehicle's environment as well as characteristics of those objects is received from a perception system is used to determine whether one of the set of objects corresponds to the emergency vehicle. How to respond to the emergency vehicle is determined based on the estimated bearing and identified road segments and the determination of whether one of the set of objects corresponds to the emergency vehicle. This determined response is then used to control the vehicle in an autonomous driving mode.

Abstract: One example system includes a first light detection and ranging (LIDAR) device that scans a first field-of-view defined by a first range of pointing directions associated with the first LIDAR device. The system also includes a second LIDAR device that scans a second FOV defined by a second range of pointing directions associated with the second LIDAR device. The second FOV at least partially overlaps the first FOV. The system also includes a first controller that adjusts a first pointing direction of the first LIDAR device. The system also includes a second controller that adjusts a second pointing direction of the second LIDAR device synchronously with the adjustment of the first pointing direction of the first LIDAR device.

Abstract: One example system comprises a LIDAR sensor that rotates about an axis to scan an environment of the LIDAR sensor. The system also comprises one or more cameras that detect external light originating from one or more external light sources. The one or more cameras together provide a plurality of rows of sensing elements. The rows of sensing elements are aligned with the axis of rotation of the LIDAR sensor. The system also comprises a controller that operates the one or more cameras to obtain a sequence of image pixel rows. A first image pixel row in the sequence is indicative of external light detected by a first row of sensing elements during a first exposure time period. A second image pixel row in the sequence is indicative of external light detected by a second row of sensing elements during a second exposure time period.

Abstract: The technology relates to detecting and responding to emergency vehicles. This may include using a plurality of microphones to detect a siren noise corresponding to an emergency vehicle and to estimate a bearing of the emergency vehicle. This estimated bearing is compared to map information to identify a portion of roadway on which the emergency vehicle is traveling. In addition, information identifying a set of objects in the vehicle's environment as well as characteristics of those objects is received from a perception system is used to determine whether one of the set of objects corresponds to the emergency vehicle. How to respond to the emergency vehicle is determined based on the estimated bearing and identified road segments and the determination of whether one of the set of objects corresponds to the emergency vehicle. This determined response is then used to control the vehicle in an autonomous driving mode.

Abstract: A method includes determining a target specification map that is associated with a task and that indicates, for each respective region of a plurality of regions around a vehicle equipped with a sensor, a target value of a parameter of the sensor. The method also includes determining a capability specification map that indicates, for each respective region, an attained value of the parameter that the sensor is configured to provide. The method additionally includes comparing the capability specification map to the target specification map to determine, for each respective region, a disparity between the target value and the attained value. The method further includes, based on the comparing, identifying one or more of: a first subset of the plurality of regions where the target value exceeds the attained value or a second subset of the plurality of regions where the attained value meets or exceeds the target value.

Abstract: One example system comprises a LIDAR sensor that rotates about an axis to scan an environment of the LIDAR sensor. The system also comprises one or more cameras that detect external light originating from one or more external light sources. The one or more cameras together provide a plurality of rows of sensing elements. The rows of sensing elements are aligned with the axis of rotation of the LIDAR sensor. The system also comprises a controller that operates the one or more cameras to obtain a sequence of image pixel rows. A first image pixel row in the sequence is indicative of external light detected by a first row of sensing elements during a first exposure time period. A second image pixel row in the sequence is indicative of external light detected by a second row of sensing elements during a second exposure time period.

Abstract: A method includes determining a target specification map that is associated with a task and that indicates, for each respective region of a plurality of regions around a vehicle equipped with a sensor, a target value of a parameter of the sensor. The method also includes determining a capability specification map that indicates, for each respective region, an attained value of the parameter that the sensor is configured to provide. The method additionally includes comparing the capability specification map to the target specification map to determine, for each respective region, a disparity between the target value and the attained value. The method further includes, based on the comparing, identifying one or more of: a first subset of the plurality of regions where the target value exceeds the attained value or a second subset of the plurality of regions where the attained value meets or exceeds the target value.

Abstract: The present disclosure relates to systems and methods that facilitate active sensor systems. An example method includes receiving information indicative of an operating context of a vehicle, wherein at least one Light Detection and Ranging (LIDAR) sensor or at least one radar sensor are coupled to the vehicle. The method also includes selecting, from a plurality of sensor power configurations, a desired sensor power configuration based on the operating context of the vehicle. The method further includes causing at least one of: the at least one LIDAR sensor to emit light pulses according to the desired sensor power configuration or the at least one radar sensor to emit radar energy according to the desired sensor power configuration.

Abstract: This technology relates to a system for clearing a sensor cover. The system may be comprised of a first sensor that rotates within a sensor cover, a plurality of second sensors that are fixed relative to the sensor cover, a first wiper that is configured to clear the sensor cover of debris, and a motor. The motor may rotate the first wiper in a first direction at a first predetermined rotation rate defined at least in part by a second predetermined rotation rate of the first sensor.

Abstract: The technology relates to camera systems for vehicles having an autonomous driving mode. An example system includes a first camera mounted on a vehicle in order to capture images of the vehicle's environment. The first camera has a first exposure time and being without an ND filter. The system also includes a second camera mounted on the vehicle in order to capture images of the vehicle's environment and having an ND filter. The system also includes one or more processors configured to capture images using the first camera and the first exposure time, capture images using the second camera and the second exposure time, use the images captured using the second camera to identify illuminated objects, use the images captured using the first camera to identify the locations of objects, and use the identified illuminated objects and identified locations of objects to control the vehicle in an autonomous driving mode.

Abstract: The present disclosure relates to systems and methods that facilitate active sensor systems. An example method includes receiving information indicative of an operating context of a vehicle, wherein at least one Light Detection and Ranging (LIDAR) sensor or at least one radar sensor are coupled to the vehicle. The method also includes selecting, from a plurality of sensor power configurations, a desired sensor power configuration based on the operating context of the vehicle. The method further includes causing at least one of: the at least one LIDAR sensor to emit light pulses according to the desired sensor power configuration or the at least one radar sensor to emit radar energy according to the desired sensor power configuration.

Abstract: The present disclosure relates to systems and methods that facilitate light detection and ranging operations. An example transmit block includes at least one substrate with a plurality of angled facets. The plurality of angled facets provides a corresponding plurality of elevation angles. A set of angle differences between adjacent elevation angles includes at least two different angle difference values. A plurality of light-emitter devices is configured to emit light into an environment along the plurality of elevation angles toward respective target locations so as to provide a desired resolution and/or a respective elevation angle. The present disclosure also relates to adjusting shot power and a shot schedule based on the desired resolution and/or a respective elevation angle.

Abstract: The technology relates to camera systems for vehicles having an autonomous driving mode. An example system includes a first camera mounted on a vehicle in order to capture images of the vehicle's environment. The first camera has a first exposure time and being without an ND filter. The system also includes a second camera mounted on the vehicle in order to capture images of the vehicle's environment and having an ND filter. The system also includes one or more processors configured to capture images using the first camera and the first exposure time, capture images using the second camera and the second exposure time, use the images captured using the second camera to identify illuminated objects, use the images captured using the first camera to identify the locations of objects, and use the identified illuminated objects and identified locations of objects to control the vehicle in an autonomous driving mode.

Abstract: The present disclosure relates to systems and methods that facilitate light detection and ranging operations. An example transmit block includes at least one substrate with a plurality of angled facets. The plurality of angled facets provides a corresponding plurality of elevation angles. A set of angle differences between adjacent elevation angles includes at least two different angle difference values. A plurality of light-emitter devices is configured to emit light into an environment along the plurality of elevation angles toward respective target locations so as to provide a desired resolution and/or a respective elevation angle. The present disclosure also relates to adjusting shot power and a shot schedule based on the desired resolution and/or a respective elevation angle.

Abstract: Example embodiments relate to multiple operating modes to expand dynamic range. An example embodiment includes a camera system. The camera system may include a first image sensor having a first dynamic range corresponding to a first range of luminance levels in a scene. The system may also include a second image sensor having a second dynamic range corresponding to a second range of luminance levels in the scene. The camera system may further include a processor coupled to the first image sensor and the second image sensor. The processor may be configured to execute instructions to identify objects of a first type in a first image of the scene captured by the first image sensor and identify objects of a second object type in a second image of the scene captured by the second image sensor.