Waymo LLC patent applications on July 4th, 2024
Patent Applications by Waymo LLC on July 4th, 2024
Waymo LLC: 8 patent applications
Waymo LLC has applied for patents in the areas of G01S13/931 (3), G01S7/497 (2), G01S17/931 (2), G01C19/00 (1), G01S17/86 (1) B60W30/09 (1), B60W60/0016 (1), G01C21/3469 (1), G01C25/00 (1), G01D18/001 (1)
With keywords such as: vehicle, data, sensor, information, light, based, location, device, signals, and radar in patent application abstracts.
Patent Applications by Waymo LLC
20240217510. TRAFFIC SIGNAL RESPONSE FOR AUTONOMOUS VEHICLES_simplified_abstract_(waymo llc)
Inventor(s): Jens-Steffen Ralf Gutmann of Cupertino CA (US) for waymo llc, Andreas Wendel of Mountain View CA (US) for waymo llc, Nathaniel Fairfield of Mountain View CA (US) for waymo llc, Dmitri A. Dolgov of Los Altos CA (US) for waymo llc, Donald Jason Burnette of Mountain View CA (US) for waymo llc
IPC Code(s): B60W30/09, B60W30/18, G08G1/0962, G08G1/0967
CPC Code(s): B60W30/09
Abstract: aspects of the disclosure relate to determining whether a vehicle should continue through an intersection. for example, the one or more of the vehicle's computers may identify a time when the traffic signal light will turn from yellow to red. the one or more computers may also estimate a location of a vehicle at the time when the traffic signal light will turn from yellow to red. a starting point of the intersection may be identified. based on whether the estimated location of the vehicle is at least a threshold distance past the starting point at the time when the traffic signal light will turn from yellow to red, the computers can determine whether the vehicle should continue through the intersection.
Inventor(s): Nicholas Armstrong-Crews of Mountain View CA (US) for waymo llc
IPC Code(s): B60W60/00, B60W40/02, B60W50/06, G06N5/04, G06N20/00, G10L25/51, H04R1/40, H04R3/00
CPC Code(s): B60W60/0016
Abstract: the technology relates to determining a source of a horn honk or other noise in an environment around one or more self-driving vehicles. aspects of the technology leverage real-time information from a group of self-driving vehicles regarding received acoustical information. the location and pose of each self-driving vehicle in the group, along with the precise arrangement of acoustical sensors on each vehicle, can be used to triangulate or otherwise identify the actual location in the environment for the origin of the horn honk or other sound. other sensor information, map data, and additional data can be used narrow down or refine the location of a likely noise source. once the location and source of the noise is known, each self-driving vehicle can use that information to modify current driving operations and/or use it as part of a reinforcement learning approach for future driving situations.
20240219192. MANAGING A FLEET OF VEHICLES_simplified_abstract_(waymo llc)
Inventor(s): Christopher Kennedy Ludwick of Los Altos CA (US) for waymo llc, Andrew Hughes Chatham of San Francisco CA (US) for waymo llc, Matthew Paul McNaughton of Mountain View CA (US) for waymo llc, Charles Bigelow Johnson of Atherton CA (US) for waymo llc
IPC Code(s): G01C21/34, B60L58/12, G07C5/00, G08G1/00
CPC Code(s): G01C21/3469
Abstract: aspects of the disclosure relate to determining a next vehicle task for a vehicle of a fleet. vehicle data from the vehicle, charger data about at least one charger, and demand data may be received and used to determine the next vehicle task. the vehicle may be directed to the next vehicle task. determining a next vehicle task may further be based on predictions made using the vehicle data, the charger data, and the demand data. heuristics may also be used in determining a next vehicle task.
Inventor(s): Dave Ferguson of Mountain View CA (US) for waymo llc, Dorel Ionut Iordache of Mountain View CA (US) for waymo llc
IPC Code(s): G01C25/00, G01C21/00, G01C21/30, G01S3/781, G01S5/16, G01S7/484, G01S7/486, G01S7/497, G01S11/12, G01S13/86, G01S13/931, G01S17/86, G01S17/87, G01S17/89, G01S17/931, G01S19/40, G06V20/56
CPC Code(s): G01C25/00
Abstract: example methods and systems for calibrating sensors using road map data are provided. an autonomous vehicle may use various vehicle sensors to assist in navigation. within examples, the autonomous vehicle may calibrate vehicle sensors through performing a comparison or analysis between information about the environment received by sensors with similar information provided by map data (e.g., a road map). the autonomous vehicle may compare object locations as provided by the sensors and as shown by map data. based on the comparison, the autonomous vehicle may adjust various sensors to accurately reflect the information as provided by the road map. in some instances, the autonomous vehicle may adjust the position, height, orientation, direction-of-focus, scaling, or other parameters of a sensor based on the information provided by a road map.
20240219211. DEVICES AND METHODS FOR ROTARY ENCODER CALIBRATION_simplified_abstract_(waymo llc)
Inventor(s): Craig ROBINSON of Mountain View CA (US) for waymo llc, Alec BERG of Mountain View CA (US) for waymo llc
IPC Code(s): G01D18/00, G01B7/16, G01C19/00, G01D5/14, G01S13/931, G01S17/931
CPC Code(s): G01D18/001
Abstract: one example method involves generating a calibration control signal that causes an actuator to rotate a first platform at least one complete rotation about an axis. the method also involves receiving encoder output signals. the encoder output signals are indicative of angular positions of the first platform about the axis. the method also involves receiving sensor output signals from an orientation sensor mounted on the first platform. the sensor output signals are indicative of a rate of change to an orientation of the orientation sensor. the method also involves determining calibration data based on given sensor output signals received from the orientation sensor during the at least one complete rotation. the calibration data is for mapping the encoder output signals to calibrated measurements of the angular positions of the first platform about the axis.
Inventor(s): Lucas Peeters of Palo Alto CA (US) for waymo llc, Chase Salsbury of San Mateo CA (US) for waymo llc, Kanika Sachdev of Sunnyvale CA (US) for waymo llc, Luke Wachter of San Francisco CA (US) for waymo llc, Tadeusz Pudlik of Mountain View CA (US) for waymo llc, Caner Onal of Palo Alto CA (US) for waymo llc, Logan Su of Palo Alto CA (US) for waymo llc
IPC Code(s): G01S7/497, B08B1/00, B08B3/02, B08B5/02, B08B7/04, B08B13/00
CPC Code(s): G01S7/497
Abstract: example embodiments relate to using cleaning protocols to monitor defects associated with light detection and ranging (lidar) devices. an example embodiment includes a method. the method includes applying, using a cleaning device, a cleaning protocol to one or more optical components of a light detection and ranging (lidar) device. the method also includes emitting, from a light emitter of the lidar device, one or more light signals. additionally, the method includes detecting, by a light detector of the lidar device, reflections of the one or more light signals. further, the method includes determining, by a controller of the lidar device based on the detected reflections of the one or more light signals, that one or more defects are present within the one or more optical components or within the cleaning device.
Inventor(s): Nicholas ARMSTRONG-CREWS of Mountain View CA (US) for waymo llc
IPC Code(s): G01S13/89, G01S13/931
CPC Code(s): G01S13/89
Abstract: example embodiments relate to self-reflection filtering techniques within radar data. a computing device may use radar data to determine a first radar representation that conveys information about surfaces in a vehicle's environment. the computing device may use a predefined model to generate a second radar representation that assigns predicted self-reflection values to respective locations of the environment based on the information about the surfaces conveyed by the first radar representation. the predefined model can enable a predefined self-reflection value to be assigned to a first location based on information about a surface positioned at a second location and a relationship between the first location and the second location. the computing device may then modify the first radar representation based on the predicted self-reflection values in the second radar representation and provide instructions to a control system of the vehicle based on modifying the first radar representation.
20240223882. Multiple Operating Modes to Expand Dynamic Range_simplified_abstract_(waymo llc)
Inventor(s): Andreas Wendel of Mountain View CA (US) for waymo llc, Jeremy Dittmer of Mountain View CA (US) for waymo llc, Brendan Hermalyn of San Francisco CA (US) for waymo llc, Benjamin Ingram of Santa Clara CA (US) for waymo llc
IPC Code(s): H04N23/61, H04N23/45, H04N23/73, H04N23/741
CPC Code(s): H04N23/61
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.
- Waymo LLC
- B60W30/09
- B60W30/18
- G08G1/0962
- G08G1/0967
- CPC B60W30/09
- Waymo llc
- B60W60/00
- B60W40/02
- B60W50/06
- G06N5/04
- G06N20/00
- G10L25/51
- H04R1/40
- H04R3/00
- CPC B60W60/0016
- G01C21/34
- B60L58/12
- G07C5/00
- G08G1/00
- CPC G01C21/3469
- G01C25/00
- G01C21/00
- G01C21/30
- G01S3/781
- G01S5/16
- G01S7/484
- G01S7/486
- G01S7/497
- G01S11/12
- G01S13/86
- G01S13/931
- G01S17/86
- G01S17/87
- G01S17/89
- G01S17/931
- G01S19/40
- G06V20/56
- CPC G01C25/00
- G01D18/00
- G01B7/16
- G01C19/00
- G01D5/14
- CPC G01D18/001
- B08B1/00
- B08B3/02
- B08B5/02
- B08B7/04
- B08B13/00
- CPC G01S7/497
- G01S13/89
- CPC G01S13/89
- H04N23/61
- H04N23/45
- H04N23/73
- H04N23/741
- CPC H04N23/61