Waymo LLC

Muvr Labs, Inc.

Pablo Abad

Jasman Singh Malik

Joe Riggs

Aman Ved Kalia

Jiayi Chen

Juan Gomez-Ramos

Khawaja Waqee Khalid

Kang Li

Ivan Vican

Prudhvi Tej Chinimilli

Karen Rajen Parikh

David Garber

Tony Grue

Karan Rajen Parikh

Example embodiments relate to a method for cut-in identification and classification. An example embodiment includes a obtaining operational data about one or more vehicles; based on the operational data, identifying the presence of one or more cut-ins within the operational data; extracting, from the operational data, cut-in data that depicts one or more of the cut-ins identified within the operational data; and, based on the extracted cut-in data, training a model for controlling an autonomous vehicle. Identifying the presence of a given cut-in includes: determining that at least one vertex of a bounding box surrounding a vehicle was located more than a threshold distance within a lane being navigated by a given vehicle; and determining that the ability of the given vehicle to maintain its course and speed was impeded by the presence of the particular additional vehicle within the lane.

Automated cut-in identification and classification

Example embodiments relate to lane adjustment techniques for slow lead agents. A vehicle computing system may use sensor data depicting the surrounding environment to detect when another vehicle is traveling in front of the vehicle at a speed that is less than a threshold minimum speed. If the other vehicle fails to increase speed above the minimum speed, the computing system may determine whether to change lanes to avoid the other vehicle based on speed data for other lanes. In some implementations, the computing system assigns penalties to lane segments surrounding the vehicle based on speed data for the different lane segments. For instance, the path finding system for the vehicle can use penalties and speed data to determine efficient routes that safely circumvent slow agents.

Lane adjustment techniques for slow lead agents

A computer-implemented method is provided that involves determining, based on map data, an approaching merge region comprising an on-ramp merging with a road comprising one or more lanes, wherein a truck is traveling on an initial lane of the road according to a navigation plan. The method involves an indication of movement of a vehicle on the on-ramp, wherein the indication of movement is based on data collected by one or more sensors configured to capture sensor data from an environment surrounding the truck. The method involves determining, for the on-ramp and the one or more lanes, respective avoidance scores indicative of a likelihood of an interaction between the truck and the vehicle based on the approaching merge region. The method involves updating the navigation plan based on the respective avoidance scores. The method also involves controlling the truck to execute a driving strategy based on the updated navigation plan.

Systems and methods to determine a lane change strategy at a merge region

Systems and methods for calculating mobility metrics associated to a plurality of wearable sensors in various arrangements comprising a plurality of communicatively-connected sensors comprising inertial measurement units (IMU) attached to connected bodies of a hinge or ball joint in communication with a computing device. Systems and methods for quaternion calculations comprising a first sensor's quaternion output as estimate into another sensor's quaternion calculation to improve the other sensor's quaternion estimate and vice versa. Systems and methods for data synchronization of a plurality of sensors involving building an external reference time vector and interpolating the sensor's data based on the reference time vector. Systems and methods for calculating a sensor's orientation and position based on the inertial measurements captured by the wearable sensors during hinge or ball joint movements to, at least, calculate a joint angle.

System and method for angle calculations for a plurality of inertial measurement units

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San Francisco, CA, United States of America

Pablo Abad