Abstract: Systems and methods for determining whether a vehicle is driving in an unsafe or unsatisfactory manner are disclosed. In some implementations, a system may determine one or more driving scores for a vehicle based on observations of a driving behavior of the vehicle during a time period. The system may generate an indication of unsatisfactory driving based on at least one of the one or more driving scores exceeding a threshold value. The system may provide the indication of unsatisfactory driving to one or more entities. In some aspects, the system may identify one or more dangerous driving attributes exhibited by the vehicle during the time period based on the observations received from the one or more devices. The system may also generate the indication of unsatisfactory driving based at least in part on the identified dangerous driving attributes.

Abstract: Methods, devices and systems enable controlling an autonomous vehicle by identifying a vehicle that is within a threshold distance of the autonomous vehicle, determining an autonomous capability metric (ACM) the identified vehicle, determining whether the ACM of the identified vehicle is greater than a first threshold, determining whether the ACM of the identified vehicle is less than a second threshold, and adjusting a driving parameter of the autonomous vehicle so that the autonomous vehicle is more or less reliant on the capabilities of the identified vehicle based on whether the ACM of the identified vehicle exceeds the thresholds.

Abstract: Various aspects may include methods enabling a vehicle to broadcast intentions and/or motion plans to surrounding vehicles. Various aspects include methods for using intentions and/or motion plans received from one or more surrounding vehicles.

Abstract: In some aspects, a device of a vehicle may obtain information relating to an environment in which the vehicle is located. The device may determine using a machine learning model, a driving context of the vehicle based at least in part on the information relating to the environment, and a set of hyperparameters for a model, that is used to determine a driving behavior for the vehicle, based at least in part on the driving context. The device may determine, using the model configured with the set of hyperparameters, the driving behavior for the vehicle. The device may cause autonomous operation of the vehicle in accordance with the driving behavior. Numerous other aspects are described.

Abstract: Methods, systems, and devices for automatically customizing operation of a robotic vehicle are described. The method may include identifying an operator, retrieving an operator profile and associated metadata for the operator from a database, where the metadata includes operator habit information, and configuring the robotic vehicle based on existing preference-based and performance-based settings, where the existing preference-based and performance-based settings are based on the metadata. The methods may include identifying operator habit information during operation of the robotic vehicle, deriving updated preference-based and performance-based settings for the operator based on the identified operator habit information, and providing, to the database, modifications to the metadata associated with the operator profile of the operator.

Abstract: Systems and methods for determining whether a vehicle is driving in an unsafe or unsatisfactory manner are disclosed. In some implementations, a system may determine one or more driving scores for a vehicle based on observations of a driving behavior of the vehicle during a time period. The system may generate an indication of unsatisfactory driving based on at least one of the one or more driving scores exceeding a threshold value. The system may provide the indication of unsatisfactory driving to one or more entities. In some aspects, the system may identify one or more dangerous driving attributes exhibited by the vehicle during the time period based on the observations received from the one or more devices. The system may also generate the indication of unsatisfactory driving based at least in part on the identified dangerous driving attributes.

Abstract: Methods, devices and systems enable controlling an autonomous vehicle by identifying a vehicle that is within a threshold distance of the autonomous vehicle, determining an autonomous capability metric (ACM) the identified vehicle, determining whether the ACM of the identified vehicle is greater than a first threshold, determining whether the ACM of the identified vehicle is less than a second threshold, and adjusting a driving parameter of the autonomous vehicle so that the autonomous vehicle is more or less reliant on the capabilities of the identified vehicle based on whether the ACM of the identified vehicle exceeds the thresholds.

Abstract: Various embodiments include methods and interactive traffic control devices for interactively controlling traffic, which may include receiving refined location and state information associated with individual vehicles on a roadway, and determining customized dynamic traffic control instructions for a first one or more of the individual vehicles. The determined customized dynamic traffic control instructions may be based on the received refined location and state information and offer an optional route alternative to a set limited number of the individual vehicles. The first customized dynamic traffic control instructions may be transmitted by the interactive traffic control device to the first one or more of the individual vehicles.

Abstract: Methods, devices and systems enable controlling an autonomous vehicle by identifying vehicles that are within a threshold distance of the autonomous vehicle, determining an autonomous capability metric of each of the identified vehicles, and adjusting a driving parameter of the autonomous vehicle based on the determined autonomous capability metric of each of the identified vehicles. Adjusting a driving parameter may include adjusting one or more of a minimum separation distance, a minimum following distance, a speed parameter, or an acceleration rate parameter.

Abstract: Methods, devices and systems enable controlling an autonomous vehicle by identifying vehicles that are within a threshold distance of the autonomous vehicle, determining an autonomous capability metric of each of the identified vehicles, and adjusting a driving parameter of the autonomous vehicle based on the determined autonomous capability metric of each of the identified vehicles. Embodiments may further include determining, based on the determined ACMs, whether one or more identified vehicles would provide an operational advantage to the autonomous vehicle in a cooperative driving engagement, and initiating a cooperative driving engagement with the one or more identified vehicles in response to determining that the one or more identified vehicles would provide an operational advantage to the autonomous vehicle in a cooperative driving engagement.

Abstract: Various embodiments include processing devices and methods for managing cleaning behavior by a cleaning robot. In some embodiments, a processor of the cleaning robot may obtain user planning information and user location information from one or more information sources external to the cleaning robot. The processor may analyze the user planning information and the user location information. The processor may determine one or more cleaning parameters for the cleaning robot based on the analysis of the user planning information and the user location information. The processor may generate an instruction for the cleaning robot to schedule an operation of the cleaning robot based on the one or more cleaning parameters. The processor may execute the generated instruction to perform the operation of the cleaning robot.

Abstract: Embodiments include devices and methods for vehicle collision avoidance. A processor of the vehicle may receive lidar sensor data comprising one or more points including a distance and a direction from the vehicle to the one or more points. The processor may determine a velocity constraint for each of the one or more points based on the distance and direction from the vehicle to the one or more points. Based on a navigation instruction, the processor may determine one or more velocity solutions that satisfy the one or more velocity constraints. The processor may select a velocity solution from the determined one or more velocity solutions based on the navigation instruction, and may adjust a vehicle velocity based on the selected velocity solution.

Abstract: Methods, systems, and devices for robotic navigation are described. A robotic device such as a robotic vacuum or a robotic assistant may navigate a first surface. In some cases, navigating the first surface may include removing debris from the first surface. The robotic device may identify a location of a track that connects the first surface to a second surface that is vertically displaced from the first surface. The robotic device may engage the track based at least in part on the identified location. The robotic device may ascend to the second surface by activating an actuator and navigate the second surface (e.g., may remove debris from the second surface, may map the second surface, etc.).

Abstract: Methods, systems, and devices for automatically customizing operation of a robotic vehicle are described. The method may include identifying an operator, retrieving an operator profile and associated metadata for the operator from a database, where the metadata includes operator habit information, and configuring the robotic vehicle based on existing preference-based and performance-based settings, where the existing preference-based and performance-based settings are based on the metadata. The methods may include identifying operator habit information during operation of the robotic vehicle, deriving updated preference-based and performance-based settings for the operator based on the identified operator habit information, and providing, to the database, modifications to the metadata associated with the operator profile of the operator.

Abstract: Some embodiments include methods for customizing operation of the robotic vehicle for an operator. Such embodiments may include identifying a current operator of the robotic vehicle, configuring the robotic vehicle based on metadata associated with an operator profile for the operator, determining whether the operator has changed, and if so, identifying the new operator, deriving updated preference-based settings and performance-based settings for the new operator, and updating configurations of the robotic vehicle accordingly.

Abstract: Various embodiments may include methods of using image data to estimate motion of a vehicle observed within camera images, such as images captured by a vehicle navigation system of a host vehicle. Various embodiments may include a camera capturing a sequence of images including the observed vehicle, and a processor performing image processing to identify a wheel of the observed vehicle, and determining a rate of rotation of the wheel based on changes in orientation of the wheel between at least two images within the sequence of images. The processor may further determine a speed of the observed vehicle based on the wheel's rate of rotation and diameter. The processor may further determine a direction of travel and/or turning rate of the observed vehicle by determining relative angles of wheels of the observed vehicle in at least one image.

Abstract: Methods, devices and systems enable controlling an autonomous vehicle by identifying vehicles that are within a threshold distance of the autonomous vehicle, determining an autonomous capability metric of each of the identified vehicles, and adjusting a driving parameter of the autonomous vehicle based on the determined autonomous capability metric of each of the identified vehicles. Embodiments may further include determining, based on the determined ACMs, whether one or more identified vehicles would provide an operational advantage to the autonomous vehicle in a cooperative driving engagement, and initiating a cooperative driving engagement with the one or more identified vehicles in response to determining that the one or more identified vehicles would provide an operational advantage to the autonomous vehicle in a cooperative driving engagement.

Abstract: Methods, devices and systems enable controlling an autonomous vehicle by identifying vehicles that are within a threshold distance of the autonomous vehicle, determining an autonomous capability metric of each of the identified vehicles, and adjusting a driving parameter of the autonomous vehicle based on the determined autonomous capability metric of each of the identified vehicles. Adjusting a driving parameter may include adjusting one or more of a minimum separation distance, a minimum following distance, a speed parameter, or an acceleration rate parameter.

Abstract: Various aspects may include methods enabling a vehicle to broadcast intentions and/or motion plans to surrounding vehicles. Various aspects include methods for using intentions and/or motion plans received from one or more surrounding vehicles.

Abstract: Various embodiments include methods, systems, and devices for interactively controlling traffic. The method, which may be performed by operations of the systems and/or devices, may include receiving, for example by an interactive traffic control device, refined location and state information associated with a first vehicle on a roadway. The interactive traffic control device may also determine at least one notable element in the refined location and state information, customized dynamic traffic control instructions based on the refined location and state information, and whether the customized dynamic traffic control instructions conflict with the at least one notable element. In addition, the interactive traffic control device may transmit the customized dynamic traffic control instructions to the first vehicle in response to determining the customized dynamic traffic control instructions do not conflict with the at least one notable element.