Abstract: Techniques for determining to modify a trajectory based on an object are discussed herein. A vehicle can determine a drivable area of an environment, capture sensor data representing an object in the environment, and perform a spot check to determine whether or not to modify a trajectory. Such a spot check may include processing to incorporate an actual or predicted extent of the object into the drivable area to modify the drivable area. A distance between a reference trajectory and the object can be determined at discrete points along the reference trajectory, and based on a cost, distance, or intersection associated with the trajectory and the modified area, the vehicle can modify its trajectory. One trajectory modification includes following, which may include varying a longitudinal control of the vehicle, for example, to maintain a relative distance and velocity between the vehicle and the object.

Abstract: A delegate interoperability network for may include a plurality of delegates instantiated on a plurality of different blockchains. The delegate network may enable blockchain interoperability by receiving, at a first delegate instantiated on a first blockchain, a request to initiate, on a second blockchain, a blockchain action on behalf of a user. The method further includes generating, by the first delegate, a unique delegate network address associated with the user and the first blockchain. The method further includes determining, by the first delegate, whether the second blockchain has sufficient gas token liquidity to complete the blockchain action. The method further includes based at least in part on determining that the second blockchain has sufficient gas token liquidity, sending, to a second delegate instantiated on the second blockchain, a first message to initiate the blockchain action.

Abstract: Techniques and methods for determining regions. For instance, a vehicle may determine a trajectory of the vehicle and a trajectory of an agent, such as a pedestrian. The vehicle may then determine one or more contextual factors. In some examples, the one or more contextual factors are associated with a location of the agent with respect to a crosswalk, a location of the vehicle with respect to the crosswalk, a state of the crosswalk, and/or the like. The vehicle may then determine the region using the trajectory of the vehicle, the trajectory of the agent, and the one or more contextual factors. Additionally, using a time buffer value and a distance buffer value associated with the region, the vehicle may determine whether to yield to the agent within the region.

Abstract: Techniques for determining a speed for a vehicle as it traverses an environment with pedestrians are discussed herein. For example, a vehicle computing system may implement techniques to determine an action for a vehicle to take based on a detected pedestrian in an environment. The vehicle computing system may receive sensor data of an environment from a sensor associated with a vehicle, determine, based at least in part on the sensor data, an object in the environment and receive a predicted object trajectory associated with the object. The vehicle computing system may then determine, based on the predicted object trajectory, a distance between a simulated vehicle passing location and a predicted object location, determine, based on the distance, a speed, determine, based on the distance and the speed, a trajectory for the vehicle to follow, and control the vehicle based on the trajectory.

Abstract: A vehicle computing system may implement techniques to emit warning sounds from a vehicle to notify other entities in an environment with the vehicle of the vehicle operation. A vehicle computing system may be configured to emit warning sounds based on a speed associated with the vehicle. The vehicle computing system may determine a planned vehicle trajectory and that a speed corresponding to the planned vehicle trajectory is associated with the warning sound emission. The vehicle computing system may determine a time that the vehicle will be at the speed and may emit the warning sound substantially at the time. In some examples, the vehicle computing system may emit a different sound prior to the time and may transition to the warning sound associated with the speed at the time. By warning other entities of the vehicle operation, the warning sound emission system may improve the safety of vehicle operation.

Abstract: The described techniques relate to modifying a trajectory of a vehicle, such as an autonomous vehicle, based on a latency associated with one or more systems of the vehicle. In examples, a planning system of the vehicle may predict a future latency (e.g., based on an interval between receipt of sensor data and/or object predictions), and use the future latency to determine a time at which to predict object behavior. Additionally, in some cases, the described techniques may include associating a predetermined acceleration with a predicted future location of the object to create a safety distance around the object, where the predetermined acceleration may be based on a maximum expected acceleration of the object. The safety distance may account for the object potentially accelerating in one or more directions at the future time.

Abstract: Techniques for detecting an object in an environment, determining a probability that the object is a region of particulate matter, and controlling a vehicle based on the probability. The region particulate matter may include steam (e.g., emitted from a man-hole cover, a dryer exhaust port, etc.), exhaust from a vehicle (e.g., car, truck, motorcycle, etc.), dust, environmental gases (e.g., resulting from sublimation, fog, evaporation, etc.), or the like. Based on the associated probability that the object is a region of particulate matter, a vehicle computing system may substantially maintain a vehicle trajectory, modify a trajectory of the vehicle to ensure the vehicle does not impact the object, stop the vehicle, or otherwise control the vehicle to ensure that the vehicle continues to progress in a safe manner. The vehicle controller may continually adjust the trajectory based on additionally acquired sensor data and associated region probabilities.

Abstract: Techniques and methods for providing additional safety for interactions with pedestrians. For instance, a vehicle may identify a region through which the vehicle and agent (such as a pedestrian) pass. The vehicle may then use a first state of the vehicle and predicted positions for the agent to determine a first collision metric between the vehicle and the agent within the region. Additionally, the vehicle may use the first collision metric to determine a maneuver for the vehicle. Next, the vehicle may simulate a state of the vehicle at a second time, where the state if based on the maneuver. The vehicle may then determine a second collision metric between the vehicle and the agent within the region using the state and the predicted positions of the agent. Additionally, the vehicle may use the second collision metric to determine another maneuver for the vehicle.

Abstract: Techniques and methods for determining regions. For instance, a vehicle may determine a trajectory of the vehicle and a trajectory of an agent, such as a pedestrian. The vehicle may then determine one or more contextual factors. In some examples, the one or more contextual factors are associated with a location of the agent with respect to a crosswalk, a location of the vehicle with respect to the crosswalk, a state of the crosswalk, and/or the like. The vehicle may then determine the region using the trajectory of the vehicle, the trajectory of the agent, and the one or more contextual factors. Additionally, using a time buffer value and a distance buffer value associated with the region, the vehicle may determine whether to yield to the agent within the region.

Abstract: A vehicle computing device may implement techniques to predict behavior of objects or predicted objects in an environment. The techniques may include using a model to determine whether a potential object will emerge from an occluded region in the environment. The model may be configured to use one or more algorithms, classifiers, and/or computational resources to predict an intersection point and/or an intersection time between the potential object and the vehicle. Based on the predicted intersection point and/or the predicted intersection time, the vehicle computing device may control operation of the vehicle.

Abstract: Techniques and methods for determining regions. For instance, a vehicle may determine a trajectory of the vehicle and a trajectory of an agent, such as a pedestrian. The vehicle may then determine one or more contextual factors. In some examples, the one or more contextual factors are associated with a location of the agent with respect to a crosswalk, a location of the vehicle with respect to the crosswalk, a state of the crosswalk, and/or the like. The vehicle may then determine the region using the trajectory of the vehicle, the trajectory of the agent, and the one or more contextual factors. Additionally, using a time buffer value and a distance buffer value associated with the region, the vehicle may determine whether to yield to the agent within the region.

Abstract: Techniques and methods for providing additional safety for interactions with pedestrians. For instance, a vehicle may identify a region through which the vehicle and agent (such as a pedestrian) pass. The vehicle may determine a time buffer value and/or a distance buffer value based on the vehicle and the agent passing through the region. The vehicle may determine a time threshold and/or a distance threshold for passing through the region in the presence of the agent. The time threshold and/or the distance threshold may be based on a velocity of the vehicle, a safety factor, a hysteresis factor, a comfort factor, and/or an assertiveness factor. If the time buffer value is below the time threshold and/or the distance buffer value is below the distance threshold, the vehicle may yield to the agent. Otherwise, the vehicle may not yield to the agent within the region.

Abstract: Techniques for determining to modify a trajectory based on an object are discussed herein. A vehicle can determine a drivable area of an environment, capture sensor data representing an object in the environment, and perform a spot check to determine whether or not to modify a trajectory. Such a spot check may include processing to incorporate an actual or predicted extent of the object into the drivable area to modify the drivable area. A distance between a reference trajectory and the object can be determined at discrete points along the reference trajectory, and based on a cost, distance, or intersection associated with the trajectory and the modified area, the vehicle can modify its trajectory. One trajectory modification includes following, which may include varying a longitudinal control of the vehicle, for example, to maintain a relative distance and velocity between the vehicle and the object.

Abstract: Techniques for determining to modify a trajectory based on an object are discussed herein. A vehicle can determine a drivable area of an environment, capture sensor data representing an object in the environment, and perform a spot check to determine whether or not to modify a trajectory. Such a spot check may include processing to incorporate an actual or predicted extent of the object into the drivable area to modify the drivable area. A distance between a reference trajectory and the object can be determined at discrete points along the reference trajectory, and based on a cost, distance, or intersection associated with the trajectory and the modified area, the vehicle can modify its trajectory. One trajectory modification includes following, which may include varying a longitudinal control of the vehicle, for example, to maintain a relative distance and velocity between the vehicle and the object.

Abstract: The described techniques relate to modifying a trajectory of a vehicle, such as an autonomous vehicle, based on a latency associated with one or more systems of the vehicle. In examples, a planning system of the vehicle may predict a future latency (e.g., based on an interval between receipt of sensor data and/or object predictions), and use the future latency to determine a time at which to predict object behavior. Additionally, in some cases, the described techniques may include associating a predetermined acceleration with a predicted future location of the object to create a safety distance around the object, where the predetermined acceleration may be based on a maximum expected acceleration of the object. The safety distance may account for the object potentially accelerating in one or more directions at the future time.

Abstract: A vehicle computing system may implement techniques to determine an action for a vehicle to take based on a detected object blocking a path (e.g., trajectory) of the vehicle. The vehicle computing system may detect the object based on sensor data and determine that a location associated with the object is at least partially within a drivable surface over which the vehicle plans to travel on a trajectory. The vehicle computing system may determine a likelihood that object will continue to block the path of the vehicle. Based in part on the likelihood that the object will continue to block the path, the vehicle computing system may determine to maintain a stopped position prior to the location to wait for the object to move or to modify the trajectory of the vehicle to circumnavigate the object.

Abstract: Techniques for detecting an object in an environment, determining a probability that the object is a region of particulate matter, and controlling a vehicle based on the probability. The region particulate matter may include steam (e.g., emitted from a man-hole cover, a dryer exhaust port, etc.), exhaust from a vehicle (e.g., car, truck, motorcycle, etc.), dust, environmental gases (e.g., resulting from sublimation, fog, evaporation, etc.), or the like. Based on the associated probability that the object is a region of particulate matter, a vehicle computing system may substantially maintain a vehicle trajectory, modify a trajectory of the vehicle to ensure the vehicle does not impact the object, stop the vehicle, or otherwise control the vehicle to ensure that the vehicle continues to progress in a safe manner. The vehicle controller may continually adjust the trajectory based on additionally acquired sensor data and associated region probabilities.

Abstract: Techniques and methods for determining regions. For instance, a vehicle may determine a trajectory of the vehicle and a trajectory of an agent, such as a pedestrian. The vehicle may then determine one or more contextual factors. In some examples, the one or more contextual factors are associated with a location of the agent with respect to a crosswalk, a location of the vehicle with respect to the crosswalk, a state of the crosswalk, and/or the like. The vehicle may then determine the region using the trajectory of the vehicle, the trajectory of the agent, and the one or more contextual factors. Additionally, using a time buffer value and a distance buffer value associated with the region, the vehicle may determine whether to yield to the agent within the region.

Abstract: Techniques and methods for providing additional safety for interactions with pedestrians. For instance, a vehicle may identify a region through which the vehicle and agent (such as a pedestrian) pass. The vehicle may determine a time buffer value and/or a distance buffer value based on the vehicle and the agent passing through the region. The vehicle may determine a time threshold and/or a distance threshold for passing through the region in the presence of the agent. The time threshold and/or the distance threshold may be based on a velocity of the vehicle, a safety factor, a hysteresis factor, a comfort factor, and/or an assertiveness factor. If the time buffer value is below the time threshold and/or the distance buffer value is below the distance threshold, the vehicle may yield to the agent. Otherwise, the vehicle may not yield to the agent within the region.

Abstract: Techniques for determining to modify a trajectory based on an object are discussed herein. A vehicle can determine a drivable area of an environment, capture sensor data representing an object in the environment, and perform a spot check to determine whether or not to modify a trajectory. Such a spot check may include processing to incorporate an actual or predicted extent of the object into the drivable area to modify the drivable area. A distance between a reference trajectory and the object can be determined at discrete points along the reference trajectory, and based on a cost, distance, or intersection associated with the trajectory and the modified area, the vehicle can modify its trajectory. One trajectory modification includes following, which may include varying a longitudinal control of the vehicle, for example, to maintain a relative distance and velocity between the vehicle and the object.