Abstract: Described herein are compounds that are inhibitors of autophagy and their use in the treatment of disorders such as cancers.

Abstract: Described herein are compounds that are inhibitors of wild type and oncogenic mutant c-KIT kinase and their use in the treatment of disorders such as cancers.

Abstract: Techniques for determining a vehicle trajectory that causes a vehicle to navigate in an environment relative to one or more objects are described herein. For example, the techniques may include a computing device determining a decision tree having nodes to represent different object intents and/or nodes to represent vehicle actions at a future time. A tree search algorithm can search the decision tree to evaluate potential interactions between the vehicle and the one or more objects over a time period, and output a vehicle trajectory for the vehicle. The vehicle trajectory can be sent to a vehicle computing device for consideration during vehicle planning, which may include simulation.

Abstract: Trajectory generation for controlling motion or other behavior of an autonomous vehicle may include alternately determining a candidate action and predicting a future state based on that candidate action. The technique may include determining a cost associated with the candidate action that may include an estimation of a transition cost from a current or former state to a next state of the vehicle. This cost estimate may be a lower bound cost or an upper bound cost and the tree search may alternately apply the lower bound cost or upper bound cost exclusively or according to a ratio or changing ratio. The prediction of the future state may be based at least in part on a machine-learned model's classification of a dynamic object as being a reactive object or a passive object, which may change how the dynamic object is modeled for the prediction.

Abstract: Drive envelope determination is described. In an example, a vehicle can capture sensor data while traversing an environment and can provide the sensor data to computing system(s). The sensor data can indicate agent(s) in the environment and the computing system(s) can determine, based on the sensor data, a planned path through the environment relative to the agent(s). The computing system(s) can also determine lateral distance(s) to the agent(s) from the planned path. In an example, the computing system(s) can determine modified distance(s) based at least in part on the lateral distance(s) and information about the agents. The computing system can determine a drive envelope based on the modified distance(s) and can determine a trajectory in the drive envelope.

Abstract: A vehicle computing system may identify an obstruction along a route of travel and may connect to a service computing device for guidance. The service computing device may include a guidance system configured to receive waypoint and/or orientation input from an operator. The operator may evaluate the scenario and determine one or more waypoints and/or associated orientations for the vehicle to navigate the scenario. In some examples, the guidance system may validate the waypoint(s) and/or associated orientation(s). The service computing device may send the waypoint(s) and/or associated orientation(s) to the vehicle computing system. The vehicle computing system may validate the waypoint(s) and/or associated orientation(s) and, based on the validation, control the vehicle according to the input. Based on a determination that the vehicle has navigated the scenario, the guidance system may release vehicle guidance back to the vehicle computing system.

Abstract: A method for autonomously operating a driverless vehicle along a path between a first geographic location and a destination may include receiving communication signals from the driverless vehicle. The communication signals may include sensor data from the driverless vehicle and data indicating occurrence of an event associated with the path. The communication signals may also include data indicating that a confidence level associated with the path is less than a threshold confidence level due to the event. The method may also include determining, via a teleoperations system, a level of guidance to provide the driverless vehicle based on data associated with the communication signals, and transmitting teleoperations signals to the driverless vehicle. The teleoperations signals may include guidance to operate the driverless vehicle according to the determined level of guidance, so that a vehicle controller maneuvers the driverless vehicle to avoid, travel around, or pass through the event.

Abstract: Described herein are compounds that are inhibitors of autophagy and their use in the treatment of disorders such as cancers.

Abstract: A vehicle computing system may identify an obstruction along a route of travel and may connect to a service computing device for guidance. The service computing device may include a guidance system configured to receive waypoint and/or orientation input from an operator. The operator may evaluate the scenario and determine one or more waypoints and/or associated orientations for the vehicle to navigate the scenario. In some examples, the guidance system may validate the waypoint(s) and/or associated orientation(s). The service computing device may send the waypoint(s) and/or associated orientation(s) to the vehicle computing system. The vehicle computing system may validate the waypoint(s) and/or associated orientation(s) and, based on the validation, control the vehicle according to the input. Based on a determination that the vehicle has navigated the scenario, the guidance system may release vehicle guidance back to the vehicle computing system.

Abstract: Described herein are compounds that are inhibitors of autophagy and their use in the treatment of disorders such as cancers.

Abstract: Described herein are compounds that are inhibitors of autophagy and their use in the treatment of disorders such as cancers.

Abstract: Trajectory generation for controlling motion or other behavior of an autonomous vehicle may include alternately determining a candidate action and predicting a future state based on that candidate action. The technique may include determining a cost associated with the candidate action that may include an estimation of a transition cost from a current or former state to a next state of the vehicle. This cost estimate may be a lower bound cost or an upper bound cost and the tree search may alternately apply the lower bound cost or upper bound cost exclusively or according to a ratio or changing ratio. The prediction of the future state may be based at least in part on a machine-learned model's classification of a dynamic object as being a reactive object or a passive object, which may change how the dynamic object is modeled for the prediction.

Abstract: Described herein are compounds that are inhibitors of autophagy and their use in the treatment of disorders such as cancers.

Abstract: Techniques described herein are directed to classifying lanes in an environment of a vehicle for, for example, performing lane handling. In an example, system(s) of a vehicle can determine a signal indicative of a presence of the vehicle in a lane of a drivable surface in an environment within which the vehicle is located. The system(s) can determine, based at least in part on the signal, a classification of the lane as at least one of occupied (an object is at least partially in the lane), unoccupied (no object in the lane), and/or established (e.g., where an object has established a priority in the lane). The system(s) can control the vehicle based at least in part on the classification of the lane to improve safety in scenarios, for example, including merging.

Abstract: Techniques for generating simulations for evaluating a performance of a controller of an autonomous vehicle are described. A computing system may evaluate the performance of the controller to navigate the simulation and respond to actions of one or more objects (e.g., other vehicles, bicyclists, pedestrians, etc.) in a simulation. Actions of the objects in the simulation may be controlled by the computing system (e.g., by an artificial intelligence) and/or one or more users inputting object controls, such as via a user interface. The computing system may calculate performance metrics associated with the actions performed by the vehicle in the simulation as directed by the autonomous controller. The computing system may utilize the performance metrics to verify parameters of the autonomous controller (e.g., validate the autonomous controller) and/or to train the autonomous controller utilizing machine learning techniques to bias toward preferred actions.

Abstract: Described herein are compounds that are inhibitors of autophagy and their use in the treatment of disorders such as cancers.

Abstract: Described herein are compounds that are inhibitors of autophagy and their use in the treatment of disorders such as cancers.

Abstract: Techniques for determining vehicle trajectories to operate a vehicle according to a planned path are described herein. In an example, a vehicle computing system may determine a location of the vehicle at a first time. Based on the location, the vehicle computing system may determine an estimated location of the vehicle at a second time, the estimated location of the vehicle including a lateral coordinate and a longitudinal coordinate. The vehicle computing system may determine the longitudinal coordinate based on a vehicle trajectory associated with the first time (e.g., previously determined trajectory) and the lateral coordinate based on the planned path. The vehicle computing system may determine a second vehicle trajectory based in part on the estimated location and the first trajectory, and may control the vehicle according to the second vehicle trajectory.

Abstract: Techniques described herein are directed to classifying lanes in an environment of a vehicle for, for example, performing lane handling. In an example, system(s) of a vehicle can determine a signal indicative of a presence of the vehicle in a lane of a drivable surface in an environment within which the vehicle is located. The system(s) can determine, based at least in part on the signal, a classification of the lane as at least one of occupied (an object is at least partially in the lane), unoccupied (no object in the lane), and/or established (e.g., where an object has established a priority in the lane). The system(s) can control the vehicle based at least in part on the classification of the lane to improve safety in scenarios, for example, including merging.

Abstract: A vehicle computing system may identify a scenario in an environment that violates an operating constraint. The vehicle computing system may request remote guidance from a guidance system of a service computing device. The vehicle computing system may receive input from the guidance system including one or more waypoints and/or associated orientations for the vehicle to navigate through the scenario. The vehicle computing system may be configured to validate the input. A validation may include processing the input to determine whether the waypoint(s) and/or orientation(s) associated therewith may cause the vehicle to violate a safety protocol. Based on a determination that the input will not cause the vehicle to violate the safety protocol, the vehicle computing system may control the vehicle according to the input, such as by causing a drive system to operate the vehicle to each waypoint at the associated orientation.