Abstract: In various examples, sensor data representative of a field of view of at least one sensor of a vehicle in an environment is received from the at least one sensor. Based at least in part on the sensor data, parameters of an object located in the environment are determined. Trajectories of the object are modeled toward target positions based at least in part on the parameters of the object. From the trajectories, safe time intervals (and/or safe arrival times) over which the vehicle occupying the plurality of target positions would not result in a collision with the object are computed. Based at least in part on the safe time intervals (and/or safe arrival times) and a position of the vehicle in the environment a trajectory for the vehicle may be generated and/or analyzed.

Abstract: In various examples, sensor data representative of a field of view of at least one sensor of a vehicle in an environment is received from the at least one sensor. Based at least in part on the sensor data, parameters of an object located in the environment are determined. Trajectories of the object are modeled toward target positions based at least in part on the parameters of the object. From the trajectories, safe time intervals (and/or safe arrival times) over which the vehicle occupying the plurality of target positions would not result in a collision with the object are computed. Based at least in part on the safe time intervals (and/or safe arrival times) and a position of the vehicle in the environment a trajectory for the vehicle may be generated and/or analyzed.

Abstract: Embodiments of the present disclosure relate to behavior planning for autonomous vehicles. The technology described herein selects a preferred trajectory for an autonomous vehicle based on an evaluation of multiple hypothetical trajectories by different components within a planning system. The various components provide an optimization score for each trajectory according to the priorities of the component and scores from multiple components may form a final optimization score. This scoring system allows the competing priorities (e.g., comfort, minimal travel time, fuel economy) of different components to be considered together. In examples, the trajectory with the best combined score may be selected for implementation. As such, an iterative approach that evaluates various factors may be used to identify an optimal or preferred trajectory for an autonomous vehicle when navigating an environment.

Abstract: In various examples, sensor data representative of a field of view of at least one sensor of a vehicle in an environment is received from the at least one sensor. Based at least in part on the sensor data, parameters of an object located in the environment are determined. Trajectories of the object are modeled toward target positions based at least in part on the parameters of the object. From the trajectories, safe time intervals (and/or safe arrival times) over which the vehicle occupying the plurality of target positions would not result in a collision with the object are computed. Based at least in part on the safe time intervals (and/or safe arrival times) and a position of the vehicle in the environment a trajectory for the vehicle may be generated and/or analyzed.