Abstract: Systems and methods of maneuvering an autonomous vehicle in a local region using topological planning, while traversing a route to a destination location, are disclosed. The system includes an autonomous vehicle including one or more sensors and a processor. The processor is configured to determine the local region on the route and receive real-time information corresponding to the local region. The processor performs topological planning to identify on or more topologically distinct classes of trajectories, compute a constraint set for each of the one or more topologically distinct classes of trajectories, optimize a trajectory to generate a candidate trajectory for each constraint set, and select a trajectory for the autonomous vehicle to traverse the local region from amongst the one or more candidate trajectories.

Abstract: An autonomous vehicle navigates an intersection in which occlusions block the vehicle's ability to detect moving objects. The vehicle handles this by generating a phantom obstacle behind the occlusion. The vehicle will predict the speed of the phantom obstacle and use the predicted speed to assess whether the phantom obstacle may collide with the vehicle. If a collision is a risk, the vehicle will slow or stop until it confirms that either (a) the phantom obstacle is not a real obstacle or (b) the vehicle can proceed at a speed that avoids the collision. To determine which occlusions shield real objects, the system may use a rasterized visibility grid of the area to identify occlusions that may accommodate the object.

Abstract: Systems and methods for operating a vehicle. The methods comprise: generating, by a computing device, a vehicle trajectory for the vehicle that is in motion; detecting an object within a given distance from the vehicle; generating, by the computing device, at least one possible object trajectory for the object which was detected; using, by the computing device, the vehicle trajectory and the at least one possible object trajectory to determine whether there is an undesirable level of risk that a collision will occur between the vehicle and the object; modifying, by the computing device, the vehicle trajectory when a determination is made that there is an undesirable level of risk that the collision will occur; and automatically causing the vehicle to move according to the modified vehicle trajectory.

Abstract: Systems and methods for operating a vehicle. The methods comprise: generating, by a computing device, a vehicle trajectory for the vehicle that is in motion; detecting an object within a given distance from the vehicle; generating, by the computing device, at least one possible object trajectory for the object which was detected; performing, by the computing device, a collision check to determine that there remains time to react safely to worst-case behavior by the object (the collision check being based on the vehicle trajectory and at least one possible object trajectory); and performing operations, by the computing device, to selectively cause the vehicle to perform an emergency maneuver based on results of the collision check.

Abstract: Systems and methods for controlling the motion of an autonomous are provided. In one example embodiment, a computer implemented method includes obtaining, by one or more computing devices on-board an autonomous vehicle, data associated with one or more objects that are proximate to the autonomous vehicle. The data includes a predicted path of each respective object. The method includes identifying at least one object as an object of interest based at least in part on the data associated with the object of interest. The method includes generating cost data associated with the object of interest. The method includes determining a motion plan for the autonomous vehicle based at least in part on the cost data associated with the object of interest. The method includes providing data indicative of the motion plan to one or more vehicle control systems to implement the motion plan for the autonomous vehicle.

Abstract: Systems and methods for controlling the motion of an autonomous are provided. In one example embodiment, a computer implemented method includes obtaining, by one or more computing devices on-board an autonomous vehicle, data associated with one or more objects that are proximate to the autonomous vehicle. The data includes a predicted path of each respective object. The method includes identifying at least one object as an object of interest based at least in part on the data associated with the object of interest. The method includes generating cost data associated with the object of interest. The method includes determining a motion plan for the autonomous vehicle based at least in part on the cost data associated with the object of interest. The method includes providing data indicative of the motion plan to one or more vehicle control systems to implement the motion plan for the autonomous vehicle.