Abstract: The technology relates to controlling a vehicle in an autonomous driving mode. For example, sensor data identifying a plurality of objects may be received. Pairs of objects of the plurality of objects may be identified. For each identified pair of objects of the plurality of objects, a similarity value which indicates whether the objects of that identified pair of objects can be responded to by the vehicle as a group may be determined. The objects of one of the identified pairs of objects may be clustered together based on the similarity score. The vehicle may be controlled in the autonomous mode by responding to each object in the cluster in a same way.

Abstract: A first driving solution for a vehicle along a portion of a route is determined based on an agent detected in the vehicle's environment following a first trajectory of a plurality of possible trajectories. A switching time is determined for the vehicle to deviate from the first driving solution for a situation in which the agent is following a second trajectory of the plurality of possible trajectories. The first driving solution is revised such that the vehicle will be able to switch from the revised first driving solution to another driving solution at the switching time in case if the detected agent is following the second trajectory.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode. In one instance, sensor data identifying an object in an environment of the vehicle may be received. A first path of a first trajectory where the vehicle will pass the object may be determined. A function is used to determining a first maximum speed of the vehicle based on a predetermined minimum lateral clearance between the object and the vehicle. The first maximum speed may be used to determine whether an actual lateral clearance between the object and the vehicle will meet the predetermined minimum lateral clearance. The determination of whether the actual lateral clearance will meet the predetermined minimum lateral clearance may be used to generate a first speed plan for the first trajectory. The vehicle may be controlled in the autonomous driving mode according to the first trajectory including the first speed plan and the first path.

Abstract: Aspects of the disclosure relate to detecting sidewalks adjacent to roads. In this regard, a set of potential sidewalk areas adjacent to one or more roads in a vehicle's vicinity may be determined based on map data. Topology data for the set of potential sidewalk areas may be generated based on sensor data received from a perception system of the vehicle. The set of potential sidewalks may be filtered to remove areas unlikely to include a sidewalk. The vehicle may be operated based on the filtered set of potential sidewalk areas, which may include taking precautionary measures when within a predetermined distance from any of the filtered set of potential sidewalks.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode. For instance, sensor data identifying an object in an environment of the vehicle may be received. A grid including a plurality of cells may be projected around the object. For each given one of the plurality of cells, a likelihood that the object will enter the given one within a period of time into the future is predicted. A contour is generated based on the predicted likelihoods. The vehicle is then controlled in the autonomous driving mode in order to avoid an area within the contour.

Abstract: Aspects of the disclosure relate to generating a speed plan for an autonomous vehicle. As an example, the vehicle is maneuvered in an autonomous driving mode along a route using pre-stored map information. This information identifies a plurality of keep clear regions where the vehicle should not stop but can drive through in the autonomous driving mode. Each keep clear region of the plurality of keep clear regions is associated with a priority value. A subset of the plurality of keep clear regions is identified based on the route. A speed plan for stopping the vehicle is generated based on the priority values associated with the keep clear regions of the subset. The speed plan identifies a location for stopping the vehicle. The speed plan is used to stop the vehicle in the location.

Abstract: The disclosure provides a method for operating an autonomous vehicle. To operate the autonomous vehicle, a plurality of lane segments that are in an environment of the autonomous vehicle is determined and a first object and a second object in the environment are detected. A first position for the first object is determined in relation to the plurality of lane segments, and particular lane segments that are occluded by the first object are determined using the first position. According to the occluded lane segments, a reaction time is determined for the second object and a driving instruction for the autonomous vehicle is determined according to the reaction time. The autonomous vehicle is then operated based on the driving instruction.

Abstract: A system for estimating a spacing profile for a road agent includes a first module and a second module. The first module includes instructions that cause one or more processors to receive data related to characteristics of the road agent and road agent behavior detected in an environment of an autonomous vehicle, initiate an analysis of the road agent behavior, and estimate the spacing profile of the road agent as part of the analysis. The spacing profile includes a lateral gap preference and predicted behaviors of the road agent related to changes in lateral gap. The second module includes instructions that cause the one or more processors to determine one or more components of autonomous vehicle maneuver based on the estimated spacing profile and send control instructions for performing the autonomous vehicle maneuver.

Abstract: The disclosure provides for a method for determining a route for passenger comfort and operating a vehicle according to the determined route. To start, a set of routes from a start location to an end location may be determined. Each route includes one or more portions. For each route of the set of routes, a total motion sickness value is determined based on a sway motion sickness value, a surge motion sickness value, and a heave motion sickness value for each of the given portions. The total motion sickness value for a route reflects a likelihood that a user will experience motion sickness while in a vehicle along the route. A route may then be selected from the set of routes based on the total motion sickness value of each route of the set of routes, and the vehicle may be maneuvered according to the selected route.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode. For example, sensor data identifying a plurality of objects may be received. Pairs of objects of the plurality of objects may be identified. For each identified pair of objects of the plurality of objects, a similarity value which indicates whether the objects of that identified pair of objects can be responded to by the vehicle as a group may be determined. The objects of one of the identified pairs of objects may be clustered together based on the similarity score. The vehicle may be controlled in the autonomous mode by responding to each object in the cluster in a same way.

Abstract: The technology relates to adjusting a trajectory of an autonomous vehicle. In one example, one or more processors are configured to determine a current trajectory and an alternate trajectory of the autonomous vehicle. The one or more processors select a segment of the current trajectory and a segment of the alternate trajectory and determine, for each of the segments, a total expected value of an estimated length of time to traverse the respective segment. The one or more processors may then select one of the segments having the lowest expected value and maneuver the autonomous vehicle along at least a portion of the selected segment.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode. For example, sensor data identifying a plurality of objects may be received. Pairs of objects of the plurality of objects may be identified. For each identified pair of objects of the plurality of objects, a similarity value which indicates whether the objects of that identified pair of objects can be responded to by the vehicle as a group may be determined. The objects of one of the identified pairs of objects may be clustered together based on the similarity score. The vehicle may be controlled in the autonomous mode by responding to each object in the cluster in a same way.

Abstract: The disclosure provides a method for operating an autonomous vehicle. To operate the autonomous vehicle, a plurality of lane segments that are in an environment of the autonomous vehicle is determined and a first object and a second object in the environment are detected. A first position for the first object is determined in relation to the plurality of lane segments, and particular lane segments that are occluded by the first object are determined using the first position. According to the occluded lane segments, a reaction time is determined for the second object and a driving instruction for the autonomous vehicle is determined according to the reaction time. The autonomous vehicle is then operated based on the driving instruction.

Abstract: The technology relates to planning trajectories for self-driving vehicles in order to transport passengers or cargo from a pickup location to a destination. Trajectory planning includes generating a speed plan for an upcoming portion of the trip in view of one or more constraints. The constraints may be due to proximity to an adjacent vehicle or other road user, and can include projected overlaps between the vehicle and other objects in the vehicle's nearby environment. Certain constraints may be binary or otherwise discontinuous in nature, in which a condition either exists at a given point in time or it does not. Noise in sensor data or prediction models may trigger such binary conditions, which in turn may cause the vehicle to alter the speed plan. Aspects of the technology employ permeable speed constraints that enable the vehicle to avoid problems associated with discontinuous constraints.

Abstract: The disclosure provides a method for operating an autonomous vehicle. To operate the autonomous vehicle, a plurality of lane segments that are in an environment of the autonomous vehicle is determined and a first object and a second object in the environment are detected. A first position for the first object is determined in relation to the plurality of lane segments, and particular lane segments that are occluded by the first object are determined using the first position. According to the occluded lane segments, a reaction time is determined for the second object and a driving instruction for the autonomous vehicle is determined according to the reaction time. The autonomous vehicle is then operated based on the driving instruction.

Abstract: Methods, apparatus, systems, and computer-readable media are provided that relate to using one or more vision sensors to capture images of a loaded pallet in association with application of stretch wrap to the loaded pallet by an automated pallet wrapping machine. The images are used to generate an image-based identifier for the loaded pallet that is then used for pallet identification by mobile robots and/or other automated agents in a warehouse or other environment. In some implementations, the images are captured by the vision sensor when the pallet is in the wrapping area of the automated pallet wrapping machine and while the vision sensor and/or the pallet are rotating. In some implementations, the image-based identifier may be assigned to pallet attributes and/or a de-palletizing scheme of the loaded pallet.

Abstract: A first driving solution for a vehicle along a portion of a route is determined based on an agent detected in the vehicle's environment following a first trajectory of a plurality of possible trajectories. A switching time is determined for the vehicle to deviate from the first driving solution for a situation in which the agent is following a second trajectory of the plurality of possible trajectories. The first driving solution is revised such that the vehicle will be able to switch from the revised first driving solution to another driving solution at the switching time in case if the detected agent is following the second trajectory.

Abstract: The technology relates controlling an autonomous vehicle through a multi-lane turn. In one example, data corresponding to a position of the autonomous vehicle in a lane of the multi-lane turn, a trajectory of the autonomous vehicle, and data corresponding to positions of objects in a vicinity of the autonomous vehicle may be received. A determination of whether the autonomous vehicle is positioned as a first vehicle in the lane or positioned behind another vehicle in the lane may be made based on a position of the autonomous vehicle in the lane relative to the positions of the objects. The trajectory of the autonomous vehicle through the lane may be adjusted based on whether the autonomous vehicle is positioned as a first vehicle in the lane or positioned behind another vehicle in the lane. The autonomous vehicle may be controlled based on the adjusted trajectory.

Abstract: The technology relates to controlling a vehicle in an autonomous driving mode. For instance, sensor data identifying an object in an environment of the vehicle may be received. A grid including a plurality of cells may be projected around the object. For each given one of the plurality of cells, a likelihood that the object will enter the given one within a period of time into the future is predicted. A contour is generated based on the predicted likelihoods. The vehicle is then controlled in the autonomous driving mode in order to avoid an area within the contour.

Abstract: Aspects of the disclosure relate to generating a speed plan for an autonomous vehicle. As an example, the vehicle is maneuvered in an autonomous driving mode along a route using pre-stored map information. This information identifies a plurality of keep clear regions where the vehicle should not stop but can drive through in the autonomous driving mode. Each keep clear region of the plurality of keep clear regions is associated with a priority value. A subset of the plurality of keep clear regions is identified based on the route. A speed plan for stopping the vehicle is generated based on the priority values associated with the keep clear regions of the subset. The speed plan identifies a location for stopping the vehicle. The speed plan is used to stop the vehicle in the location.