Abstract: Sensor data identifying an emergency vehicle approaching the autonomous vehicle may be received. A predicted trajectory for the emergency vehicle may be received. Whether the autonomous vehicle is impeding the emergency vehicle may be determined based on the predicted trajectory and map information identifying a road on which the autonomous vehicle is currently traveling. Based on a determination that the autonomous vehicle is impeding the emergency vehicle, the autonomous vehicle may be controlled in an autonomous driving mode in order to respond to the emergency vehicle.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle and a target agent at a current time point; determine whether the target agent is an emergency vehicle that is active at the current time point; generate from the scene features, an input (i) that includes the scene features and (ii) that indicates whether the target vehicle is an emergency vehicle that is active at the current time point; and process the input using a machine learning model that is configured to generate a behavior prediction output for the target agent that characterizes predicted future behavior of the target agent after the current time point.

Abstract: Sensor data identifying an emergency vehicle approaching the autonomous vehicle may be received. A predicted trajectory for the emergency vehicle may be received. Whether the autonomous vehicle is impeding the emergency vehicle may be determined based on the predicted trajectory and map information identifying a road on which the autonomous vehicle is currently traveling. Based on a determination that the autonomous vehicle is impeding the emergency vehicle, the autonomous vehicle may be controlled in an autonomous driving mode in order to respond to the emergency vehicle.

Abstract: Aspects of the disclosure relate to a method of controlling a vehicle having an autonomous driving mode at a multi-way stop intersection. For instance, that the vehicle has come to a stop at a multi-stop intersection may be determined. At least one road user at the intersection may be identified. Based on the determination that the vehicle has come to the stop, a period of time to wait for the at least one road user to proceed through the intersection may be determined. After waiting the determined period of time, that the at least one road user has not begun to proceed through the intersection may be determined. Based on the determination that the at least one user has not begun to proceed through the intersection, the vehicle may be controlled in the autonomous driving mode in order to proceed through the intersection.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle and a target agent at a current time point; determine whether the target agent is an emergency vehicle that is active at the current time point; generate from the scene features, an input (i) that includes the scene features and (ii) that indicates whether the target vehicle is an emergency vehicle that is active at the current time point; and process the input using a machine learning model that is configured to generate a behavior prediction output for the target agent that characterizes predicted future behavior of the target agent after the current time point.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that obtain scene features in an environment that includes an autonomous vehicle, a first target agent, and a second target agent, and determines whether the first target agent is an emergency vehicle that is active at a current time point. In response to determining that the first target agent is an emergency vehicle that is active at the current time point, an input is generated from the scene features. The input can characterize the scene and indicate that the first target agent is an emergency vehicle that is active at the current time point. Also in response, the input can be processed using a machine learning model that is configured to generate a trajectory prediction output for the second target agent that characterizes predicted future behavior of the second target agent after the current time point.

Abstract: Aspects of the disclosure may enable autonomous vehicles to respond to emergency vehicles. For instance, sensor data identifying an emergency vehicle approaching the autonomous vehicle may be received. A predicted trajectory for the emergency vehicle may be received. Whether the autonomous vehicle is impeding the emergency vehicle may be determined based on the predicted trajectory and map information identifying a road on which the autonomous vehicle is currently traveling. Based on a determination that the autonomous vehicle is impeding the emergency vehicle, the autonomous vehicle may be controlled in an autonomous driving mode in order to respond to the emergency vehicle.

Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle having an autonomous driving mode. For instance, sensor data generated by a perception system of a vehicle may be received. The sensor data identifying objects in an environment of the vehicle. A trajectory corresponding to a future path of the vehicle may be received. That the vehicle is approaching an unmarked crosswalk situation may be determined based on the trajectory and the sensor data. In response to the determination, an area for an unmarked crosswalk is identified. The vehicle may be controlled in the autonomous driving mode based on the determination and the area.

Abstract: Aspects of the disclosure relate to a method of controlling a vehicle having an autonomous driving mode at a multi-way stop intersection. For instance, that the vehicle has come to a stop at a multi-stop intersection may be determined. At least one road user at the intersection may be identified. Based on the determination that the vehicle has come to the stop, a period of time to wait for the at least one road user to proceed through the intersection may be determined. After waiting the determined period of time, that the at least one road user has not begun to proceed through the intersection may be determined. Based on the determination that the at least one user has not begun to proceed through the intersection, the vehicle may be controlled in the autonomous driving mode in order to proceed through the intersection.

Abstract: Aspects of the disclosure relate to a method of controlling a vehicle having an autonomous driving mode at a multi-way stop intersection. For instance, that the vehicle has come to a stop at a multi-stop intersection may be determined. At least one road user at the intersection may be identified. Based on the determination that the vehicle has come to the stop, a period of time to wait for the at least one road user to proceed through the intersection may be determined. After waiting the determined period of time, that the at least one road user has not begun to proceed through the intersection may be determined. Based on the determination that the at least one user has not begun to proceed through the intersection, the vehicle may be controlled in the autonomous driving mode in order to proceed through the intersection.

Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle having an autonomous driving mode. For instance, sensor data generated by a perception system of a vehicle may be received. The sensor data identifying objects in an environment of the vehicle. A trajectory corresponding to a future path of the vehicle may be received. That the vehicle is approaching an unmarked crosswalk situation may be determined based on the trajectory and the sensor data. In response to the determination, an area for an unmarked crosswalk is identified. The vehicle may be controlled in the autonomous driving mode based on the determination and the area.

Abstract: Aspects of the disclosure relate to a method of controlling a vehicle having an autonomous driving mode at a multi-way stop intersection. For instance, that the vehicle has come to a stop at a multi-stop intersection may be determined. At least one road user at the intersection may be identified. Based on the determination that the vehicle has come to the stop, a period of time to wait for the at least one road user to proceed through the intersection may be determined. After waiting the determined period of time, that the at least one road user has not begun to proceed through the intersection may be determined. Based on the determination that the at least one user has not begun to proceed through the intersection, the vehicle may be controlled in the autonomous driving mode in order to proceed through the intersection.