Abstract: The technology relates to a seamless interface between an autonomous vehicle service provider and one or more ridesharing, ride-hailing or delivery partner companies, in order to provide timely, efficient rider or delivery services and support. A partner trip application programming interface (API) provides robust features to the ridesharing or ride-hailing partner companies and also supports delivery of meals, groceries, packages or other cargo. For instance, the API may be employed with delivery partners (e.g., food, package or bulk cargo delivery), and/or for concierge services (e.g., a hotel or medical provider or an e-commerce specialist that coordinates deliveries). The technology supports both ad hoc and scheduled trips. Agents for different partners may schedule trips to or from specific stores or other (geofenced) locations, and observe and manage trips for an entire enterprise. Permissions can be tailored for each agent.

Abstract: Assessing a likelihood of a person experiencing a fatigue event when the person tasked with monitoring a vehicle operating in an autonomous driving mode may include receiving a set of response times for a psychomotor vigilance test administered to the person. The test may include a plurality of trials which involve a person lifting a finger from a user input device. Whether the person passed or failed each trial of the set of trials may be determined. A model trained using data from prior psychomotor vigilance tests administered to the person may be identified for the person. Results of the determinations of whether the person passed or failed each trial of the set of trials may be input into the model in order to determine a value representative of a likelihood of a fatigue event. An intervention response may be initiated based on the value.

Abstract: Assessing a likelihood of a person experiencing a fatigue event when the person tasked with monitoring a vehicle operating in an autonomous driving mode may include receiving a set of response times for a psychomotor vigilance test administered to the person. The test may include a plurality of trials which involve a person lifting a finger from a user input device. Whether the person passed or failed each trial of the set of trials may be determined. A model trained using data from prior psychomotor vigilance tests administered to the person may be identified for the person. Results of the determinations of whether the person passed or failed each trial of the set of trials may be input into the model in order to determine a value representative of a likelihood of a fatigue event. An intervention response may be initiated based on the value.

Abstract: The disclosure relates to controlling a vehicle having an autonomous driving mode. An example method may include identifying a pullover location for the vehicle. As the vehicle approaches the pullover location, information identifying one or more road users may be received. A behavior prediction for each of the one or more road users may be received. One of one of the one or more road users may be identified based on the received behavior predictions for each of the one or more road users and a collision zone for the vehicle. After waiting for the identified one to pass the vehicle, the vehicle may be maneuvered in the autonomous driving mode into the pullover location.

Abstract: Aspects of the disclosure relates to providing deliveries of goods using autonomous vehicles. For instance, a first request for goods identifying a delivery location may be used to send a second request for an autonomous vehicle to deliver the goods to the delivery location. A first notification indicating that the autonomous vehicle has been loaded with the one or more goods at a loading location may be received. A second notification indicating arrival of the autonomous vehicle at the delivery location may be received. In response to receiving the second notification, a third notification may be sent indicating that the one or more goods has arrived at the delivery location. In response, a third request to open a door of the autonomous vehicle may be received. In response, a signal may be sent in order to unlock or open the door and provide access to the one or more goods.

Abstract: Assessing a likelihood of a person experiencing a fatigue event when the person tasked with monitoring a vehicle operating in an autonomous driving mode may include receiving a set of response times for a psychomotor vigilance test administered to the person. The test may include a plurality of trials which involve a person lifting a finger from a user input device. Whether the person passed or failed each trial of the set of trials may be determined. A model trained using data from prior psychomotor vigilance tests administered to the person may be identified for the person. Results of the determinations of whether the person passed or failed each trial of the set of trials may be input into the model in order to determine a value representative of a likelihood of a fatigue event. An intervention response may be initiated based on the value.