Abstract: The present invention relates generally to dispatching transportation to a business location. More specifically, an autonomous vehicle may be dispatched to pick up a passenger and transport that passenger to the business location.

Abstract: Aspects of the disclosure relate to determining and responding to an internal state of a self-driving vehicle. For instance, an image of an interior of the vehicle captured by a camera mounted in the vehicle is received. The image is processed in order to identify one or more visible markers at predetermined locations within the vehicle. The internal state of the vehicle is determined based on the identified one or more visible markers. A responsive action is identified action using the determined internal state, and the vehicle is controlled in order to perform the responsive action.

Abstract: Aspects of the disclosure relate to controlling a vehicle in an autonomous driving mode. The system includes a plurality of sensors configured to generate sensor data. The system also includes a first computing system configured to generate trajectories using the sensor data and send the generated trajectories to a second computing system. The second computing system is configured to cause the vehicle to follow a receive trajectory. The system also includes a third computing system configured to, when there is a failure of the first computer system, generate and send trajectories to the second computing system based on whether a vehicle is located on a highway or a surface street.

Abstract: A vehicle configured to operate in an autonomous mode can obtain sensor data from one or more sensors observing one or more aspects of an environment of the vehicle. At least one aspect of the environment of the vehicle that is not observed by the one or more sensors could be inferred based on the sensor data. The vehicle could be controlled in the autonomous mode based on the at least one inferred aspect of the environment of the vehicle.

Abstract: Aspects of the disclosure relate to validating autonomous control software for operating a vehicle autonomously. For instance, the autonomous control software is run through a driving scenario to observe an outcome for the autonomous control software. A validation model is run through the driving scenario a plurality of times to observe an outcome for the model for each of the plurality of times. Whether the software passed the driving scenario is determined based on whether the outcome for the software indicates that a virtual vehicle under control of the software collided with another object during the single time. Whether the validation model passed the driving scenario is determined based on whether the outcome for the model indicates that a virtual vehicle under control of the model collided with another object in any one of the plurality of times. The software is validated based on the determinations.

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: Aspects of the present disclosure relate to protecting the privacy of a user of a dispatching service for driverless vehicles. For example, a request for a vehicle identifying user information is received. A client computing device may be identified based on the user information. In response to the request, a driverless vehicle may be dispatched to the location of the client device. Signaling information may be generated based on a set of rules including a first rule that the signaling information does not identify, indirectly or directly, the user as well as a second rule that the signaling information does not identify, indirectly or directly, the user information. The location of the client computing device and the signaling information may be sent to the driverless vehicle for display. In addition, the signaling information may also be sent to the client computing device for display.

Abstract: The radar system includes a split-block assembly comprising a first portion and a second portion. The first portion and the second portion form a seam, where the first portion has a top side opposite the seam and the second portion has a bottom side opposite the seam. The system includes at least one port located on a bottom side of the second portion. Additionally, the system includes radiating elements located on the top side of the first portion, wherein the radiating elements are arranged in a plurality of arrays. Yet further, the system includes a set of waveguides in the split-block assembly configured to couple each array to at least one port. Furthermore, the split-block assembly is made from a polymer and where at least the set of waveguides, the at least one port, and the plurality of radiating elements include metal on a surface of the polymer.

Abstract: A method is provided that involves mounting a transmit block and a receive block in a LIDAR device to provide a relative position between the transmit block and the receive block. The method also involves locating a camera at a given position at which the camera can image light beams emitted by the transmit block and can image the receive block. The method also involves obtaining, using the camera, a first image indicative of light source positions of one or more light sources in the transmit block and a second image indicative of detector positions of one or more detectors in the receive block. The method also involves determining at least one offset based on the first image and the second image. The method also involves adjusting the relative position between the transmit block and the receive block based at least in part on the at least one offset.

Abstract: The present disclosure relates to systems and methods that utilize machine learning techniques to improve object classification in thermal imaging systems. In an example embodiment, a method is provided. The method includes receiving, at a computing device, one or more infrared images of an environment. The method additionally includes, applying, using the computing device, a trained machine learning system on the one or more infrared images to determine an identified object type in the environment by at least: determining one or more prior thermal maps associated with the environment; using the one or more prior thermal maps and the one or more infrared images, determining a current thermal map associated with the environment; and determining the identified object type based on the current thermal map. The method also includes providing the identified object type using the computing device.

Abstract: Methods and apparatus are disclosed for customizing driving operations of a vehicle based on occupant(s) of the vehicle. An autonomous vehicle that includes a passenger compartment can determine a presence of an occupant of the passenger compartment. The autonomous vehicle can determine a location of the occupant within the passenger compartment. Additional information about the occupant can be determined. A driving operation can be selected from among a plurality of driving operations based on the location and additional information about the occupant. The selected driving operation can be performed, perhaps by the autonomous vehicle.

Abstract: Examples described may enable provision of remote assistance for an autonomous vehicle. An example method includes a computing system operating in a rewind mode. In the rewind mode, the system may be configured to provide information to a remote assistance operated based on a remote-assistance triggering criteria being met, such as a detected object having a low detection confidence. When the triggering criteria is met, the remote assistance system may provide data from the time leading up to when the remote-assistance triggering criteria was met that was capture of the environment of autonomous vehicle to the remote assistance operator. Based on viewing the data, the remote assistance operator may provide and input to the system that causes a command to be issued to the autonomous vehicle.

Abstract: Example radar systems are presented herein. A radar system may include radiating elements configured to radiate electromagnetic energy and arranged symmetrically in a linear array. The radiating elements comprise a set of radiating doublets and a set of radiating singlets. The radar system also includes a waveguide configured to guide electromagnetic energy between each of the plurality of radiating elements and a waveguide feed. The waveguide feed is coupled to the second side of the waveguide at a center location between a first half of the plurality of radiating elements and a second half of the plurality of radiating elements. The waveguide feed is configured to transfer electromagnetic energy between the waveguide and a component external to the waveguides. The radar system may also include a power dividing network defined by the waveguide and configured to divide the electromagnetic energy transferred by the waveguide feed based on a taper profile.

Abstract: The technology relates to autonomous vehicles having hitched or towed trailers for transporting cargo and other items between locations. Aspects of the technology provide a smart hitch connection between the fifth-wheel of a tractor unit and the kingpin of a trailer. This avoids requiring a person to make physical pneumatic and electrical connections between the fifth-wheel and kingpin using external hoses and cables. Instead, the necessary connections are made internally, autonomously. For instance, the fifth-wheel may provide air pressure via one or more slots arranged on a connection surface, and the trailer is configured to receive the air pressure through one or more openings on a contact surface of the kingpin. An electrical connection section of the fifth-wheel may also provide electrical signals and/or power to an electrical contact interface of the kingpin. Rotational information about relative alignment of the trailer to the tractor unit may also be provided.

Abstract: This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle.

Abstract: Aspects of the present disclosure relate to a system having a memory, a plurality of self-driving systems for controlling a vehicle, and one or more processors. The processors are configured to receive at least one fallback task in association with a request for a primary task and at least one trigger of each fallback task. Each trigger is a set of conditions that, when satisfied, indicate when a vehicle requires attention for proper operation. The processors are also configured to send instructions to the self-driving systems to execute the primary task and receive status updates from the self-driving systems. The processors are configured to determine that a set of conditions of a trigger is satisfied based on the status updates and send further instructions based on the associated fallback task to the self-driving systems.

Abstract: An example circuit includes a plurality of light emitters connected in parallel between a first node and a second node. The circuit also includes a plurality of capacitors, with each capacitor corresponding to one of the light emitters, and a plurality of discharge-control switches, with each discharge-control switches corresponding to one of the capacitors. The circuit further includes a pulse-control switch connected to the plurality of light emitters. During a first period, the pulse-control switch restricts current flow, and each of the plurality of capacitors is charged via the first node. During a second period, one or more of the plurality of discharge-control switches allows current flow that discharges one or more corresponding capacitors. During a third period, the pulse-control switch allows current flow that discharges one or more undischarged capacitors of the plurality of capacitors through one or more corresponding light emitters.

Abstract: Systems and methods are described that relate to a scanning laser system configured to emit laser light and an interlock circuit communicatively coupled to the scanning laser system. The interlock circuit may carry out certain operations. The operations include, as the scanning laser system emits laser light into one or more regions of an environment around the scanning laser system, determining a respective predicted dosage amount for each region based on the emitted laser light. The operations further include detecting an interlock condition. The interlock condition includes a predicted dosage amount for at least one region being greater than a threshold dose. In response to detecting the interlock condition, the operations include controlling the scanning laser system to reduce a subsequent dosage amount in the at least one region.

Abstract: Methods and systems for detection of a construction zone sign are described. A computing device, configured to control the vehicle, may be configured to receive, from an image-capture device coupled to the computing device, images of a vicinity of the road on which the vehicle is travelling. Also, the computing device may be configured to determine image portions in the images that may depict sides of the road at a predetermined height range. Further, the computing device may be configured to detect a construction zone sign in the image portions, and determine a type of the construction zone sign. Accordingly, the computing device may be configured to modify a control strategy associated with a driving behavior of the vehicle; and control the vehicle based on the modified control strategy.