Abstract: A vehicle configured to operate in an autonomous mode is provided. The vehicle is configured to obtain an indication of a final destination, and, if the final destination is not on a pre-approved road for travel by the vehicle, the vehicle is configured to determine a route from the vehicle's current location to an intermediary destination. The vehicle is further configured to determine a means for the vehicle user to reach the final destination from the intermediate destination.

Abstract: The present disclosure relates to systems and methods relating to the fabrication of light guide elements. An example system includes an optical component configured to direct light emitted by a light source to illuminate a photoresist material at one or more desired angles so as to expose an angled structure in the photoresist material. The photoresist material overlays at least a portion of a first surface of a substrate. The optical component includes a container containing a light-coupling material that is selected based in part on the one or more desired angles. The system also includes a reflective surface arranged to reflect at least a first portion of the emitted light to illuminate the photoresist material at the one or more desired angles.

Abstract: Systems and methods described herein relate to the manufacture of optical elements and optical systems. An example system may include an optical component configured to direct light from a light source to illuminate a photoresist material at a desired angle and to expose at least a portion of an angled structure in the photoresist material, where the photoresist material overlays at least a portion of a top surface of a substrate. The optical component includes a container containing an light-coupling material that is selected based in part on the desired angle. The optical component also includes a mirror arranged to reflect at least a portion of the light to illuminate the photoresist material at the desired angle.

Abstract: The present disclosure relates to devices, systems, and methods relating to configurable silicon photomultiplier (SiPM) devices. An example device includes a substrate and a plurality of single photon avalanche diodes (SPADs) coupled to the substrate. The device also includes a plurality of outputs coupled to the substrate and a plurality of electrical components coupled to the substrate. The plurality of electrical components are configured to selectively connect the plurality of SPADs to the plurality of outputs by selecting which output of the plurality of outputs is connected to each SPAD of the plurality of SPADs and to thereby define a plurality of SiPMs in the device such that each SiPM of the plurality of SiPMs comprises a respective set of one or more SPADs connected to a respective output of the plurality of outputs.

Abstract: Aspects of the disclosure relate to models for estimating the likelihood of fatigue in test drivers. In some instances, training data including videos of the test drivers while such test drivers are tasked with monitoring driving of a vehicle operating in an autonomous driving mode may be identified. The training data also includes driver drowsiness values generated from one or more human operators observing the videos. The training inputs and outputs may be used to train the model such that when a new video of a first test driver is input into the model, the model will output an estimate of a likelihood of fatigue for that test driver.

Abstract: The technology relates to autonomous vehicles having articulating sections such as the trailer of a tractor-trailer. Aspects include approaches for tracking the pose of the trailer, including its orientation relative to the tractor unit. Sensor data is analyzed from one or more onboard sensors to identify and track the pose. The pose information is usable by on-board perception and/or planning systems when driving the vehicle in an autonomous mode. By way of example, on-board sensors such as Lidar sensors are used to detect the real-time pose of the trailer based on Lidar point cloud data. The orientation of the trailer is estimated based on the point cloud data, and the pose is determined according to the orientation and other information about the trailer. Aspects also include determining which side of the trailer the sensor data is coming from. A camera may also detect trailer marking information to supplement the analysis.

Abstract: A system and method include scanning a light detection and ranging (LIDAR) device through a range of orientations corresponding to a scanning zone while emitting light pulses from the LIDAR device. The method also includes receiving returning light pulses corresponding to the light pulses emitted from the LIDAR device and determining initial point cloud data based on time delays between emitting the light pulses and receiving the corresponding returning light pulses and the orientations of the LIDAR device. The initial point cloud data has an initial angular resolution. The method includes identifying, based on the initial point cloud data, a reflective feature in the scanning zone and determining an enhancement region and an enhanced angular resolution for a subsequent scan to provide a higher spatial resolution in at least a portion of subsequent point cloud data from the subsequent scan corresponding to the reflective feature.

Abstract: The disclosure relate to determining a realism metric for testing software for operating a vehicle in an autonomous driving mode. For instance, a plurality of versions of a simulation may be run using log data collected by a vehicle operating in an autonomous driving mode. The plurality of versions may be run using the software to control a simulated vehicle, and each of the plurality of versions may have a set of timing requirements different from the set of timing requirements of other of the plurality of versions. Results of the plurality of versions may be compared to the log data. A realism metric defining timing requirements for one or more future simulations may be generated based on the comparison.

Abstract: Aspects of the disclosure relate to controlling a vehicle in an autonomous driving mode. For instance, a trajectory is identified. The trajectory defines a future desired path for the vehicle and includes a control requirement having a corresponding point in time. A command for achieving the control requirement is generated. A fixed delay value corresponding to a delay caused by transmission of the command to an actuator of the vehicle is generated. A variable delay value corresponding to a delay caused by an amount of time to change a physical state of the actuator to a desired state according to the command is generated. The command is then sent to the actuator based on the fixed delay value, the variable delay value, and so that the actuator causes the vehicle to move according to the command.

Abstract: One example system comprises a substrate and a waveguide disposed on the substrate to define an optical path on the substrate. The waveguide is configured to guide, inside the waveguide and along the optical path, a light signal toward an edge of the waveguide. The edge defines an optical interface between the waveguide and a fluidic optical medium adjacent to the edge of the waveguide. The system also includes an optical fluid and a fluid actuator configured to adjust a physical state of the optical fluid based on a control signal. The adjustment of the physical state of the optical fluid causes an adjustment of the fluidic optical medium adjacent to the edge.

Abstract: Aspects of the disclosure relate to training and using a model for verifying accuracy of ICP alignments or alignments between data points using an iterative closest point algorithm. For instance, a model may be trained using ICP alignment data, including alignments between an object appearing in LIDAR sensor frames. The training may also include setting a definition for a trusted ICP alignment. In this regard, the model may be trained such that, n response to receiving additional LIDAR sensor frames and corresponding additional ICP alignment data, output a value indicative of whether the additional ICP alignment data is trusted according to the definition. The model may then be used to control a vehicle in an autonomous driving mode by determining whether alignment data for object determined using the ICP algorithm should be trusted.

Abstract: Aspects of the disclosure relate controlling autonomous vehicles or vehicles having an autonomous driving mode. More particularly, these vehicles may identify and respond to other vehicles engaged in a parallel parking maneuver by receiving sensor data corresponding to objects in an autonomous vehicle's environment and including location information for the objects over time. An object corresponding to another vehicle in a lane in front of the first vehicle may be identified from the sensor data. A pattern of actions of the other vehicle identified form the sensor data is used to determine that the second vehicle is engaged in a parallel parking maneuver based on a pattern of actions exhibited by the other vehicle identified from the sensor data. The determination is then used to control the autonomous vehicle.

Abstract: An example method involves detecting a sensor-testing trigger. Detecting the sensor-testing trigger may comprise determining that a vehicle is within a threshold distance to a target in an environment of the vehicle. The method also involves obtaining sensor data collected by a sensor of the vehicle after the detection of the sensor-testing trigger. The sensor data is indicative of a scan of a region of the environment that includes the target. The method also involves comparing the sensor data with previously-collected sensor data indicating detection of the target by one or more sensors during one or more previous scans of the environment. The method also involves generating performance metrics related to the sensor of the vehicle based on the comparison.

Abstract: The disclosure provides for a system that includes a seat mounted in a vehicle. The seat includes a base, a back support, a hinge, and a seat belt integrated into the seat. The back support is capable of rotating relative to the base and thereby reclining. The hinge is between the base and the back support and is configured to lock the back support in positions in relation to the base. The seat belt has a shoulder portion and a lap portion and is attached to the seat at a shoulder anchor in the back support and a base anchor in the base. When a generated torque, created from a forward force applied by the shoulder portion of the seat belt, exceeds a threshold amount of torque, the hinge is configured to unlock and back support is configured to rotate forward from a reclined position towards an upright position.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating object detection predictions from a neural network. In some implementations, an input characterizing a first region of an environment is obtained. The input includes a projected laser image generated from a three-dimensional laser sensor reading of the first region, a camera image patch generated from a camera image of the first region, and a feature vector of features characterizing the first region. The input is processed using a high precision object detection neural network to generate a respective object score for each object category in a first set of one or more object categories. Each object score represents a respective likelihood that an object belonging to the object category is located in the first region of the environment.

Abstract: The technology relates to generating a representation of an object detected by a perception system of a vehicle. For instance, a set of data points corresponding to an object is received from the perception system. Map information identifying shapes and locations of lanes as well as locations of center points for the lanes is retrieved. A representative point of the center points is selected based on the set of data points. A first position is determined based on the location of the representative point. A second position is determined based on the set of data points. The first and second positions are used to determine a third position for a representation of the object based on a distance the first position and the second position. The he representation of the object is generated using the third position. The representation of the object is displayed on a display of the vehicle.

Abstract: A method and apparatus are provided for optimizing one or more object detection parameters used by an autonomous vehicle to detect objects in images. The autonomous vehicle may capture the images using one or more sensors. The autonomous vehicle may then determine object labels and their corresponding object label parameters for the detected objects. The captured images and the object label parameters may be communicated to an object identification server. The object identification server may request that one or more reviewers identify objects in the captured images. The object identification server may then compare the identification of objects by reviewers with the identification of objects by the autonomous vehicle. Depending on the results of the comparison, the object identification server may recommend or perform the optimization of one or more of the object detection parameters.