Abstract: The present disclosure relates to systems and methods for determining a range and relative speed of objects in an environment. An example method includes causing a laser light source to emit a plurality of light pulses, both incoherent and coherent. The light pulses interact with an environment to provide reflected light pulses. The method includes providing a local oscillator signal based on a coherent light pulse. The method also includes receiving, at a detector, the reflected light pulses, and the local oscillator signal. The method additionally includes determining, based on at least one of the reflected light pulses, a presence of an object in the environment. The method yet further includes determining, based on another reflected light pulse and the local oscillator signal, a relative speed of the object with respect to the detector.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a representation of a trajectory of a target agent in an environment. In one aspect, the representation of the trajectory of the target agent in the environment is a concatenation of a plurality of channels, where each channel is represented as a two-dimensional array of data values. Each position in each channel corresponds to a respective spatial position in the environment, and corresponding positions in different channels correspond to the same spatial position in the environment. The channels include a time channel and a respective motion channel corresponding to each motion parameter in a predetermined set of motion parameters.

Abstract: Aspects and implementations of the present disclosure address shortcomings of the existing technology by enabling routing of an autonomous vehicles (AV) by identifying routes from a first location to a second location, identifying a target efficiency value of autonomous driving along a respective route, determining, in view of historical data for the respective route and using one or more randomized conditions, a confidence level associated with the target efficiency value, selecting, based on the target efficiency values and the associated confidence level, a preferred route, and causing the AV to select the first route for travel from the first location to the second location.

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 present disclosure relates to systems and methods that facilitate compliance of a laser device with a laser safety threshold. An example method includes receiving, from a sensing circuit, an operating voltage that is indicative of a charge of a capacitive element of a laser pulser circuit. The method also includes comparing a first voltage indicative of the operating voltage and a second voltage indicative of a reference voltage. The method additionally includes providing an output value based on the comparing. The method yet further includes evaluating compliance with the laser safety threshold based on the output value.

Abstract: The technology provides an interior camera sensing system for self-driving vehicles. The sensor system includes image sensors and infrared illuminators to see the vehicle's cabin and storage areas in all ambient lighting conditions. The system can monitor the vehicle for safety purposes, to detect the cleanliness of the cabin and storage areas, as well as to detect whether packages or other objects have been inadvertently left in the vehicle. The cameras are arranged to focus on selected regions in the vehicle cabin and the system carries out certain actions in response to information evaluated for those regions. The interior space is divided into multiple zones assigned different coverage priorities. Regardless of vehicle size or configuration, certain actions are performed according to various ride checklists and the imagery detected by the interior cameras. The checklists include pre-ride, mid-ride, and post-ride checklists.

Abstract: The technology relates to cargo vehicles. National, regional and/or local regulations set requirements for operating cargo vehicles, including how to distribute and secure cargo, and how often the cargo should be inspected during a trip. However, such regulations have been focused on traditional human-driven vehicles. Aspects of the technology address various issues involved with securement and inspection of cargo before a trip, as well as monitoring during the trip so that corrective action may be taken as warranted. For instance, imagery and other sensor information may be used to enable proper securement of cargo before starting a trip. Onboard sensors along the vehicle monitor the cargo and securement devices/systems during the trip to identify issues as they arise. Such information is used by the onboard autonomous driving system (or a human driver) to take corrective action depending on the nature of the issue.

Abstract: Example embodiments described herein involve a system for testing a light-emitting module. The light-emitting module may include a mounting platform configured to hold a light-emitting module for a camera. The mounting platform may also be configured to rotate. The system may further include a housing holding a plurality of photodiodes arranged in an array over at least a 90 degree arc of a hemisphere. The system may also include a controller configured to control the photodiodes and the rotation of the mounting platform.

Abstract: A Printed Circuit Board (PCB) includes a via extending through at least one layer of the PCB. The PCB may also include a first catch pad connected to the via and located within a first metal layer of the PCB. The first catch pad may have a first size. The PCB may further include a second catch pad connected to the via and located within a second metal layer of the PCB. The second catch pad may have a second size greater than the first size. The second catch pad may overlap horizontally with a portion of a metallic feature in the first metal layer to obstruct light incident on a first side of the PCB from transmission to a second side of the PCB through a region of dielectric material near the via.

Abstract: A portable sensor calibration target includes a frame assembly, a first panel, and a second panel. The frame assembly may include three legs and a plurality of frame edges that is configured to form a first frame and a second frame and is configured to be held at a pre-selected height above ground by the legs. The first panel is removably attached to the first frame in an unfolded position, and includes a plurality of boards and a plurality of hinges connecting the plurality of boards. The first panel is configured to fold at the plurality of hinges into a folded position. The second panel is removably attached to the second frame adjacent to the first frame. The first panel and the second panel meet to form an edge, which is detectable by a detection system of a vehicle for calibrating the detection system.

Abstract: Aspects of the disclosure relate to generating assets for a simulation in order to test autonomous vehicle control software. For instance, data identifying a vehicle object, a polygon for the vehicle object, and a polygon for an open-door object associated with the vehicle object may be received. A rectangle may be fit to the polygon for the vehicle object. A polygon for the vehicle object without the open-door object may be determined based on the rectangle. A vehicle asset representing a vehicle may be adjusted based on the polygon for the vehicle object without the open-door object. A position and rotation of the rectangle may be used to position an open-door asset representing an open door for the simulation. The open-door asset is adjusted based on the adjustment to the vehicle asset. The simulation may be run with the positioned and adjusted open door asset in order to test the autonomous vehicle control software.

Abstract: One example device comprises a plurality of emitters including at least a first emitter and a second emitter. The first emitter emits light that illuminates a first portion of a field-of-view (FOV) of the device. The second emitter emits light that illuminates a second portion of the FOV. The device also comprises a controller that obtains a scan of the FOV. The controller causes each emitter of the plurality of emitters to emit a respective light pulse during an emission time period associated with the scan. The controller causes the first emitter to emit a first-emitter light pulse at a first-emitter time offset from a start time of the emission time period. The controller causes the second emitter to emit a second-emitter light pulse at a second-emitter time offset from the start time of the emission time period.

Abstract: Methods and devices for using a relationship between activities of different traffic signals in a network to improve traffic signal state estimation are disclosed. An example method includes determining that a vehicle is approaching an upcoming traffic signal. The method may further include determining a state of one or more traffic signals other than the upcoming traffic signal. Additionally, the method may also include determining an estimate of a state of the upcoming traffic signal based on a relationship between the state of the one or more traffic signals other than the upcoming traffic signal and the state of the upcoming traffic signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for planning a trajectory of a vehicle. One of the methods includes obtaining input data for planning a driving trajectory for a vehicle, the input data comprising an intended route for the vehicle and data characterizing an environment in a vicinity of the vehicle; processing the input data using an input encoder neural network to generate feature data that includes a respective feature representation for each of a plurality of locations in the environment; applying spatial attention to the feature representations to generate a respective attention weight for each of the plurality of locations; generating a respective attended feature representation for each of the plurality of locations; generating a bottlenecked representation of the attended feature representations; and generating a planned future trajectory from at least the bottlenecked representation.

Abstract: An example apparatus may include a first plate having a first side. A first plurality of fins may be integral with the first side of the first plate and protruding perpendicularly therefrom. The first plurality of fins may be arranged in first concentric circles separated radially by a first distance. The apparatus may also include a second plate having a first side. The second plate may be rotatably coupled to the first plate. A second plurality of fins may be integral with the first side of the second plate and protruding perpendicularly therefrom. The second plurality of fins may be arranged in second concentric circles separated radially by the first distance. Each fin of the second plurality of fins may interpose between adjacent fins of the first plurality of fins to transfer heat between the second plate and the first plate.

Abstract: Aspects of the disclosure relate to training and using a phrase recognition model to identify phrases in images. As an example, a selected phrase list may include a plurality of phrases is received. Each phrase of the plurality of phrases includes text. An initial plurality of images may be received. A training image set may be selected from the initial plurality of images by identifying the phrase-containing images that include one or more phrases from the selected phrase list. Each given phrase-containing image of the training image set may be labeled with information identifying the one or more phrases from the selected phrase list included in the given phrase-containing images. The model may be trained based on the training image set such that the model is configured to, in response to receiving an input image, output data indicating whether a phrase of the plurality of phrases is included in the input image.

Abstract: Example embodiments relate to selective deactivation of light emitters for interference mitigation in light detection and ranging (lidar) devices. An example method includes deactivating one or more light emitters within a lidar device during a firing cycle. The method also includes identifying whether interference is influencing measurements made by the lidar device. Identifying whether interference is influencing measurements made by the lidar device includes determining, for each light detector of the lidar device that is associated with the one or more light emitters deactivated during the firing cycle, whether a light signal was detected during the firing cycle.