The technology relates to approaches for determining appropriate stopping locations at intersections for vehicles operating in a self-driving mode. While many intersections have stop lines painted on the roadway, many others have no such lines. Even if a stop line is present, the physical location may not match what is in store map data, which may be out of date due to construction or line repainting. Aspects of the technology employ a neural network that utilizes input training data and detected sensor data to perform classification, localization and uncertain estimation processes. Based on these processes, the system is able to evaluate distribution information for possible stop locations. The vehicle uses such information to determine an optimal stop point, which may or may not correspond to a stop line in the map data. This information is also used to update the existing map data, which can be shared with other vehicles.
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p.ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
2.
Systems, Apparatus, and Methods for Retrieving Image Data of Image Frames
Described examples relate to an apparatus comprising a memory for storing a sequence of image frames and at least one processor. The at least one processor may be configured to receive a first image frame of a sequence of image frames from an image capture device and select a first portion of a first image frame. The at least one processor may also be configured to obtain alignment information and determine a first portion and a second portion of a second image frame based on the alignment information. Further, the at least one processor may be configured to determine a bounding region within the second image frame and fetch image data corresponding to the bounding region of the second image frame from memory. In some examples, the first image frame may comprise a base image and the second image frame may comprise an alternative image frame. Further, the first image frame may comprise any one of the image frames of the sequence of image frames.
G06T 7/33 - Détermination des paramètres de transformation pour l'alignement des images, c. à d. recalage des images utilisant des procédés basés sur les caractéristiques
G06T 7/55 - Récupération de la profondeur ou de la forme à partir de plusieurs images
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p.ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersections; Analyse de connectivité, p.ex. de composantes connectées
3.
POINT CLOUD SEGMENTATION USING A COHERENT LIDAR FOR AUTONOMOUS VEHICLE APPLICATIONS
Aspects and implementations of the present disclosure address shortcomings of the existing technology by enabling Doppler-assisted segmentation of points in a point cloud for efficient object identification and tracking in autonomous vehicle (AV) applications, by: obtaining, by a sensing system of the AV, a plurality of return points comprising one or more velocity values and one or more coordinates of a reflecting region that reflects a signal emitted by the sensing system, the one or more velocity values and the one or more coordinates obtained for the same instance of time, identifying that the set of the return points is associated with an object in an environment, and causing a driving path of the AV to be determined in view of the object.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model on training data. In one aspect, one of the methods include: obtaining a training data set comprising a plurality of training inputs; obtaining data defining an original search space of a plurality of candidate data augmentation policies; generating, from the original search space, a compact search space that has one or more global hyperparameters; and training the machine learning model on the training data using one or more final data augmentation policies generated from the compact search space.
Example embodiments relate to a substrate integrated waveguide (SIW) with dual circular polarizations. An example SIW may include a dielectric substrate and a first metallic layer coupled to a top surface of the dielectric substrate with a through-hole extending through the dielectric substrate and the first metallic layer. The SIW also includes a dielectric layer coupled to a top surface of the first metallic layer. A second metallic layer is coupled to a top surface of the dielectric layer. The second metallic layer includes a non-conductive opening, a plurality of feeds with a first end in the non-conductive opening and a second end including a single-ended termination, and an impedance transformer. The SIW also includes a third metallic layer coupled to a bottom of the dielectric substrate, and a set of metallic via-holes proximate the non-conductive opening and coupling the second metallic layer to the third metallic layer.
H01Q 21/24 - Combinaisons d'unités d'antennes polarisées dans des directions différentes pour émettre ou recevoir des ondes polarisées circulairement ou elliptiquement ou des ondes polarisées linéairement dans n'importe quelle direction
The technology relates to detecting water or fouling on the exterior surface of a sensor cover, for instance due to precipitation or debris (fouling). Such objects on the sensor cover surface may degrade operation of the sensor, which can be problematic for vehicles operating in an autonomous driving mode. According to an aspect of the technology, a waveguide layer is provided on the sensor cover. A laser emits light at a selected wavelength along one side of the waveguide layer. The light waveform propagating along the waveguide layer is affected (distorted) by precipitation and/or fouling on the surface of this layer. A detector receives the distorted waveform. The system determines whether water and/or fouling is present based on the received waveform. This allows the system to determine whether to activate a cleaning module or to factor in the information when processing received sensor data.
B60S 1/02 - Nettoyage des pare-brise, fenêtres ou dispositifs optiques
B60W 50/02 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour préserver la sécurité en cas de défaillance du système d'aide à la conduite, p.ex. en diagnostiquant ou en palliant à un dysfonctionnement
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G01N 21/94 - Recherche de souillures, p.ex. de poussières
G01S 17/931 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
8.
RESPONDING TO EMERGENCY VEHICLES FOR AUTONOMOUS VEHICLES
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.
To operate an autonomous vehicle, a rail agent is detected in a vicinity of the autonomous vehicle using a detection system. One or more tracks are determined on which the detected rail agent is possibly traveling, and possible paths for the rail agent are predicted based on the determined one or more tracks. One or more motion paths are determined for one or more probable paths from the possible paths, and a likelihood for each of the one or more probable paths is determined based on each motion plan. A path for the autonomous vehicle is then determined based on a most probable path associated with a highest likelihood for the rail agent, and the autonomous vehicle is operated using the determined path.
G05D 1/617 - Sécurité ou protection, p. ex. définition de zones de protection autour d’obstacles ou évitement de zones dangereuses (dispositions de commande de la position ou du cap de plusieurs véhicules afin d’éviter toute collision entre les véhicules G05D 1/693;dispositions visant à réagir aux défaillances du système ou d’origine humaine ou à les prévenir G05D 1/80)
G05D 1/228 - Dispositions d’entrée de commande situées à bord de véhicules sans pilote
Aspects of the disclosure relate to generating scouting objectives in order to update map information used to control a fleet of vehicles in an autonomous driving mode. For instance, a notification from a vehicle of the fleet identifying a feature and a location of the feature may be received. A first bound for a scouting area may be identified based on the location of the feature. A second bound for the scouting area may be identified based on a lane closest to the feature. A scouting objective may be generated for the feature based on the first bound and the second bound.
Systems and methods for extrinsic calibration of vehicle-mounted sensors are provided. One example method involves obtaining first sensor data collected by a first sensor and a second sensor while a vehicle is aligned in a first yaw direction. The method also involves obtaining second sensor data collected by the first sensor and the second sensor while the vehicle is aligned in a second yaw direction. The method also involves determining, based on the first sensor data and the second sensor data, (i) first pitch and roll misalignments of the first sensor relative to the vehicle and (ii) second pitch and roll misalignments of the second sensor relative to the first sensor. The method also involves determining third pitch and roll misalignments of the second sensor relative to the vehicle based on (i) the first pitch and roll misalignments and (ii) the second pitch and roll misalignments.
G01C 25/00 - Fabrication, étalonnage, nettoyage ou réparation des instruments ou des dispositifs mentionnés dans les autres groupes de la présente sous-classe
G01C 21/16 - Navigation; Instruments de navigation non prévus dans les groupes en utilisant des mesures de la vitesse ou de l'accélération exécutées à bord de l'objet navigant; Navigation à l'estime en intégrant l'accélération ou la vitesse, c. à d. navigation par inertie
Example embodiments relate to techniques for adjusting vehicle behavior based on estimated unintentional lateral movements. A computing system may receive sensor data representing a truck's environment as the truck pulls a trailer and navigates above a threshold speed on a freeway or another type of road. The computing system may use the sensor data to detect another truck navigating in an adjacent lane and at a speed that indicates an increased likelihood of a pass maneuver occurring between the trucks. Responsive to determining the increased likelihood of the pass maneuver occurring between the vehicles, the computing system may estimate an unintentional lateral movement for the pass maneuver based on parameters that can include the truck's speed, the size of the other truck's trailer, and a wind condition of the environment. The computing system can subsequently control the truck based on estimated unintentional lateral movement for the pass maneuver.
Described examples relate to an apparatus comprising one or more image sensors coupled to a vehicle and at least one processor. The at least one processor may be configured to capture, in a burst sequence using the one or more image sensors, multiple frames of an image of a scene, the multiple frames having respective, relative offsets of the image across the multiple frames and perform super-resolution computations using the captured, multiple frames of the image of the scene. The at least one processor may also be configured to accumulate, based on the super-resolution computations, color planes and combine, using the one or more processors, the accumulated color planes to create a super-resolution image of the scene.
The present disclosure relates to devices, lidar systems, and vehicles that include optical redirectors. An example lidar system includes a transmitter and a receiver. The transmitter includes at least one light-emitter device configured to transmit emission light into an environment. The receiver is configured to detect return light from the environment and includes a plurality of apertures, a plurality of photodetectors, and a plurality of optical redirectors. Each optical redirector is configured to optically couple a respective portion of return light from a respective aperture to at least one photodetector of the plurality of photodetectors. Each optical redirector also has a rotational orientation relative to other optical redirectors such that the redirection paths of optical redirectors that correspond to adjacent apertures are not coplanar with one another.
Aspects of the disclosure relate to reducing the likelihood of injury to a passenger in a collision. In one example, a computing device may determine that an impact between a vehicle and an object external to the vehicle is imminent. The computing device may determine a protection range for a vehicle's airbag based on characteristics of the passenger, including the passenger's seating location within the vehicle. An airbag extension system may position an airbag package, including the vehicle's airbag, such that the vehicle's airbag is within the protection range of the passenger's seating location.
B60R 21/20 - Dispositions pour ranger les éléments gonflables non utilisés ou à l'état dégonflé; Agencement ou montage des composants ou modules des coussins gonflables
B60R 21/0134 - Circuits électriques pour déclencher le fonctionnement des dispositions de sécurité en cas d'accident, ou d'accident imminent, de véhicule comportant des moyens pour détecter les collisions, les collisions imminentes ou un renversement réagissant à un contact imminent avec un obstacle
B60R 21/015 - Circuits électriques pour déclencher le fonctionnement des dispositions de sécurité en cas d'accident, ou d'accident imminent, de véhicule comportant des moyens pour détecter la présence ou la position des passagers, des sièges des passagers ou des sièges pour enfants, p.ex. pour mettre hors service le déclenchement
B60R 21/264 - Moyens gonflables de retenue ou d'immobilisation des occupants prévus pour se gonfler lors d'un choc ou en cas de choc imminent, p.ex. sacs gonflables caractérisés par la source de fluide de gonflage ou par les moyens de commande de l'écoulement du fluide de gonflage utilisant une génération instantanée de gaz, p.ex. pyrotechnique
19.
Handling sensor occlusions for autonomous vehicles
The technology relates to identifying sensor occlusions due to the limits of the ranges of a vehicle's sensors and using this information to maneuver the vehicle. As an example, the vehicle is maneuvered along a route that includes traveling on a first roadway and crossing over a lane of a second roadway. A trajectory is identified from the lane that will cross with the route during the crossing at a first point. A second point beyond a range of the vehicle's sensors is selected. The second point corresponds to a hypothetical vehicle moving towards the route along the lane. A distance between the first point and the second point is determined. An amount of time that it would take the hypothetical vehicle to travel the distance is determined and compared to a threshold amount of time. The vehicle is maneuvered based on the comparison to complete the crossing.
B60W 30/00 - Fonctions des systèmes d'aide à la conduite des véhicules routiers non liées à la commande d'un sous-ensemble particulier, p.ex. de systèmes comportant la commande conjuguée de plusieurs sous-ensembles du véhicule
G01S 13/931 - Radar ou systèmes analogues, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
G01S 17/00 - Systèmes utilisant la réflexion ou la reradiation d'ondes électromagnétiques autres que les ondes radio, p.ex. systèmes lidar
G01S 17/931 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
A vehicle has a plurality of control apparatuses, a user input, a geographic position component, an object detection apparatus, memory, and a display. A processor is also included and is programmed to receive the destination information, identify a route, and determine the current geographic location of the vehicle. The processor is also programmed to identify an object and object type based on object information received from the object detection apparatus and to determine at least one warning characteristic of the identified object based on at least one of: the object type, a detected proximity of the detected object to the vehicle, the location of the detected object relative to predetermined peripheral areas of the vehicle, the current geographic location of the vehicle, and the route. The processor is also configured to select and display on the display an object warning image based on the at least one warning characteristic.
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
B60T 7/22 - Organes d'attaque de la mise en action des freins par déclenchement non soumis à la volonté du conducteur ou du passager déclenchés par le contact du véhicule, p.ex. du pare-chocs, avec un obstacle extérieur, p.ex. un autre véhicule
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
G08G 1/09 - Dispositions pour donner des instructions variables pour le trafic
G08G 1/0962 - Dispositions pour donner des instructions variables pour le trafic avec un indicateur monté à l'intérieur du véhicule, p.ex. délivrant des messages vocaux
Aspects of the disclosure relate to arranging a pickup between a driverless vehicle and a passenger. For instance, dispatch instructions dispatching the vehicle to a predetermined pickup area in order to pick up the passenger are received by the vehicle which begins maneuvering to the predetermined pickup area. While doing so, the vehicle receives from the passenger's client computing device the device's location. An indication that the passenger is interested in a fly-by pickup is identified. The fly-by pickup allows the passenger to safely enter the vehicle at a location outside of the predetermined pickup area and prior to the one or more processors have maneuvered the vehicle to the predetermined pickup area. The vehicle determines that the fly-by pickup is appropriate based on at least the location of the client computing device and the indication, and based on the determination, maneuvers itself in order to attempt the fly-by pickup.
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations
Aspects of the technology provide a method including receiving a request for a user to be picked up or dropped off by an autonomous vehicle, in which the request identifying a location, and determining a land parcel containing the identified location. The method also includes identifying a set of features that are within a selected distance from the identified location, filtering the set of identified features to obtain only curated features that are within the selected distance from the identified location, determining a distance between each curated feature and the identified location, and inferring an access point for the identified location based on the distances determined between each curated feature and the identified location. The inferred access point can then be provided to enable the autonomous vehicle to perform a pickup or drop-off.
Example embodiments relate to wiper devices for cleaning sensor housings. An example embodiment includes a wiper device for cleaning a surface of a rotatable sensor housing. The wiper device may have a driving arm having a first end and a second end. The first end of the driving arm is connected to a rotatable shaft. The wiper device may also have a wiper arm pivotally connected to the second end of the driving arm. The pivotal connection is located between a front region and a rear region of the wiper arm. Further, the wiper device may have a wiper blade coupled to the front region of the wiper arm. The wiper blade may be configured to wipe the surface of the rotatable sensor housing. Additionally, the wiper device may have a counterweight coupled to the rear region of the wiper arm.
B60S 1/60 - Nettoyage des pare-brise, fenêtres ou dispositifs optiques spécialement adaptés pour nettoyer d'autres parties ou dispositifs que les fenêtres avant ou les pare-brise pour dispositifs de signalisation, p.ex. réflecteurs
B60S 1/34 - Bras d'essuie-glaces; Montage à cet effet
24.
Synchronization of Multiple Rotating Sensors of a Vehicle
One example system includes a first light detection and ranging (LIDAR) device that scans a first field-of-view defined by a first range of pointing directions associated with the first LIDAR device. The system also includes a second LIDAR device that scans a second FOV defined by a second range of pointing directions associated with the second LIDAR device. The second FOV at least partially overlaps the first FOV. The system also includes a first controller that adjusts a first pointing direction of the first LIDAR device. The system also includes a second controller that adjusts a second pointing direction of the second LIDAR device synchronously with the adjustment of the first pointing direction of the first LIDAR device.
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
G01S 17/10 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes à modulation d'impulsion interrompues
25.
MANAGING PARKING MANEUVERS FOR AUTONOMOUS VEHICLES
Aspects of the disclosure relate to managing parking maneuvers for autonomous vehicles. For instance, a vehicle may be stopped at a parking location. A distance between the autonomous vehicle and a road edge at the parking location may be determined. Based on the distance, a plurality of points corresponding to parking locations at various distances from the road edge may be sampled. For each of the plurality of points, a trajectory for the autonomous vehicle may be determined. One of the determined trajectories may be selected. The autonomous vehicle closer to the road edge using the selected one of the determined trajectories.
A first driving solution for a vehicle along a portion of a route is determined based on an agent detected in the vehicle's environment following a first trajectory of a plurality of possible trajectories. A switching time is determined for the vehicle to deviate from the first driving solution for a situation in which the agent is following a second trajectory of the plurality of possible trajectories. The first driving solution is revised such that the vehicle will be able to switch from the revised first driving solution to another driving solution at the switching time in case if the detected agent is following the second trajectory.
B60W 30/09 - Entreprenant une action automatiquement pour éviter la collision, p.ex. en freinant ou tournant
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 30/182 - Sélection entre plusieurs modes opératoires, p.ex. confort ou sportif
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
Aspects of the disclosure relate to a system that includes a memory storing a queue for arranging tasks, a plurality of self-driving systems for controlling an autonomous vehicle, and one or more processors. The one or more processors may receive a non-passenger task request with a priority level of the non-passenger task request. When the non-passenger task request is accepted, the one or more processors may insert the task in the queue based on the priority level of the task request. Then, the one or more processors may provide instructions to one or more self-driving systems according to the non-passenger task request. Having received updates of the status of the autonomous vehicle, the one or more processors may determine that the task is completed based on the updates. After determining that the task is completed, the one or more processors may remove the task from the queue.
G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
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.
G03F 7/00 - Production par voie photomécanique, p.ex. photolithographique, de surfaces texturées, p.ex. surfaces imprimées; Matériaux à cet effet, p.ex. comportant des photoréserves; Appareillages spécialement adaptés à cet effet
G02B 6/42 - Couplage de guides de lumière avec des éléments opto-électroniques
29.
Vehicle Sensor Modules with External Audio Receivers
Example embodiments relate to vehicle sensor modules with external audio receivers. An example sensor module may include sensors and can be coupled to a vehicle's roof with a first microphone positioned proximate to the front of the sensor module. The sensor module can also include a second microphone extending into a first side of the sensor module such that the second microphone is configured to detect audio originating from an environment located relative to a first side of the vehicle and a third microphone extending into a second side of the sensor module such that the third microphone is configured to detect audio originating from the environment located relative to a second side of the vehicle, wherein the second side is opposite of the first side.
The subject matter of this specification can be implemented in, among other things, systems and methods of optical sensing that use destructive interference to suppress retro-reflected light during generation of sensing beams. Described, among other things, is a system to produce a transmitted (TX) beam and collect a received (RX) beam. The RX beam can include a reflected beam caused by interaction of the TX beam with an object, and a retro-reflected (RR) beam caused by interaction of the TX beam internal components of the system. The system is further to combine the RX beam with a phase-controlled beam to obtain a combined beam, control a phase of the phase-controlled beam to cause destructive interference of the phase-controlled beam and the RR beam, and determine, using the combined beam, one or more of the characteristics of the object.
G01S 17/34 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes continues, soit modulées en amplitude, en fréquence ou en phase, soit non modulées utilisant la transmission d'ondes continues modulées en fréquence, tout en faisant un hétérodynage du signal reçu, ou d’un signal dérivé, avec un signal généré localement, associé au signal transmis simultanément
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
Aspects of the disclosure provide for controlling an autonomous vehicle to enter a driveway. As an example, an instruction to pickup or drop off a passenger at a location may be received. It may be determined that the vehicle is arriving in a lane on an opposite side of a street as the location, the lane having a traffic direction opposite to a traffic direction of a lane adjacent to the location. A difficulty score to maneuver the vehicle to the lane adjacent to the location may be determined, and the difficulty score may be compared to a predetermined difficulty score. Based on the comparison, it may be determined to an available driveway on the same side of the street as the location. The vehicle may be controlled to enter the available driveway.
B60W 30/06 - Manœuvre automatique de stationnement
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
A sensor assembly contains at least first and second sensors configured to perform imaging from a portion of a vehicle, each sensor having a respective field of view (FOV) based on an imaging direction of the sensor, each sensor having an FOV origin. The sensor assembly is configured to be disposed at the portion of the vehicle such that (i) the first and second sensors' FOV origins are each outboard from the vehicle, (ii) the first and second sensors' imaging directions are each within 90 degrees in yaw of being parallel to the backward direction of the vehicle, (iii) the first sensor's imaging direction is closer in yaw than the second sensor's imaging direction to being parallel to the backward direction of the vehicle, and (iv) the first sensor's FOV origin is more outboard from the vehicle than the second sensor's FOV origin.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using slice-based dynamic neural networks. One of the methods includes receiving a new input for processing by a neural network that includes a first conditional neural network layer that has a set of shared parameters and a respective set of slice parameters for each of a plurality of slices. One or more slices to which the new input belongs are identified. The new input is processed to generate a network output, including: receiving a layer input to the first conditional neural network layer; and processing the layer input using the set of shared parameters, the respective one or more sets of slice parameters for the identified one or more slices, but not the respective sets of slice parameters for any other slices to which the new input does not belong.
B60W 40/00 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
G06F 18/211 - Sélection du sous-ensemble de caractéristiques le plus significatif
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.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G01C 21/20 - Instruments pour effectuer des calculs de navigation
G01S 7/52 - DÉTERMINATION DE LA DIRECTION PAR RADIO; RADIO-NAVIGATION; DÉTERMINATION DE LA DISTANCE OU DE LA VITESSE EN UTILISANT DES ONDES RADIO; LOCALISATION OU DÉTECTION DE LA PRÉSENCE EN UTILISANT LA RÉFLEXION OU LA RERADIATION D'ONDES RADIO; DISPOSITIONS ANALOGUES UTILISANT D'AUTRES ONDES - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
35.
EXTERNAL INDICATION HANDLING FOR AUTONOMOUS DRIVING SYSTEMS
A method includes detecting, by a sensing system of an autonomous vehicle (AV) executing a trip from a first location to a second location, a signal to stop the AV, determining, in response to the signal, that the AV is to be stopped for a roadside inspection, and causing a vehicle control system of the AV to stop the AV at a third location to allow the roadside inspection to be performed.
Aspects of the disclosure relate to detecting and responding to malfunctioning traffic signals for a vehicle having an autonomous driving mode. For instance, information identifying a detected state of a traffic signal for an intersection. An anomaly for the traffic signal may be detected based on the detected state and prestored information about expected states of the traffic signal. The vehicle may be controlled in the autonomous driving mode based on the detected anomaly.
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
G06V 40/10 - Corps d’êtres humains ou d’animaux, p.ex. occupants de véhicules automobiles ou piétons; Parties du corps, p.ex. mains
One example method of testing an electrical device comprises transmitting a data pattern to a memory device of the electrical device by a controller of the electrical device to provide a written data pattern to the memory device, wherein the data pattern replicates a resonant frequency of at least a portion of the electrical device, reading the written data pattern from the memory device with the controller, and comparing the written data pattern to the data pattern.
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.
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
G01S 7/491 - DÉTERMINATION DE LA DIRECTION PAR RADIO; RADIO-NAVIGATION; DÉTERMINATION DE LA DISTANCE OU DE LA VITESSE EN UTILISANT DES ONDES RADIO; LOCALISATION OU DÉTECTION DE LA PRÉSENCE EN UTILISANT LA RÉFLEXION OU LA RERADIATION D'ONDES RADIO; DISPOSITIONS ANALOGUES UTILISANT D'AUTRES ONDES - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe - Détails des systèmes non pulsés
39.
LIDAR SYSTEMS WITH PLANAR MULTI-PIXEL SENSING ARRAYS
The subject matter of this specification can be implemented in, among other things, systems and methods of optical sensing for pixel multiplexing and polarized beam steering. Described, among other things, is a system that includes a light source configured to generate a light and one or more optical devices, integrated on a photonic integrated circuit, configured to impart modulation to the generated light and deliver the modulated light to an interface coupling device. The interface coupling device can include a plurality of interface couplers (ICs), each IC configured to scatter the modulated light in a direction that makes at least 5 degrees with an optical axis of lens configured to transmit the light scattered by each IC along a respective direction of a plurality of directions.
G01S 7/4914 - Réseaux des détecteurs, p.ex. portes de transfert de charge
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
G01S 7/4911 - DÉTERMINATION DE LA DIRECTION PAR RADIO; RADIO-NAVIGATION; DÉTERMINATION DE LA DISTANCE OU DE LA VITESSE EN UTILISANT DES ONDES RADIO; LOCALISATION OU DÉTECTION DE LA PRÉSENCE EN UTILISANT LA RÉFLEXION OU LA RERADIATION D'ONDES RADIO; DISPOSITIONS ANALOGUES UTILISANT D'AUTRES ONDES - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe - Détails des systèmes non pulsés Émetteurs
G01S 7/499 - DÉTERMINATION DE LA DIRECTION PAR RADIO; RADIO-NAVIGATION; DÉTERMINATION DE LA DISTANCE OU DE LA VITESSE EN UTILISANT DES ONDES RADIO; LOCALISATION OU DÉTECTION DE LA PRÉSENCE EN UTILISANT LA RÉFLEXION OU LA RERADIATION D'ONDES RADIO; DISPOSITIONS ANALOGUES UTILISANT D'AUTRES ONDES - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe utilisant des effets de polarisation
G01S 17/58 - Systèmes de détermination de la vitesse ou de la trajectoire; Systèmes de détermination du sens d'un mouvement
The present disclosure relates to devices, light detection and ranging (lidar) systems, and vehicles involving solid-state, single photon detectors. An example device includes a substrate defining a primary plane and a plurality of photodetector cells disposed along the primary plane. The plurality of photodetector cells includes at least one large-area cell and at least one small-area cell. The large-area cell has a first area and the small-area cell has a second area and the first area is greater than the second area. The device also includes read out circuitry coupled to the plurality of photodetector cells. The read out circuitry is configured to provide an output signal based on incident light detected by the plurality of photodetector cells.
G01S 7/4863 - Réseaux des détecteurs, p.ex. portes de transfert de charge
H01L 27/144 - Dispositifs commandés par rayonnement
H01L 31/0232 - Dispositifs à semi-conducteurs sensibles aux rayons infrarouges, à la lumière, au rayonnement électromagnétique d'ondes plus courtes, ou au rayonnement corpusculaire, et spécialement adaptés, soit comme convertisseurs de l'énergie dudit rayonnement e; Procédés ou appareils spécialement adaptés à la fabrication ou au traitement de ces dispositifs ou de leurs parties constitutives; Leurs détails - Détails Éléments ou dispositions optiques associés au dispositif
H01L 31/107 - Dispositifs sensibles au rayonnement infrarouge, visible ou ultraviolet caractérisés par une seule barrière de potentiel ou de surface la barrière de potentiel fonctionnant en régime d'avalanche, p.ex. photodiode à avalanche
41.
OBJECT IDENTIFICATION IN BIRD'S-EYE VIEW REFERENCE FRAME WITH EXPLICIT DEPTH ESTIMATION CO-TRAINING
The described aspects and implementations enable efficient detection and classification of objects with machine learning models that deploy a bird's-eye view representation and are trained using depth ground truth data. In one implementation, disclosed are system and techniques that include obtaining images, generating, using a first neural network (NN), feature vectors (FVs) and depth distributions pixels of images, wherein the first NN is trained using training images and a depth ground truth data for the training images. The techniques further include obtaining a feature tensor (FT) in view of the FVs and the depth distributions, and processing the obtained FTs, using a second NN, to identify one or more objects depicted in the images.
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
G06T 7/55 - Récupération de la profondeur ou de la forme à partir de plusieurs images
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p.ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersections; Analyse de connectivité, p.ex. de composantes connectées
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
42.
SEMANTIC SEGMENTATION NEURAL NETWORK FOR POINT CLOUDS
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a semantic segmentation neural network for point clouds. One of the methods includes: obtaining a plurality of training points divided into a respective plurality of components; obtaining, for each of the respective plurality of components, data identifying a ground truth category for one or more labeled point; processing each training points using a semantic segmentation neural network to generate a semantic segmentation that includes a respective score for each of the plurality of categories; determining a gradient of a loss function that penalizes the semantic segmentation neural network for generating, for points in the component, non-zero scores for categories that are not the ground truth category for any labeled point in the component; and updating, using the gradient, the parameters of the semantic segmentation neural network.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 10/80 - Fusion, c. à d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
43.
CARRIER EXTRACTION FROM SEMICONDUCTING WAVEGUIDES IN HIGH-POWER LIDAR APPLICATIONS
The subject matter of this specification can be implemented in, among other things, systems and methods of optical sensing that use carrier extraction from waveguides that can support propagation of high-power sensing beams. Described, among other things, is a system that includes one or more waveguides that include a semiconducting material with a temperature-dependent refractive index. The system further includes a plurality of extraction electrodes configured to extract from the waveguide(s), charge carriers generated by an electromagnetic wave propagating in the waveguide(s). The system further includes a heating electrode configured to cause a change of a temperature of the waveguide(s).
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.
A simulation may be used to determine a difference between progress of a manually-driven vehicle and progress of a simulated autonomous vehicle. The method includes retrieving log data collected for the manually-driven vehicle driving along a route, generating a plurality of path segments for a portion of the route. The plurality of path segments corresponds to points in a lane that the manually-driven vehicle traveled through on the portion of the route. The method also includes running, using a software of the autonomous vehicle, a simulation of the autonomous vehicle driving along the plurality of path segments, extracting metrics from the log data and the simulation, and determining the difference between a first progress of the manually-driven vehicle and a second progress of the simulated autonomous vehicle based on the metrics.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
G01C 22/00 - Mesure de la distance parcourue sur le sol par des véhicules, des personnes, des animaux ou autres corps solides en mouvement, p.ex. en utilisant des odomètres ou en utilisant des podomètres
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
The technology relates to detecting and responding to emergency vehicles. This may include using a plurality of microphones to detect a siren noise corresponding to an emergency vehicle and to estimate a bearing of the emergency vehicle. This estimated bearing is compared to map information to identify a portion of roadway on which the emergency vehicle is traveling. In addition, information identifying a set of objects in the vehicle's environment as well as characteristics of those objects is received from a perception system is used to determine whether one of the set of objects corresponds to the emergency vehicle. How to respond to the emergency vehicle is determined based on the estimated bearing and identified road segments and the determination of whether one of the set of objects corresponds to the emergency vehicle. This determined response is then used to control the vehicle in an autonomous driving mode.
G08G 1/0965 - Dispositions pour donner des instructions variables pour le trafic avec un indicateur monté à l'intérieur du véhicule, p.ex. délivrant des messages vocaux répondant à des signaux provenant d'un autre véhicule, p.ex. d'un véhicule de secours
G06F 16/68 - Recherche de données caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/683 - Recherche de données caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
The technology involves operation of a self-driving truck or other cargo vehicle when it is being inspected at a weigh station. This may include determining whether a weigh station is open for inspection. Once at the weigh station, the vehicle may follow instructions of an inspection officer or autonomous inspection system. The vehicle may perform predefined actions or operations so that various vehicle systems and safety issues can be evaluated, such as the brakes, lights, tires, connections between the tractor and trailer, exposed fuel tanks, leaks, etc. A visual inspection may be performed to ensure the load is secured, vehicle and cargo documents meet certain criteria, and the carrier's safety record meets any requirements. In addition, the weigh station itself may be operated in a partly or fully autonomous mode when dealing with autonomous and manually driven vehicles.
G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
G01G 19/02 - Appareils ou méthodes de pesée adaptés à des fins particulières non prévues dans les groupes pour peser des objets à roues ou roulants, p.ex. des véhicules
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G07C 5/02 - Enregistrement ou indication du temps de circulation, de fonctionnement, d'arrêt ou d'attente uniquement
Example embodiments relate to LIDAR systems with multi-faceted mirrors. An example embodiment includes a LIDAR system. The system includes a multi-faceted mirror that includes a plurality of reflective facets, which rotates about a first rotational axis. The system also includes a light emitter configured to emit a light signal toward one or more regions of a scene. Further, the system includes a light detector configured to detect a reflected light signal. In addition, the system includes an optical window positioned between the multi-faceted mirror and the one or more regions of the scene such that light reflected from one or more of the reflective facets is transmitted through the optical window. The optical window is positioned such that the optical window is non-perpendicular to the direction toward which the light emitted along the optical axis is directed for all angles of the multi-faceted mirror.
G01S 17/931 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
G01C 3/06 - Utilisation de moyens électriques pour obtenir une indication finale
G01S 7/48 - DÉTERMINATION DE LA DIRECTION PAR RADIO; RADIO-NAVIGATION; DÉTERMINATION DE LA DISTANCE OU DE LA VITESSE EN UTILISANT DES ONDES RADIO; LOCALISATION OU DÉTECTION DE LA PRÉSENCE EN UTILISANT LA RÉFLEXION OU LA RERADIATION D'ONDES RADIO; DISPOSITIONS ANALOGUES UTILISANT D'AUTRES ONDES - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
G01S 17/10 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes à modulation d'impulsion interrompues
G01S 17/42 - Mesure simultanée de la distance et d'autres coordonnées
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
50.
Using Wheel Orientation To Determine Future Heading
The technology relates to determining a future heading of an object. In order to do so, sensor data, including information identifying a bounding box representing an object in a vehicle's environment and locations of sensor data points corresponding to the object, may be received. Based on dimensions of the bounding box, an area corresponding to a wheel of the object may be identified. An orientation of the wheel may then be estimated based on the sensor data points having locations within the area. The estimation may then be used to determine a future heading of the object.
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 10/04 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des ensembles de propulsion
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 40/04 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes liés aux conditions de trafic
B60W 50/00 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
G01S 13/931 - Radar ou systèmes analogues, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
G01S 15/931 - Systèmes sonar, spécialement adaptés à des applications spécifiques pour prévenir les collisions de véhicules terrestres
G01S 17/931 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
Described herein is a LIDAR device that may include a transmitter, first and second receivers, and a rotating platform. The transmitter may be configured to emit light having a vertical beam width. The first receiver may be configured to detect light at a first resolution while scanning the environment with a first FOV and the second receiver may be configured to detect light at a second resolution while scanning the environment with a second FOV. In this arrangement, the first resolution may be higher than the second resolution, the first FOV may be at least partially different from the second FOV, and the vertical beam width may encompass at least a vertical extent of the first and second FOVs. Further, the rotating platform may be configured to rotate about an axis such that the transmitter and first and second receivers each move based on the rotation.
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
G01S 7/4911 - DÉTERMINATION DE LA DIRECTION PAR RADIO; RADIO-NAVIGATION; DÉTERMINATION DE LA DISTANCE OU DE LA VITESSE EN UTILISANT DES ONDES RADIO; LOCALISATION OU DÉTECTION DE LA PRÉSENCE EN UTILISANT LA RÉFLEXION OU LA RERADIATION D'ONDES RADIO; DISPOSITIONS ANALOGUES UTILISANT D'AUTRES ONDES - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe - Détails des systèmes non pulsés Émetteurs
G01S 13/931 - Radar ou systèmes analogues, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
G01S 17/42 - Mesure simultanée de la distance et d'autres coordonnées
G01S 17/86 - Combinaisons de systèmes lidar avec des systèmes autres que lidar, radar ou sonar, p.ex. avec des goniomètres
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
G01S 17/931 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
52.
Temporally Modulated Light Emission for Defect Detection in Light Detection and Ranging (Lidar) Devices and Cameras
Example embodiments relate to temporally modulated light emission and defect detection in light detection and ranging (lidar) devices and cameras. An example embodiment includes a method. The method includes detecting, by a first detector via an optical component, a background signal corresponding to a surrounding environment. The method also includes illuminating, by a first light source, a first portion of the optical component with a first light signal. Additionally, the method includes detecting, by the first detector when one or more defects are present in a body of the first portion of the optical component or on a surface of the first portion of the optical component, the first light signal. Further, the method includes determining, by a computing device, when one or more defects are present in the body of the first portion of the optical component or on the surface of the first portion of the optical component.
The technology relates to controlling a vehicle in an autonomous driving mode in accordance with behavior predictions for other road users in the vehicle's vicinity. In particular, the vehicle's onboard computing system may predict whether another road user will perform a “continuing” lane driving operation, such as going straight in a turn-only lane. Sensor data from detected/observed objects in the vehicle's nearby environment may be evaluated in view of one or more possible behaviors for different types of objects. In addition, roadway features, in particular whether lane segments are connected in a roadgraph, are also evaluated to determine probabilities of whether other road users may make an improper continuing lane driving operation. This is used to generate more accurate behavior predictions, which the vehicle can use to take alternative (e.g., corrective) driving actions.
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G05B 13/02 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
G05B 13/04 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
54.
DETECTING AND RESPONDING TO PROCESSIONS FOR AUTONOMOUS VEHICLES
The technology relates to detecting and responding to processions. For instance, sensor data identifying two or more objects in an environment of a vehicle may be received. The two or more objects may be determined to be disobeying a predetermined rule in a same way. Based on the determination that the two or more objects are disobeying a predetermined rule, that the two or more objects are involved in a procession may be determined. The vehicle may then be controlled autonomously in order to respond to the procession based on the determination that the two or more objects are involved in a procession.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
55.
PHYSICS-INFORMED OPTIMIZATION FOR AUTONOMOUS DRIVING SYSTEMS
A method includes identifying map data comprising driving constraint data for a route of an autonomous vehicle (AV), the map data being of a road network associated with the route of the AV, the driving constraint data being based on physical vehicle data. The method further includes, while the AV is travelling the route, identifying current environmental sensing data for a portion of the route. The method further includes causing, based on the map data comprising the driving constraint data for the route and the current environmental sensing data associated with the portion of the route, the AV to travel the portion of the route.
Aspects of the disclosure provide for determining when to provide and providing secondary disengage alerts for a vehicle having autonomous and manual driving modes. For instance, while the vehicle is being controlled in the autonomous driving mode, user input is received at one or more user input devices of the vehicle. In response to receiving the user input, the vehicle may be transitioned from the autonomous driving mode to a manual driving mode and provide a primary disengage alert to an occupant of the vehicle regarding the transition. Whether to provide a secondary disengage alert may be determined based on at least circumstances of the user input. After the transition, the secondary disengage alert may be provided based on the determination.
B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
57.
Low-Overhead, Bidirectional Error Checking for a Serial Peripheral Interface
Example embodiments relate to low-overhead, bidirectional error checking for a serial peripheral interface. An example device includes an integrated circuit. The device also includes a serial peripheral interface (SPI) with a Master In Slave Out (MISO) channel and a Master Out Slave In (MOSI) channel. The MOSI channel is configured to receive a write address, payload data, and a forward error-checking code usable to identify data corruption within the write address or the payload data. The integrated circuit is configured to calculate and provide a reverse error-checking code usable to identify data corruption within the write address or the payload data. Additionally, the integrated circuit is configured to compare the forward error-checking code to the reverse error-checking code. Further, the integrated circuit is configured to write, to the write address if the forward error-checking code matches the reverse error-checking code, the payload data.
G06F 11/10 - Détection ou correction d'erreur par introduction de redondance dans la représentation des données, p.ex. en utilisant des codes de contrôle en ajoutant des chiffres binaires ou des symboles particuliers aux données exprimées suivant un code, p.ex. contrôle de parité, exclusion des 9 ou des 11
G06F 11/07 - Réaction à l'apparition d'un défaut, p.ex. tolérance de certains défauts
An integrated hybrid rotary assembly is configured to provide power, torque and bi-directional communication to a rotatable sensor, such as a lidar, radar or optical sensor. A common ferrite core is shared by a motor, rotary transformer and radio frequency communication link. This hybrid configuration reduces cost, simplifies the manufacturing process, and can improve system reliability by employing a minimum number of parts. The assembly can be integrated with the sensor unit, which may be used in vehicles and other systems.
G01R 33/07 - Mesure de la direction ou de l'intensité de champs magnétiques ou de flux magnétiques en utilisant des dispositifs galvano-magnétiques des dispositifs à effet Hall
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
Example embodiments relate to replaceable, heated, and wipeable apertures for optical systems. An example embodiment includes an apparatus that includes an optical system (e.g., a camera) with a lens. The apparatus also includes a housing in which the lens is disposed. The housing has a sealing surface and a threated portion. The apparatus further includes a chamfered window that provides a protective aperture for the lens. The apparatus also includes a retainer ring that has a retaining portion and a threaded portion. The retaining portion contacts the chamfer of the window while the threaded portion of the retainer ring threads onto the threaded portion of the housing to hold the window against the sealing surface of the housing and form a watertight seal.
Aspects of the disclosure provide for controlling an autonomous vehicle. For instance, a first probability distribution may be generated for the vehicle at a first future point in time using a generative model for predicting expected behaviors of objects and a set of characteristics for the vehicle at an initial time expected to be perceived by an observer. Planning system software of the vehicle may be used to generate a trajectory for the vehicle to follow. A second probability distribution may be generated for a second future point in time using the generative model based on the trajectory and a set of characteristics for the vehicle at the first future point expected to be perceived by the observer. A surprise assessment may be generated by comparing the first probability distribution to the second probability distribution. The vehicle may be controlled based on the surprise assessment.
B60W 50/00 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
G05B 13/04 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
Example implementations are provided for an arrangement of co-aligned rotating sensors. One example device includes a light detection and ranging (LIDAR) transmitter that emits light pulses toward a scene according to a pointing direction of the device. The device also includes a LIDAR receiver that detects reflections of the emitted light pulses reflecting from the scene. The device also includes an image sensor that captures an image of the scene based on at least external light originating from one or more external light sources. The device also includes a platform that supports the LIDAR transmitter, the LIDAR receiver, and the image sensor in a particular relative arrangement. The device also includes an actuator that rotates the platform about an axis to adjust the pointing direction of the device.
Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. For instance, a current state of a traffic light may be determined. One of a plurality of yellow light durations may be selected based on the current state of the traffic light. When the traffic light will turn red may be predicted based on the selected one. The prediction may be used to control the vehicle in the autonomous driving mode.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
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.
B60W 40/00 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
G01C 21/26 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
G01C 21/30 - Mise en coïncidence avec des cartes ou des contours
G01S 13/88 - Radar ou systèmes analogues, spécialement adaptés pour des applications spécifiques
G01S 15/88 - Systèmes sonar, spécialement adaptés à des applications spécifiques
G01S 17/88 - Systèmes lidar, spécialement adaptés pour des applications spécifiques
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
65.
Approach for consolidating observed vehicle trajectories into a single representative trajectory
A method and apparatus is provided for controlling the operation of an autonomous vehicle. According to one aspect, the autonomous vehicle may track the trajectories of other vehicles on a road. Based on the other vehicle's trajectories, the autonomous vehicle may generate a pool of combined trajectories. Subsequently, the autonomous vehicle may select one of the combined trajectories as a representative trajectory. The representative trajectory may be used to change at least one of the speed or direction of the autonomous vehicle.
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
B60W 30/095 - Prévision du trajet ou de la probabilité de collision
B60W 30/16 - Contrôle de la distance entre les véhicules, p.ex. pour maintenir la distance avec le véhicule qui précède
B60W 40/04 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes liés aux conditions de trafic
B60W 50/04 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour surveiller le fonctionnement du système d'aide à la conduite
B62D 6/00 - Dispositions pour la commande automatique de la direction en fonction des conditions de conduite, qui sont détectées et pour lesquelles une réaction est appliquée, p.ex. circuits de commande
B62D 15/02 - Indicateurs de direction ou aides de direction
G01C 21/26 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
G01S 13/86 - Combinaisons de systèmes radar avec des systèmes autres que radar, p.ex. sonar, chercheur de direction
G01S 13/931 - Radar ou systèmes analogues, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
G01S 15/42 - Mesure simultanée de la distance et d'autres coordonnées
G01S 17/42 - Mesure simultanée de la distance et d'autres coordonnées
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
G08G 1/0967 - Systèmes impliquant la transmission d'informations pour les grands axes de circulation, p.ex. conditions météorologiques, limites de vitesse
A laser diode firing circuit for a light detection and ranging device is disclosed. The firing circuit includes a laser diode coupled in series to a transistor, such that current through the laser diode is controlled by the transistor. The laser diode is configured to emit a pulse of light in response to current flowing through the laser diode. The firing circuit includes a capacitor that is configured to charge via a charging path that includes an inductor and to discharge via a discharge path that includes the laser diode. The transistor controlling current through the laser diode can be a Gallium nitride field effect transistor.
The technology relates to route planning and performing driving operations in autonomous vehicles, such as cargo trucks, articulating buses, as well as other vehicles. A detailed kinematic model of the vehicle in evaluated in conjunction with roadgraph and other information to determine whether a route or driving operation is feasible for the vehicle. This can include evaluating a hierarchical set of driving rules and whether current driving conditions impact any of the rules. Driving trajectories and cost can be evaluated when pre-planning a route for the vehicle to follow. This can include determining an ideal trajectory for the vehicle to take a particular driving action. Pre-planned routes may be shared with a fleet of vehicles, and can be modified based on information obtained by different vehicles of the fleet.
B60W 40/04 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes liés aux conditions de trafic
G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
A system includes a dome, a wiper assembly, a position sensor and a control device. The wiper assembly includes a wiper blade configured to rotate around the dome. The position sensor may be configured to send a signal to a control device when a wiper blade passes the position sensor. The control device may include one or more processors configured to receive the signal from the position sensor and determine a location of the wiper blade relative to the dome based on the received signal.
B60S 1/56 - Nettoyage des pare-brise, fenêtres ou dispositifs optiques spécialement adaptés pour nettoyer d'autres parties ou dispositifs que les fenêtres avant ou les pare-brise
B08B 1/00 - Nettoyage par des procédés impliquant l'utilisation d'outils, de brosses ou d'éléments analogues
B08B 1/04 - Nettoyage par des procédés impliquant l'utilisation d'outils, de brosses ou d'éléments analogues utilisant des éléments actifs rotatifs
B60S 1/08 - Essuie-glaces ou analogues, p.ex. grattoirs caractérisés par l'entraînement entraînés électriquement
B60S 1/34 - Bras d'essuie-glaces; Montage à cet effet
G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
H02P 7/06 - Dispositions pour réguler ou commander la vitesse ou le couple de moteurs électriques à courant continu pour réguler ou commander individuellement un moteur dynamo-électrique à courant continu en faisant varier le champ ou le courant d'induit
70.
Pipeline Architecture for Road Sign Detection and Evaluation
The technology provides a sign detection and classification methodology. A unified pipeline approach incorporates generic sign detection with a robust parallel classification strategy. Sensor information such as camera imagery and lidar depth, intensity and height (elevation) information are applied to a sign detector module. This enables the system to detect the presence of a sign in a vehicle's external environment. A modular classification approach is applied to the detected sign. This includes selective application of one or more trained machine learning classifiers, as well as a text and symbol detector. Annotations help to tie the classification information together and to address any conflicts with different outputs from different classifiers. Identification of where the sign is in the vehicle's surrounding environment can provide contextual details. Identified signage can be associated with other objects in the vehicle's driving environment, which can be used to aid the vehicle in autonomous driving.
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
Example embodiments relate to time-division multiple access scanning for crosstalk mitigation in light detection and ranging (lidar) devices. An example embodiment includes a method. The method includes emitting a first group of light signals into a surrounding environment. The first group of light signals corresponds to a first angular resolution. The method also includes detecting, during a first listening window, a first group of reflected light signals. Additionally, the method includes emitting a second group of light signals into the surrounding environment. The second group of light signals corresponds to a second angular resolution with respect to the surrounding environment. The second angular resolution is lower than the first angular resolution. Further, the method includes detecting a second group of reflected light signals from the surrounding environment. In addition, the method includes synthesizing, by a controller of the lidar device, a dataset usable to generate one or more point clouds.
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
72.
Methods and Systems for using Interference to Detect Sensor Impairment
Example embodiments relate to methods and systems for using interference to detect sensor impairment. Radar or another type of sensor on a vehicle may receive radio-frequency (RF) signals propagating in the environment. These RF signals may originate from an external source and a computing device can be used to determine a distance and an angle to the source in order to identify a power level threshold that represents an expected power associated with the RF signals. The computing device may then perform a comparison between a power level of the RF signals and a power level threshold. Based on the comparison, the computing device may decrease a confidence assigned to the radar coupled to the vehicle and control the vehicle based on the decreased confidence assigned to the radar.
A rotary joint includes a shaft having a first end, a second end, and a cavity. The rotary joint includes a first waveguide section having a first proximal end and a first distal end. The first proximal end of the first waveguide section is positioned within the cavity and secured to the inner surface of the shaft. The rotary joint includes a second waveguide section that includes a second proximal end and a second distal end. The second proximal end of the second waveguide section is positioned within the cavity of the shaft and unsecured to the inner surface of the shaft to form a radial gap between an outer surface of the second proximal end and a laterally adjacent portion of the inner surface of the shaft. The shaft and the first waveguide section are configured to rotate about the rotational axis and relative to the second waveguide section.
Aspects of the present disclosure relate to a vehicle having one or more computing devices that may receive instructions to pick up a passenger at a location, determine when the vehicle is within a first distance of the location, provide a first notification that the vehicle is within the first distance, and stop the vehicle. When the vehicle is stopped, the computing device may initiate a countdown. When a client computing device associated with the passenger has not been authenticated, the computing devices may provide a second notification based on a first amount of time remaining in the countdown and a third notification indicating that the trip is cancelled based on a second amount of time remaining in the countdown less than the first amount of time. Once the third notification is provided, the computing devices move the vehicle from the where the vehicle is stopped without the passenger.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
E05F 15/70 - Mécanismes pour battants mus par une force motrice avec déclenchement automatique
E05F 15/76 - Mécanismes pour battants mus par une force motrice avec déclenchement automatique sensible au déplacement ou à la présence de personnes ou d’objets sensible à des dispositifs portés par des personnes ou des objets, p.ex. aimants ou miroirs
B60R 25/24 - Moyens pour enclencher ou arrêter le système antivol par des éléments d’identification électroniques comportant un code non mémorisé par l’utilisateur
G01C 21/20 - Instruments pour effectuer des calculs de navigation
B60W 30/06 - Manœuvre automatique de stationnement
B62D 15/02 - Indicateurs de direction ou aides de direction
G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
G01C 21/26 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
G06Q 10/1093 - Ordonnancement basé sur un agenda pour des personnes ou des groupes
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
G08G 1/14 - Systèmes de commande du trafic pour véhicules routiers indiquant des places libres individuelles dans des parcs de stationnement
The technology relates to an exterior sensor system for a vehicle configured to operate in an autonomous driving mode. The technology includes a close-in sensing (CIS) camera system to address blind spots around the vehicle. The CIS system is used to detect objects within a few meters of the vehicle. Based on object classification, the system is able to make real-time driving decisions. Classification is enhanced by employing cameras in conjunction with lidar sensors. The specific arrangement of multiple sensors in a single sensor housing is also important to object detection and classification. Thus, the positioning of the sensors and support components are selected to avoid occlusion and to otherwise prevent interference between the various sensor housing elements.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G01S 17/86 - Combinaisons de systèmes lidar avec des systèmes autres que lidar, radar ou sonar, p.ex. avec des goniomètres
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
B60W 10/18 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de freinage
B60W 10/20 - Commande conjuguée de sous-ensembles de véhicule, de fonction ou de type différents comprenant la commande des systèmes de direction
G01S 7/02 - DÉTERMINATION DE LA DIRECTION PAR RADIO; RADIO-NAVIGATION; DÉTERMINATION DE LA DISTANCE OU DE LA VITESSE EN UTILISANT DES ONDES RADIO; LOCALISATION OU DÉTECTION DE LA PRÉSENCE EN UTILISANT LA RÉFLEXION OU LA RERADIATION D'ONDES RADIO; DISPOSITIONS ANALOGUES UTILISANT D'AUTRES ONDES - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
G01S 13/86 - Combinaisons de systèmes radar avec des systèmes autres que radar, p.ex. sonar, chercheur de direction
G01S 13/89 - Radar ou systèmes analogues, spécialement adaptés pour des applications spécifiques pour la cartographie ou la représentation
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
H04N 23/74 - Circuits de compensation de la variation de luminosité dans la scène en influençant la luminosité de la scène à l'aide de moyens d'éclairage
77.
AUTONOMOUS VEHICLE SENSOR SECURITY, AUTHENTICATION AND SAFETY
A method includes obtaining, by a processing device, an impact analysis configuration related to an image sensor operation type for an autonomous vehicle (AV), receiving, by the processing device, image data from a sensing system including at least one image sensor of the AV, causing, by the processing device, fault detection to be performed based on the image data, causing, by the processing device, a fault notification to be generated using the impact analysis configuration, and sending, by the processing device to a data processing system of the AV, the fault notification to perform at least one action to address the fault notification. The fault notification includes a fault summary related to the image sensor operation type.
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
B60W 50/02 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour préserver la sécurité en cas de défaillance du système d'aide à la conduite, p.ex. en diagnostiquant ou en palliant à un dysfonctionnement
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G06V 10/75 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexte; Sélection des dictionnaires
G06V 10/80 - Fusion, c. à d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
G06V 10/98 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos Évaluation de la qualité des motifs acquis
78.
Systems and Methods for Adaptive Range Coverage using LIDAR
The present disclosure relates to systems and methods that facilitate light detection and ranging operations. An example method includes determining, for at least one light-emitter device of a plurality of light-emitter devices, a light pulse schedule. The plurality of light-emitter devices is operable to emit light along a plurality of emission vectors. The light pulse schedule is based on a respective emission vector of the at least one light-emitter device and a three-dimensional map of an external environment. The light pulse schedule includes at least one light pulse parameter and a listening window duration. The method also includes causing the at least one light-emitter device of the plurality of light-emitter devices to emit a light pulse according to the light pulse schedule. The light pulse interacts with an external environment.
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
G01S 7/4861 - Circuits pour la détection, d'échantillonnage, d'intégration ou de lecture des circuits
G01S 17/10 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes à modulation d'impulsion interrompues
G01S 17/931 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions de véhicules terrestres
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing sensor data, e.g., laser sensor data, using neural networks. One of the methods includes obtaining a temporal sequence of multiple three-dimensional point clouds generated from sensor readings of an environment collected by one or more sensors within a given time period, each three-dimensional point cloud comprising a respective plurality of points in a first coordinate system; processing, using a feature extraction neural network, an input that comprises data derived from the temporal sequence of multiple three-dimensional point clouds to generate a feature embedding; receiving a query that specifies one time point within the given time period; and generating, from the feature embedding and conditioned on the query, one or more outputs that characterize one or more objects in the environment at the time point specified in the received query.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for predictability estimation using a behavior prediction model. One of the methods includes receiving a candidate future behavior to be performed by an agent in an environment after a current time point; receiving data characterizing a scene that includes the agent in the environment as of the current time point; processing a behavior prediction input generated from the data using a behavior prediction model, wherein the behavior prediction model is configured to receive the behavior prediction input and to process the behavior prediction input to generate a behavior prediction output that characterizes a set of predicted future behaviors for the agent after the current time point; and determining a predictability score for the candidate future behavior by comparing the candidate future behavior with the behavior prediction output.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G06N 5/02 - Représentation de la connaissance; Représentation symbolique
B60W 50/00 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
81.
Modifying autonomous vehicle behavior prediction based on behavior prediction errors
A system includes a memory device and a processing device, operatively coupled to the memory device, to obtain a set of predicted behavior data including data indicative of one or more predicted object behaviors for one or more respective objects in an environment of an autonomous vehicle, obtain a set of observed behavior data including data indicative of one or more observed object behaviors of the one or more objects, determine, based on a comparison of the set of predicted behavior data and the set of observed behavior data, whether a set of incorrect object behavior predictions exists within the set of predicted behavior data, and upon determining that the set of incorrect object behavior predictions exists, initiate, based on at least a generated subset of the set of incorrect object behavior predictions, one or more operations to address the set of incorrect object behavior predictions.
G06F 18/21 - Conception ou mise en place de systèmes ou de techniques; Extraction de caractéristiques dans l'espace des caractéristiques; Séparation aveugle de sources
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
One example device includes a rotor platform that rotates about an axis of rotation. The device also includes a rotor coil comprising a first plurality of conductive loops disposed along a planar mounting surface of the rotor platform. The device also includes a stator platform and a stator coil comprising a second plurality of conductive loops disposed along a planar mounting surface of the stator platform. The rotor coil and the stator coil are coaxially arranged about the axis of rotation. The stator coil remains within a first predetermined distance to the rotor coil in response to rotation of the rotor platform. The device also includes a magnetic core extending along the axis of rotation and through the stator coil. The magnetic core remains within a second predetermined distance to the stator coil in response to rotation of the rotor platform.
H02K 11/20 - Association structurelle de machines dynamo-électriques à des organes électriques ou à des dispositifs de blindage, de surveillance ou de protection pour la mesure, la surveillance, les tests, la protection ou la coupure
Aspects of the disclosure relate to determining a sign type of an unfamiliar sign. The system may include one or more processors. The one or more processors may be configured to receive an image and identify image data corresponding to a traffic sign in the image. The image data corresponding to the traffic sign may be input in a sign type model. The processors may determine that the sign type model was unable to identify a type of the traffic sign and determine one or more attributes of the traffic sign. The one or more attributes of the traffic sign may be compared to known attributes of other traffic signs and based on this comparison, a sign type of the traffic sign may be determined. The vehicle may be controlled in an autonomous driving mode based on the sign type of the traffic sign.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G06T 7/90 - Détermination de caractéristiques de couleur
G06V 20/20 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène dans les scènes de réalité augmentée
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
84.
Identifying Defects in Optical Detector Systems Based on Extent of Stray Light
Example embodiments relate to identifying defects in optical detector systems based on extent of stray light. An example embodiment includes a method. The method includes capturing, using an optical detector system, an image of a scene that includes a bright object. The method also includes determining a location of the bright object within the image. Further, the method includes determining, based on the location of the bright object within the image, an extent of stray light from the bright object that is represented in the image. In addition, the method includes determining, by comparing the extent of stray light from the bright object that is represented in the image to a predetermined threshold extent of stray light, whether one or more defects are present within the optical detector system. The predetermined threshold extent of stray light corresponds to an expected extent of stray light.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting agent response times. One of the methods includes continually updating, at each time step of a plurality of time steps, an accumulated measure of surprise for the agent due to the movements of another entity in the traffic environment. A distribution of previously predicted trajectories is obtained at a previous time step for the other entity in the environment. A measure of surprise is computed from the perspective of the agent. An accumulated measure of surprise is updated for the time step using the computed measure of surprise for the agent. If the accumulated measure of surprise crosses a threshold at a particular point in time, a predicted response time for the agent is generated based on the particular point in time that the accumulated measure of surprise crosses the threshold.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
B60W 40/04 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes liés aux conditions de trafic
The technology relates to keeping sensors of a perception system optically clear and free from condensation. A transparent film, such as Indium Tin Oxide (ITO), acts as a moisture sensor that covers the optical area of interest. When a measured value of the moisture sensor meets a certain threshold that indicates the presence of condensate, power is applied to the sensor, turning it into a heater. When the measured value no longer meets the threshold, power is removed and heating ceases. The ITO layer may be lithographically applied to a glass sensor cover or other window, with interleaved sections of material that are spaced closely to detect a minimum amount of condensate. This arrangement enables the system to be employed in sensor assemblies at various locations along a self-driving vehicle, and can be used with different types of sensors such as lidar sensors, cameras and other imaging devices.
H05B 3/84 - Dispositions pour le chauffage spécialement adaptées à des surfaces transparentes ou réfléchissantes, p.ex. pour désembuer ou dégivrer des fenêtres, des miroirs ou des pare-brise de véhicules
H05B 1/02 - Dispositions de commutation automatique spécialement adaptées aux appareils de chauffage
H05B 3/34 - Eléments chauffants ayant une surface s'étendant essentiellement dans deux dimensions, p.ex. plaques chauffantes flexibles, p.ex. grillages ou tissus chauffants
B60S 1/56 - Nettoyage des pare-brise, fenêtres ou dispositifs optiques spécialement adaptés pour nettoyer d'autres parties ou dispositifs que les fenêtres avant ou les pare-brise
B60H 1/00 - Dispositifs de chauffage, de refroidissement ou de ventilation
B60S 1/02 - Nettoyage des pare-brise, fenêtres ou dispositifs optiques
Aspects of the present disclosure relate to a vehicle for maneuvering a passenger to a destination autonomously. The vehicle includes one or more computing devices and a set of user input buttons for communicating requests to stop the vehicle and to initiate a trip to the destination with the one or more computing devices. The set of user input buttons consisting essentially of a dual-purpose button and an emergency stopping button different from the dual-purpose button configured to stop the vehicle. The dual-purpose button has a first purpose for communicating a request to initiate the trip to the destination and a second purpose for communicating a request to pull the vehicle over and stop the vehicle. The vehicle has no steering wheel and no user inputs for the steering, acceleration, and deceleration of the vehicle other than the set of user input buttons.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
B60K 35/00 - Agencement ou adaptations des instruments
B60K 37/06 - Agencement des accessoires sur le tableau de bord des commandes, p.ex. boutons de commande
B60W 30/06 - Manœuvre automatique de stationnement
B60W 50/08 - Interaction entre le conducteur et le système d'aide à la conduite
B62D 15/02 - Indicateurs de direction ou aides de direction
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
B60K 28/02 - Dispositifs de sécurité pour la commande des ensembles de propulsion spécialement adaptés aux véhicules ou aménagés dans ceux-ci, p.ex. empêchant l'alimentation en carburant ou l'allumage en cas de danger sensibles à des conditions relatives au conducteur
89.
Light Detection and Ranging (LIDAR) Device Range Aliasing Resilience by Multiple Hypotheses
A computing system may operate a LIDAR device to emit light pulses in accordance with a time sequence including a time-varying dither. The system may then determine that the LIDAR detected return light pulses during corresponding detection periods for each of two or more emitted light pulses. Responsively, the system may determine that the detected return light pulses have (i) detection times relative to corresponding emission times of a plurality of first emitted light pulses that are indicative of a first set of ranges and (ii) detection times relative to corresponding emission times of a plurality of second emitted light pulses that are indicative of a second set of ranges. Given this, the system may select between using the first set of ranges as a basis for object detection and using the second set of ranges as a basis for object detection, and may then engage in object detection accordingly.
G01S 17/10 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement utilisant la transmission d'ondes à modulation d'impulsion interrompues
G01S 7/483 - DÉTERMINATION DE LA DIRECTION PAR RADIO; RADIO-NAVIGATION; DÉTERMINATION DE LA DISTANCE OU DE LA VITESSE EN UTILISANT DES ONDES RADIO; LOCALISATION OU DÉTECTION DE LA PRÉSENCE EN UTILISANT LA RÉFLEXION OU LA RERADIATION D'ONDES RADIO; DISPOSITIONS ANALOGUES UTILISANT D'AUTRES ONDES - Détails des systèmes correspondant aux groupes , , de systèmes selon le groupe - Détails de systèmes à impulsions
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
G01S 7/4865 - Mesure du temps de retard, p.ex. mesure du temps de vol ou de l'heure d'arrivée ou détermination de la position exacte d'un pic
G01S 17/42 - Mesure simultanée de la distance et d'autres coordonnées
Methods and devices for actively modifying a field of view of an autonomous vehicle in view of constraints are disclosed. In one embodiment, an example method is disclosed that includes causing a sensor in an autonomous vehicle to sense information about an environment in a first field of view, where a portion of the environment is obscured in the first field of view. The example method further includes determining a desired field of view in which the portion of the environment is not obscured and, based on the desired field of view and a set of constraints for the vehicle, determining a second field of view in which the portion of the environment is less obscured than in the first field of view. The example method further includes modifying a position of the vehicle, thereby causing the sensor to sense information in the second field of view.
B60R 1/00 - Dispositions pour la visibilité optique; Dispositions de visualisation en temps réel pour les conducteurs ou les passagers utilisant des systèmes de capture d’images optiques, p.ex. des caméras ou des systèmes vidéo spécialement adaptés pour être utilisés dans ou sur des véhicules
91.
PSYCHOMOTOR VIGILANCE TESTING FOR PERSONS TASKED WITH MONITORING AUTONOMOUS VEHICLES
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.
Example embodiments relate to using remote assistance to maneuver an autonomous vehicle to a location. A computing device used by a remote operator may receive a request for assistance from a vehicle that indicates the vehicle is stopped at a first location with one or more navigation options for enabling the vehicle to navigate from the first location to a second location. At least one navigation option includes a maneuver technique that requires operator approval prior to execution. The computing device may then display a graphical user interface (GUI) that conveys the one or more navigation options. Based on detecting a selection of a particular navigation option, the computing device may transmit instructions to the vehicle to perform the particular navigation option. The vehicle may configured to navigate from the first location to the second location by performing the particular navigation option while monitoring for changes in the environment.
B60W 60/00 - Systèmes d’aide à la conduite spécialement adaptés aux véhicules routiers autonomes
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
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.
Systems and methods are disclosed to identify a presence of a volumetric medium in an environment associated with a LIDAR system. In some implementations, the LIDAR system may emit a light pulse into the environment, receive a return light pulse corresponding to reflection of the emitted light pulse by a surface in the environment, and determine a pulse width of the received light pulse. The LIDAR system may compare the determined pulse width with a reference pulse width, and determine an amount of pulse elongation of the received light pulse. The LIDAR system may classify the surface as either an object to be avoided by a vehicle or as air particulates associated with the volumetric medium based, at least in part, on the determined amount of pulse elongation.
The present disclosure relates to multi-channel optical transmitter modules, lidar systems, and methods that involve micromirror devices. An example optical transmitter module includes at least one light-emitter device and a plurality of micromirror devices optically-coupled to the at least one light-emitter device. The at least one light-emitter device is configured to emit respective light beams toward an environment via the micromirror devices. The micromirror devices are configured to deflect the light beams. The optical transmitter module also includes a controller having at least one processor and a memory. The controller is configured to carry out operations. The operations include receiving information indicative of a retroreflector object in the environment. The operations include, based on the received information, causing at least one micromirror device of the plurality of micromirror devices to deflect at least one light beam so that the at least one light beam does not interact with the retroreflector object.
G02B 26/08 - Dispositifs ou dispositions optiques pour la commande de la lumière utilisant des éléments optiques mobiles ou déformables pour commander la direction de la lumière
Disclosed herein are systems and methods for providing supplemental identification abilities to an autonomous vehicle system. The sensor unit of the vehicle may be configured to receive data indicating an environment of the vehicle, while the control system may be configured to operate the vehicle. The vehicle may also include a processing unit configured to analyze the data indicating the environment to determine at least one object having a detection confidence below a threshold. Based on the at least one object having a detection confidence below a threshold, the processor may communicate at least a subset of the data indicating the environment for further processing. The vehicle is also configured to receive an indication of an object confirmation of the subset of the data. Based on the object confirmation of the subset of the data, the processor may alter the control of the vehicle by the control system.
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
B60W 40/04 - Calcul ou estimation des paramètres de fonctionnement pour les systèmes d'aide à la conduite de véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier liés aux conditions ambiantes liés aux conditions de trafic
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
G06V 20/58 - Reconnaissance d’objets en mouvement ou d’obstacles, p.ex. véhicules ou piétons; Reconnaissance des objets de la circulation, p.ex. signalisation routière, feux de signalisation ou routes
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G07C 5/00 - Enregistrement ou indication du fonctionnement de véhicules
One example system comprises a light source configured to emit light. The system also comprises a waveguide configured to guide the emitted light from a first end of the waveguide toward a second end of the waveguide. The waveguide has an output surface between the first end and the second end. The system also comprises a plurality of mirrors including a first mirror and a second mirror. The first mirror reflects a first portion of the light toward the output surface. The second mirror reflects a second portion of the light toward the output surface. The first portion propagates out of the output surface toward a scene as a first transmitted light beam. The second portion propagates out of the output surface toward the scene as a second transmitted light beam.
Aspects of the disclosure provide for advanced trip planning for an autonomous vehicle service. For instance, an example method may include determining a potential pickup location for a user, determining a set of potential destination locations for a user, and determining a set of potential trips. For each potential trip a vehicle of a fleet of autonomous vehicles of the service may be assigned and trip information, including an estimated time of arrival for the assigned vehicle of the potential trip to reach the destination location of the potential trip, may be determined. The trip information for each potential trip may be provided for display to the user. Thereafter, confirmation information identifying one of the set of potential trips may be received, and the assigned vehicle for one first of the set of potential trips may be dispatched to pick up the user.
G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
A camera module includes a housing with an opening and a portion that surrounds the opening, wherein the portion of the housing is transparent to near infrared (NIR) light. A fisheye lens is disposed within the opening such that a portion of the fisheye lens protrudes through the opening. An image sensor is disposed within the housing and optically coupled to the fisheye lens. The image sensor is sensitive to visible light and NIR light. A plurality of NIR light emitters is disposed within the housing. The NIR light emitters are configured to emit NIR light through the NIR-transparent portion of the housing. The NIR-transparent portion of the housing may include a light-diffusing structure, such as a pattern of microlenses formed on an inner surface of the NIR-transparent portion of the housing, to spread out the NIR light emitted by the NIR light emitters.
Aspects of the disclosure relate to controlling a vehicle in an autonomous driving mode using trajectories. For instance, a trajectory may be received by one or more first computing devices from one or more second computing devices. While the first computing devices are controlling the vehicle in the autonomous driving mode based on the trajectory, an error may be generated by second computing devices. Whether the error is a recoverable error may be determined, and if so, the second computing devices attempt to generate a new trajectory. When the second computing devices generate the new trajectory, the vehicle may be controlled by the first computing devices according to the new trajectory.
B60W 50/02 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour préserver la sécurité en cas de défaillance du système d'aide à la conduite, p.ex. en diagnostiquant ou en palliant à un dysfonctionnement
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
B60W 50/029 - Adaptation aux défaillances ou contournement par solutions alternatives, p.ex. en évitant l'utilisation de parties défaillantes
B60W 50/023 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier pour préserver la sécurité en cas de défaillance du système d'aide à la conduite, p.ex. en diagnostiquant ou en palliant à un dysfonctionnement Élimination des défaillances en utilisant des éléments redondants
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