An optical signal detection system includes a plurality of photodetectors configured to detect optical signals reflected from an environment surrounding the optical signal detection system and convert the optical signals into electrical signals. The optical signal detection system also includes an amplifier coupled to the plurality of photodetectors. The amplifier is shared by the plurality of photodetectors and configured to generate an output signal by amplifying an individual electrical signal converted by a corresponding photodetector. The optical signal detection system further includes a multiplexing circuit configured to selectively establish a connection between one of the plurality of photodetectors and the amplifier to amply the electrical signal converted by that photodetector.
Methods and systems of annotation densification for semantic segmentation are disclosed herein. In one example embodiment, such a method includes obtaining image information, obtaining coarse annotation information, performing an image matting operation based upon the image information and based at least indirectly upon the coarse annotation information, and applying an already-trained Convolutional Neural Network (ConvNet) semantic segmentation model in relation to the image information. The method also includes performing a merging operation with respect to both first intermediate information generated at least indirectly by the performing of the image matting operation and second intermediate information generated at least indirectly by the applying of the ConvNet model, where the performing of the merging operation results in fine semantic segmentation annotation information, whereby an additional semantic segmentation model can be trained using that annotation information and the trained additional semantic segmentation model can be applied to generate semantic segmentation output information.
G06K 9/66 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques utilisant des comparaisons ou corrélations simultanées de signaux images avec une pluralité de références, p.ex. matrice de résistances avec des références réglables par une méthode adaptative, p.ex. en s'instruisant
G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
3.
MULTI-AGENT REINFORCEMENT LEARNING FOR ORDER-DISPATCHING VIA ORDER-VEHICLE DISTRIBUTION MATCHING
Multi-agent reinforcement learning may be used for rider order-dispatching via matching the distribution of orders and vehicles. Information may be obtained. The information may include a plurality of vehicle locations of a plurality of vehicles, a plurality of ride orders, and a current time. The obtained information may be input into a trained model. The trained model may be based on Kullback-Leibler divergence optimization and independent agents under a guidance of a joint policy. A plurality of order-dispatching tasks may be generated for the plurality of vehicles to fulfill.
G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
G01C 21/00 - Navigation; Instruments de navigation non prévus dans les groupes
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 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
4.
JOINT ORDER DISPATCHING AND FLEET MANAGEMENT FOR ONLINE RIDE-SHARING PLATFORMS
Hierarchical multi-agent reinforcement learning may be used for joint order dispatching and fleet management for ride-sharing platforms. Information may be obtained. The information may include a status of a ride- sharing platform and a set of messages. The obtained information may be input into a trained hierarchical reinforcement learning (HRL) model. The trained HRL model may include at least one manager module corresponding to a region, and the at least one manager module may include a set of worker modules each corresponding to a division the region. At least one goal of the division in the region may be obtained based on the status of the ride- sharing platform and the set of messages. A vehicle action may be generated for each vehicle in the division in the region based on the status of the ride- sharing platform, the set of messages, and the at least one goal.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
G07B 15/02 - Dispositions ou appareils pour encaisser le prix des billets ou les droits d’entrée ou de péage en un ou plusieurs points de contrôle prenant en compte un facteur variable tel que la distance ou le temps, p.ex. pour le transport de passagers, les systèmes de parcs de stationnement ou les systèmes de location de véhicules
G08G 1/123 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p.ex. de véhicules à horaire déterminé
5.
SYSTEMS AND METHODS FOR MANAGING A COMPROMISED AUTONOMOUS VEHICLE SERVER
Systems and methods for managing a compromised autonomous vehicle server are described herein. A processor may obtain an indication of a first server configured to control an autonomous vehicle being compromised. The autonomous vehicle may have previously been provisioned with a first public key. The first public key may be paired with a first private key. A processor may compile command information. The command information may include a command for the autonomous vehicle and a digital certificate of a second server configured to control the autonomous vehicle in the event of the first server being compromised. The digital certificate may include a second public key and may be signed with the first private key. The command may be signed with a second private key associated with the second server. The second private key may be paired with the second public key.
Methods and systems for remotely executing or communicating messages or commands such as security commands, or facilitating the execution or communication of such messages or commands, are disclosed herein. In one example embodiment, such a system or method can include an agent application installed on a client device directing the client device to periodically check a server for a new command request for the client device, the client device downloading the new command request from the server, and the client device executing the new command request. Also, in an additional example embodiment, the new command request can direct the client device to set up a command session between the server and the client device and, responsive to executing the new command request, the client device can set up the command session with the server.
Methods and systems for downloading software information are disclosed herein. In one example embodiment, the method includes performing a first determination as to whether a first number of inquiries or download requests received by a server computer is or has been excessive and, if the first determination is that the first number of inquiries or download requests is not or has not been excessive, sending a signal including a first permission to download a software package. Also, the method includes performing a second determination as to whether either the first number or a second number of inquiries or download requests received by the server computer is or has been excessive and, if the second determination is that the first or second number of inquiries or download requests is not or has not been excessive, sending a first part of the software package for receipt by a first client computer.
Embodiments of the disclosure provide a method and system for processing a customer inquiry. The method includes obtaining multiple conversations. Each of the conversations includes multiple conversation entries associated with the conversation. The method also includes, for each of the conversations, generating a directed path from a start to an end of the historical conversation. The directed path includes multiple edges and vertices. Each of the edges represents a conversation entry or an API call associated with the conversation, and each of the vertices represents a state of the conversation. The method further includes generating a directed graph based on the generated directed paths and determining an optimized directed path based on the directed graph. The method also includes receiving a customer inquiry from a user device associated with a customer, and generating a response based on the optimized directed path.
G10L 21/00 - Traitement du signal de parole ou de voix pour produire un autre signal audible ou non audible, p.ex. visuel ou tactile, afin de modifier sa qualité ou son intelligibilité
9.
SYSTEMS AND METHODS FOR FRAUD DETECTING IN A TRANSPORTATION SERVICE
Embodiments of the disclosure provide systems and methods for fraud detecting in a transportation service. An exemplary method may include receiving user data from a terminal device associated with a user providing transportation service. The user data may include a location associated with the transportation service and positioning data of a geographical positioning system. The method may also include determining a first fingerprint based on the positioning data. The method may further include determining whether the first fingerprint matches a first reference fingerprint of a transmitter of the geographical position system corresponding to the location. Moreover, the method may include triggering a first fraud alert when the first fingerprint does not match the first reference fingerprint.
G01S 19/01 - Systèmes de positionnement par satellite à radiophares émettant des messages horodatés, p.ex. GPS [Système de positionnement global], GLONASS [Système global de navigation par satellite] ou GALILEO
10.
SYSTEMS AND METHODS FOR DEVICE FINGERPRINT DETERMINATION IN A TRANSPORTATION SERVICE
Embodiments of the disclosure provide systems and methods for determining fingerprint information of a terminal device in a transportation service. An exemplary system may include a communication interface configured to establish a communication link between first and second terminal devices and receive user data from the first terminal device associated with a user of the transportation service. The communication interface may also be configured to receive authentication information authenticating the second terminal device. The system may also include a memory configured to store the user data and at least one processor coupled to the memory. The at least one processor is configured to determine a first fingerprint of the first terminal device based on the user data after receiving the authentication information authenticating the second terminal device.
Embodiments of the disclosure provide a micromachined mirror assembly having a mirror-base layer, a first reflective layer on a top surface of the mirror-base layer, and a second reflective layer on a bottom surface of the mirror-base layer. In an example, the first reflective layer is reflective to incident light of the micromachined mirror assembly, and the first reflective layer and the second reflective layer are made of a same material and have same dimensions.
B81C 1/00 - Fabrication ou traitement de dispositifs ou de systèmes dans ou sur un substrat
B81B 7/02 - Systèmes à microstructure comportant des dispositifs électriques ou optiques distincts dont la fonction a une importance particulière, p.ex. systèmes micro-électromécaniques (SMEM, MEMS)
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
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
12.
METHOD AND SYSTEM FOR CONFIGURABLE DEVICE FINGERPRINTING
Methods and systems for configurable device fingerprinting and/or achieving communications with enhanced security are disclosed herein. In one example embodiment, a method of configurable device fingerprinting includes storing, at a server, first information regarding one or more selected system attributes, and further includes receiving, at the server, a first signal requesting that a first client device be registered and including system information pertaining to the first client device. Also, the method includes extracting, from the system information, relevant portions of the system information corresponding to the one or more selected system attributes, where the server determines a fingerprint of the first client device based at least in part the relevant portions. Additionally, the method includes generating a first identifier pertaining to the first client device at least indirectly in response to the extracting of the relevant portions, and sending the first identifier for receipt by the first client device.
Methods and systems involving convolutional neural networks as applicable for semantic segmentation, including multi-task convolutional networks employing curriculum based transfer learning, are disclosed herein. In one example embodiment, a method of semantic segmentation involving a convolutional neural network includes training and applying the convolutional neural network. The training of the convolutional neural network includes each of training a semantic segmentation decoder network of the convolutional neural network, generating first feature maps by way of an encoder network of the convolutional neural network, based at least in part upon a dataset received at the encoder network, and training an instance segmentation decoder network of the convolutional neural network based at least in part upon the first feature maps. The applying includes receiving an image, and generating each of a semantic segmentation map and an instance segmentation map in response to the receiving of the image, in a single feedforward pass.
Embodiments of the disclosure provide methods and systems for generating a customer inquiry processing model for processing customer inquiries. The method includes obtaining a conversation log comprising a plurality of conversation entries associated with a conversation between a customer and an agent. The method also includes identifying, from the conversation entries, a slot of key information and determining that the identified slot relates to an application program interface (API) call. The method also includes obtaining an API log comprising a plurality of API calls associated with the conversation, and identifying an API call from the API calls included in the API call log based on the identified slot. The method further includes associating the identified slot with the corresponding API call and generating a customer inquiry processing model for processing a customer inquiry based on information relating to the identified slot and the corresponding API call.
Embodiments of the disclosure provide systems and methods for fraud detection in a transportation service. An exemplary system may include a communication interface configured to receive user data from a terminal device associated with a user providing the transportation service. The user data may include identification information of the terminal device. The system may also include a memory configured to store the user data. The system may also include at least one processor coupled to the memory. The processor may be configured to determine a first fingerprint based on the identification information. The processor may be further configured to determine whether the first fingerprint matches a first reference fingerprint associated with a registered terminal device. Moreover, the processor may be configured to generate a first notice when the first fingerprint does not match the first reference fingerprint.
G01S 19/01 - Systèmes de positionnement par satellite à radiophares émettant des messages horodatés, p.ex. GPS [Système de positionnement global], GLONASS [Système global de navigation par satellite] ou GALILEO
16.
SYSTEMS AND METHODS FOR SAFE ROUTE PLANNING FOR A VEHICLE
Technologies are disclosed that determine when alternative routes are to be pre-generated for a vehicle. A route planning system receives a request for a navigation route for a vehicle. The navigation route is generated, where the navigation route includes navigation nodes. For a given navigation node, a corresponding weight and/or a probability of an exception event occurring are determined, and are used to determine whether to generate an alternate route configured to be utilized in response to a future detection by the vehicle of an exception event associated with the given node. The route planning system may then generate alternate routes accordingly, and may transmit the navigation route and an alternate route for a corresponding given node to the vehicle. The navigation route may be used to navigate the vehicle, and the alternate route may be used to navigate the vehicle if an exception event is detected.
Technologies are disclosed that are used to control the transmission and processing of vehicle telemetry data. Routing data configured to be used to navigate the vehicle is accessed. Using the routing data, telemetry broadcast parameters are generated. The telemetry broadcast parameters are transmitted to the vehicle. Transmissions of telemetry data in accordance with the broadcast parameters are received from the vehicle. The received telemetry data is used in generating a simulated environment for a route planning learning engine, in simulating a vehicle, in validating routes and maps, and/or in performing vehicle diagnostics.
A method and systems for loading and tracking maps on a moving vehicle. One method includes obtaining a geographic location of a system on a vehicle, obtaining a boundary corresponding to a contiguous geographical boundary area around the geographic location of the system, loading map data comprising a plurality of map data tiles each including a portion of the geographical boundary area, the plurality of map data tiles including a center tile having a point corresponding to the system location and surrounding map data tiles. The method further includes obtaining an updated system location, and if the updated geographic location is outside of the boundary area, obtaining an updated boundary centered on the updated geographic location and loading map data based on the updated boundary such that the resulting loaded map data includes a center tile and map data tiles surrounding the center tile that intersect the geographical boundary area.
A first data tree and a second data tree may be accessed. The first data tree may include a first set of directory nodes and a first set of file nodes, and the second data tree may include a second set of directory nodes and a second set of file nodes. The first data tree may be converted into a first data tree file, and the second data tree may be converted into a second data tree file. A delta for the first data tree and the second data tree may be generated based on a comparison of the first data tree file and the second data tree file.
Embodiments of the disclosure provide control systems and methods for controlling a pulsed laser diode and a sensing device including a pulsed laser diode. An exemplary control system includes a distance detector configured to generate a distance signal indicating a distance between the pulsed laser diode and an object reflecting pulsed laser beams emitted by the pulsed laser diode. The control system may also include a controller configured to dynamically control power supplied to the pulse laser diode based on the distance signal.
H01S 5/062 - Dispositions pour commander les paramètres de sortie du laser, p.ex. en agissant sur le milieu actif en faisant varier le potentiel des électrodes
G01S 17/88 - Systèmes lidar, spécialement adaptés pour des applications spécifiques
G01B 11/24 - Dispositions pour la mesure caractérisées par l'utilisation de techniques optiques pour mesurer des contours ou des courbes
G01S 17/08 - Systèmes déterminant les données relatives à la position d'une cible pour mesurer la distance uniquement
Systems and methods for vehicle identification are described herein. A set of vehicle identification information may be obtained from a set of autonomous vehicles. Individual vehicle identification information may convey identifications of one or more vehicles and locations of the one or more vehicles. Vehicle context information for individual vehicles may be determined from the set of vehicle identification information. The vehicle context information for the individual vehicles may describe a context of the individual vehicles. The context may include one or a combination of a speed of travel, a direction of travel, a trajectory, or an identity profile.
G08G 1/127 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p.ex. de véhicules à horaire déterminé à une station centrale
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
A shared memory message system for communication between modules configured to perform a function related to controlling a vehicle in a computer system on the vehicle. The system may include a plurality of modules each representative as a node, the plurality of modules collectively representative as a plurality of nodes, each node a publisher node and/or a subscriber node, a topic registry having message storage location information, message buffers configured to store published messages, and a communication bus coupled to the topic registry, the message buffers, and the plurality of nodes. The communication bus is configured such that publisher node messages are stored in a message buffer and associated storage location information is stored in the topic registry without going through the kernel of the computer system, and such that subscriber nodes can read messages from a message buffer without going through the computer system kernel.
G06F 16/13 - Structures d’accès aux fichiers, p.ex. indices distribués
G06F 12/02 - Adressage ou affectation; Réadressage
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
23.
MESSAGE BUFFER FOR COMMUNICATING INFORMATION BETWEEN VEHICLE COMPONENTS
A method of communicating between a plurality of modules on a vehicle, each module configured as a publisher or subscriber node that communicate in the operation of the autonomous vehicle utilizing a shared memory communication system. The method may include generating groups of messages by publisher nodes, each group associated with a unique topic and generated by a single publisher node associated with the unique topic, writing a group of messages in a message buffer associated with a single topic, writing in a registry, location information indicating where the messages were written, reading new message information from the registry, the new message information indicative of whether a new message associated with a particular topic is available, reading location information indicating where the new message is stored if a new message is available, and reading the new message from the respective message buffer.
G06F 16/13 - Structures d’accès aux fichiers, p.ex. indices distribués
G06F 12/02 - Adressage ou affectation; Réadressage
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
A vehicle can include an on-board data processing system that receives velocity data captured by one or more sensors of the vehicle. As a vehicle travels along a route, the on-board data processing system can process the velocity data to identify potential vehicle stops. For example, the system can detect a trough in velocity values, and determine whether a velocity value at the trough is below a threshold velocity value. If the velocity value is below the threshold velocity value, the system can determine whether any vehicle stops were previously detected within a threshold time of the time corresponding to the trough. If a vehicle stop was previously detected, the system may detect that a stop occurred at the time of the trough if the velocity of the vehicle increased by at least a velocity ripple value between the time of the previously-detected stop and the time of the trough.
A method of communicating messages between modules in a system on a vehicle, each module configured as a publisher node and/or subscriber node, the publisher nodes and the subscriber nodes collectively forming a plurality of nodes that communicate in the operation of the vehicle. One method includes communicating, by a subscriber node, with a registry for information to determine if a new message associated with a first topic is available for reading, determining, by each subscriber node, if a new message associated with the first topic is available for reading, in response to determining a new message associated with the first topic is available for reading, reading from the registry location information indicating where the first message is stored in a first message buffer, and reading, by each subscriber node the first message from the first message buffer using the location information.
G06F 16/13 - Structures d’accès aux fichiers, p.ex. indices distribués
G06F 12/02 - Adressage ou affectation; Réadressage
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
26.
WRITING MESSAGES IN A SHARED MEMORY ARCHITECTURE FOR A VEHICLE
A method of communicating messages between a plurality of modules in a system on a vehicle, each module of the plurality of modules implemented on at least one processor and configured as a publisher node and/or a subscriber node and collectively forming a plurality of nodes that communicate in the operation of the vehicle. The method may include generating a first message associated with a first topic by a first publisher node, writing, by the first publisher node, the first message in a memory location in a first message buffer of the plurality of message buffers, the first message buffer associated with the first topic and configured to store a plurality of messages associated with the first topic, and writing in a registry information associated with writing the first message, the registry configured to store location information of the first message.
G06F 16/13 - Structures d’accès aux fichiers, p.ex. indices distribués
G06F 12/02 - Adressage ou affectation; Réadressage
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
In some embodiments, a method for operating a light detection and ranging (LiDAR) system in an automobile provides a more accurate range estimate by combining multiple processed waveforms which are weighted according to their signal to noise ratios. At least one waveform is transmitted within a first time period, and reflected of an object. The reflected waveform is received and processed to improve the signal to noise ratio (SNR). The processing produces a higher number of output waveforms, such as through processing convolution. The SNR for each of the output waveforms is determined. An estimated range to the object from each output waveform is determined. The estimated ranges are then weighted according to their SNRs, and combined to provide an final determined range to the object.
G01S 7/487 - Extraction des signaux d'écho désirés
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 17/88 - Systèmes lidar, spécialement adaptés pour des applications spécifiques
28.
SYSTEM AND METHOD FOR UPDATING VEHICLE OPERATION BASED ON REMOTE INTERVENTION
Technologies disclosed relate to a remote intervention system for the operation of a vehicle, which can be an autonomous vehicle, a vehicle that includes driver assist features, a vehicle used for ride sharing services or the like. The system includes a vehicle sending a request for remote intervention to a remote operator when the operation of the vehicle is suspended. The request for remote intervention can include a request for object identification or a request for decision confirmation. The vehicle can update vehicle operation based in part on vehicle-based sensor data and a response to the remote intervention request from the remote operator. The remote operator can be a human operator or an AI operator.
B60W 30/02 - Commande de la stabilité dynamique du véhicule
H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p.ex. véhicule à nuage ou véhicule à domicile
29.
ARCHITECTURE FOR SIMULATION OF DISTRIBUTED SYSTEMS
Systems and methods are provided for the deterministic simulation of distributed systems, such as vehicle-based processing systems. A distributed system may be represented as a plurality of subsystems or "nodelets" executing with a single process of a computing device during a simulation. The nodelets may communicate using in-process communication. A task scheduler can schedule the nodelets to execute separately in serially-occurring frames. A simulated clock may be used to mitigate the variability in timestamped data that may be caused by latency or jitter.
G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p.ex. pour le traitement simultané de plusieurs programmes
G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
30.
DISTRIBUTED SYSTEM TASK MANAGEMENT USING A SIMULATED CLOCK
Systems and methods are provided for the deterministic simulation of distributed systems, such as vehicle-based processing systems. A distributed system may be represented as a plurality of subsystems or "nodelets" executing with a single process of a computing device during a simulation. A simulated clock may be used during execution of the nodelets to mitigate the variability in timestamped data that may be caused by latency or jitter. In some embodiments, all timestamps generated during a given frame of work will be assigned the same time value, regardless of when within the frame the timestamps were generated. A task scheduler can update the value of the simulated clock as execution proceeds through different frames of work.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p.ex. pour le traitement simultané de plusieurs programmes
G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
Systems and methods are provided for the deterministic simulation of distributed systems, such as vehicle-based processing systems. A distributed system may be represented as a plurality of subsystems or "nodelets" executing with a single process of a computing device during a simulation. A task scheduler can schedule the nodelets to execute separately, on a single thread, in serially-occurring frames. In some embodiments, only one nodelet is permitted to execute during any given frame, and therefore only one nodelet is permitted to execute at any given time.
G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p.ex. pour le traitement simultané de plusieurs programmes
A method comprising: adhering a first surface of a mask to a carrier substrate via a first adhesive layer; forming a second adhesive layer on at least one of a second surface of the mask or a third surface of a wafer having a second alignment mark; bringing the carrier substrate and the wafer towards each other along a vertical axis such that the second surface of the mask and the third surface of the wafer is separated by an alignment gap based on a thickness of the second adhesive layer; performing an alignment operation based on imaging the first alignment mark and the second alignment mark; configuring the second surface of the mask to adhere to the third surface of the wafer via the second adhesive; and disconnecting the carrier substrate from the mask.
B81C 1/00 - Fabrication ou traitement de dispositifs ou de systèmes dans ou sur un substrat
C23C 14/04 - Revêtement de parties déterminées de la surface, p.ex. au moyen de masques
H01L 21/02 - Fabrication ou traitement des dispositifs à semi-conducteurs ou de leurs parties constitutives
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
G01S 17/00 - Systèmes utilisant la réflexion ou la reradiation d'ondes électromagnétiques autres que les ondes radio, p.ex. systèmes lidar
33.
SYSTEMS AND METHODS FOR LOADING OBJECT GEOMETRY DATA ON A VEHICLE
A method and systems for loading object data on a moving vehicle. One system includes a data storage component configured to store object geometry data in a data structure such that a portion of the stored object geometry data representing an area around the vehicle may be retrieved, at least one processor having a memory component and configured to retrieve portions of the object geometry data from the data storage component and store the retrieved object geometry data in the memory component. The at least one processor also configured to obtain a location of the vehicle, determine data retrieval information based on the vehicle location, the data retrieval information defining a proximal portion of the object geometry data that is within a certain distance of the vehicle, and retrieve the proximal portion of the object geometry data from the data storage component and store it in the memory component.
Embodiments of the disclosure provide a system for analyzing noise data for light detection and ranging (LiDAR). The system includes a communication interface configured to sequentially receive noise data of the LiDAR in time windows, at least one storage device configured to store instructions, and at least one processor configured to execute the instructions to perform operations. Exemplary operations include determining an estimated noise value of a first time window using the noise data received in the first time window and determining an instant noise value of a second time window using the noise data received in the second time window. The second time window is immediately subsequent to the first time window. The operations also include determining an estimated noise value of the second time window by aggregating the estimated noise value of the first time window and the instant noise value of the second time window.
A first data tree of a first version of the software and a second data tree of a second version of the software may be provided. The first data tree may be converted into a first data tree file, and the second data tree may be converted into a second data tree file. A delta for the first data tree and the second data tree may be generated based on a comparison of the first data tree file and the second data tree file. The delta may be packaged for provision to a client-side agent. The client-side agent may be configured to modify a client-side version of the software based on the delta.
Systems and processes can automatically identify lane markings within images through the use of a machine learning model. The machine learning model may use a reduced set of data and output an improved estimate of lane markings by applying normalized data or images to the machine learning model. Each image applied to the model can be normalized by, for example, rotating each of the images such that the depicted roads are horizontal or otherwise share the same angle. By aligning disparate images of roads, it is possible to reduce the amount of data applied to the model or to model generation, and to increase the accuracy of the machine learning model. Further, the use of normalized images by the machine learning model enables a reduction in computing resources used to apply data to the machine learning model to, for example, identify lane markings within images.
Systems and processes can reduce or divide images of road networks into sub-images that depict straight or substantially straight sections of roads in the road networks. These sub-images or image segments can be normalized by, for example, rotating each of the sub-images such that the depicted roads are horizontal or otherwise share the same angle. By aligning disparate images of roads, it is possible to both reduce the amount of training data used to generate a machine learning model and to increase the accuracy of an automated lane marking or labelling system. Further, the use of normalized images by the machine learning model enables a reduction in computing resources used to perform automated lane marking processes while maintaining or improving accuracy of the lane marking processes.
Systems and processes can reduce an amount of training data used to generate a machine learning model while maintaining or improving a resultant of the machine learning model. The amount of training data may be reduced by pre-processing the training data to normalize the training data. The training data may include images of portions of an elongated object, such as a road. Each of the images can be normalized by, for example, rotating each of the images such that the depicted roads are horizontal or otherwise share the same angle. By aligning disparate images of roads, it is possible to reduce the amount of training data and to increase the accuracy of the machine learning model. Further, the use of normalized images by the machine learning model enables a reduction in computing resources used to apply data to the machine learning model to, for example, identify lane markings within images.
Systems and methods are disclosed related to generating an interactive user interface that enables a user to move, rotate or otherwise edit 3D point cloud data in virtual 3D space to align or match point clouds captured from LiDAR scans prior to generation of a high definition map. A system may obtain point cloud data for two or more point clouds, render the point clouds for display in a user interface, then receive a user selection of one of the point clouds and commands from the user to move and/or rotate the selected point cloud. The system may adjust the displayed position of the selected point cloud relative to the other simultaneously displayed point cloud(s) in real time in response to the user commands, and store the adjusted point cloud position data for use in generating a new high definition map.
G01C 21/26 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
G06F 3/048 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI]
G01S 17/88 - Systèmes lidar, spécialement adaptés pour des applications spécifiques
B60W 40/02 - 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
40.
INTERFACE FOR IMPROVED HIGH DEFINITION MAP GENERATION
Systems and methods are disclosed related to generating interactive user interfaces that enable a user to alter 3D point cloud data and/or associated pose graph data generated from LiDAR scans prior to generation of a high definition map. A user may make selections in a 2D map representation with overlaid graph node indicators in order to alter graph connections, remove nodes, view corresponding 3D point clouds, and otherwise edit intermediate results from LiDAR scans in order to improve the quality of a high definition map subsequently generated from the user-manipulated data.
G01C 21/26 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
G06F 3/048 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI]
G01S 17/88 - Systèmes lidar, spécialement adaptés pour des applications spécifiques
B60W 40/02 - 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
41.
THREE-DIMENSIONAL LIGHT DETECTION AND RANGING SYSTEM USING HYBRID TDC AND ADC RECEIVER
A method for operating a LiDAR system in an automobile that can include sending light pulses toward an object; receiving analog sensor data from an optical sensor measuring the light pulses reflected off the object; digitizing the analog sensor data using an analog to digital conversion system having a first sampling rate to generate a first set of processed sensor data and using a time to digital conversion system having a second sampling rate that is greater than the first sampling rate to generate a second set of processed sensor data; selecting the first set of processed sensor data when the analog sensor data is beneath a threshold signal to noise ratio; selecting the second set of processed sensor data when the analog sensor data exceeds the threshold signal to noise ratio; and calculating a range between the LiDAR system and the object by extracting time of flight data from the selected set of processed sensor data.
G04F 10/00 - Appareils pour mesurer des intervalles de temps inconnus par des moyens électriques
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 17/93 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions
42.
SYSTEM AND METHODS FOR RANGING OPERATIONS USING MULTIPLE SIGNALS
Method and system for performing ranging operation are provided. In one example, a transmitter is configured to transmit a first signal having a first signal level and a second signal having a second signal level, the second signal being transmitted after the first signal, the first signal and the second signal being separated by a time gap configured based on a minimum distance of a range of distances to be measured by the LiDAR module. The first signal level and the second signal level are configured based on the range of distances to be measured by the LiDAR module, a range of levels of reflectivity of a target object to be detected by the LiDAR module, and a dynamic range of a receiver circuit to receive the first signal and the second signal. Ranging operation can be performed based on the time-of-flight of at least one of the first signal or the second signal.
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
43.
VEHICLE-PROVIDED VIRTUAL STOP AND YIELD LINE CLUSTERING
A server in communication with multiple vehicles can receive virtual stop or yield line data from such vehicles. The virtual stop or yield line data may correspond to different vehicles that stopped at the same intersection at the same or at different points in time. The server can aggregate or cluster the virtual stop or yield line data to identify a representative virtual stop or yield line that can be used to aid vehicles when navigating, driving, and/or maneuvering in the future. The representative virtual stop or yield line can be a virtual stop or yield line corresponding to virtual stop or yield line data transmitted by a particular vehicle or can be any combination of virtual stop or yield lines corresponding to virtual stop or yield line data transmitted by one or more vehicles.
A server in communication with multiple vehicles can receive virtual stop or yield line data from such vehicles. The virtual stop or yield line data may correspond to different vehicles that stopped at the same intersection at the same or at different points in time. The server can identify a representative virtual stop or yield line using the received virtual stop or yield line data, and validate the representative virtual stop or yield line using map data. Once validated, the server can update map data to incorporate the representative virtual stop or yield line, and transmit the updated map data to one or more vehicles to aid such vehicles when navigating, driving, and/or maneuvering in the future.
G01C 21/28 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier avec corrélation de données de plusieurs instruments de navigation
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
B60W 30/08 - Anticipation ou prévention de collision probable ou imminente
45.
VEHICLE-BASED VIRTUAL STOP AND YIELD LINE DETECTION
A vehicle can include an on-board data processing system that receives sensor data captured by various sensors of the vehicle. As a vehicle travels along a route, the on-board data processing system can process the captured sensor data to identify a potential vehicle stop. The on-board data processing system can then identify geographical coordinates of the location at which the potential vehicle stop occurred, use artificial intelligence to classify a situation of the vehicle at the potential stop, and determine whether the stop was caused by an unmarked intersection or a location at which vehicles typically yield to oncoming traffic using the classification and/or map data. If the stop was caused by an unmarked intersection or a yielding maneuver, the on-board data processing system can generate virtual stop or yield line data corresponding to the identified geographic coordinates and transmit this data to a server over a network for processing.
A vehicle can include an on-board data processing system that receives sensor data captured by various sensors of the vehicle. As a vehicle travels along a route, the on-board data processing system can process the captured sensor data to identify a potential vehicle stop. The on-board data processing system can then identify geographical coordinates of the location at which the potential vehicle stop occurred, use artificial intelligence to classify a situation of the vehicle at the potential stop, and determine whether the stop was caused by a road obstacle, such as a speed bump, a gutter, an unmarked crosswalk, or any other obstacle not at an intersection. If the stop was caused by the road obstacle, the on-board data processing system can generate virtual stop or yield line data corresponding to the identified geographic coordinates and transmit this data to a server over a network for processing.
In some embodiments, a method for operating a light detection and ranging (LiDAR) system in an automobile provides a more accurate range estimate by combining multiple processed waveforms which are weighted according to their signal to noise ratios. At least one waveform is transmitted within a first time period, and reflected of an object. The reflected waveform is received and processed to improve the signal to noise ratio (SNR). The processing produces a higher number of output waveforms, such as through processing convolution. The SNR for each of the output waveforms is determined. An estimated range to the object from each output waveform is determined. The estimated ranges are then weighted according to their SNRs, and combined to provide an final determined range to the object.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
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
48.
TRUSTED PLATFORM PROTECTION IN AN AUTONOMOUS VEHICLE
Disclosed are techniques for securing electronic control units (ECUs) in a vehicle. A security platform for a vehicle includes a key distribution center (KDC) for the vehicle. The KDC is con-figured to verify that a digital certificate associated with a first electronic control unit (ECU) on the vehicle is a valid certificate, where the digital certificate indicates a first security level of the first ECU. The KDC is configured to generate, based on the first security level of the first ECU, one or more security keys for secure communication between the first ECU and a set of ECUs on the vehicle, and provision the one or more security keys to the first ECU and the set of ECUs. In some embodiments, the KDC uses the provisioned keys to authenticate each ECU when the ve-hicle is powered up.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
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
49.
SYSTEM AND METHOD FOR REMOTE INTERVENTION OF VEHICLES
Technologies disclosed relate to a remote intervention system for the operation of a vehicle, which can be an autonomous vehicle, a vehicle that includes driver assist features, a vehicle used for ride sharing services or the like. The system includes a remote operator receiving a request for remote intervention from a vehicle when the operation of the vehicle is suspended and sending a response to the vehicle. The vehicle can transmit visual data detected by one or more sensors on the vehicle to the remote operator. The remote operator can output a response after analyzing the visual data transmitted by the vehicle. The remote operator can be a human operator or an AI operator. The response can result in an update of the vehicle operation.
B60W 30/02 - Commande de la stabilité dynamique du véhicule
H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p.ex. véhicule à nuage ou véhicule à domicile
Similarity between files nodes of two data tree may be classified based on file names, file paths, and file values. Similarity between directory nodes of two data trees. Responsive to similarity between a file node of a data tree being classified within a no match level: (1) a matching file node of the other data tree may be identified based fingerprints, and (2) a file-node delta may be determined between the file node and the matching file node. A delta between the two data trees may be generated based on the classification of similarity between the file nodes, the classification of similarity between the directory nodes, and the file-node delta.
Embodiments of the disclosure provide micromachined mirror assemblies and hybrid driving methods thereof. In one example, a micromachined mirror assembly includes a base and an array of micro mirrors affixed on the base. The base is configured to tilt around a base tilting axis. Each micro mirror in the array of micro mirrors is configured to tilt around a respective mirror tilting axis. Each of the mirror tilting axes is parallel to one another and is nonparallel to the base tilting axis.
Embodiments of the disclosure provide transmitters for light detection and ranging (LiDAR). The transmitter includes a laser source configured to provide a plurality of native laser beams, and a light modulator configured to receive and modulate the plurality of native laser beams to form an output laser beam. The output laser beam includes a plurality of modulated laser beams. Each of the plurality of modulated laser beams has a chief ray. A first set of the chief rays on margins of the output laser beam are parallel to one another along an optical axis.
Embodiments of the disclosure provide systems and methods for determining depth information in a two-dimensional (2D) image. An exemplary system may include a processor and a non-transitory memory storing instructions that, when executed by the processor, cause the system to perform the various operations. The operations may include receiving a first feature map based on the 2D image and applying an extraction network having a convolution operation and a pooling operation to the first feature map to obtain a second feature map. The operations may also include applying a reconstruction network having a deconvolution operation to the second feature map to obtain a depth map.
Systems and methods for managing networked communication sessions are described herein. A processor may obtain, by a driver running in a first operating mode of the one or more processors, session information and content information from a client application to be communicated to an external entity over a network. The processor may redirect, by the driver, the session information and the content information to a local proxy running in a second operating mode of the one or more processors via a local listening port of the local proxy. The redirecting may comprise modifying the session information to generate modified session information. The processor may obtain, at the local proxy, the modified session information and the content information. The processor may establish a communication channel between the local proxy and the external entity by modifying the modified session information to communicate the content information to the external entity.
A first data tree may include a first set of directory nodes and a first set of file nodes. A second data tree may include a second set of directory nodes and a second set of file nodes. Similarity between the first set of file nodes and the second set of file nodes may be classified based on file names, file paths, and file values. Similarity between the first set of directory nodes and the second set of directory nodes may be classified based on directory names, directory paths, nested folders, and included files. A delta between the first data tree and the second data tree may be generated based on the classification of similarity between the first set of file nodes and the second set of file nodes and the classification of similarity between the first set of directory nodes and the second set of directory nodes.
Fingerprints of file node(s) within a first data tree and file node(s) within a second data tree may be generated. The first data tree may include a first set of directory nodes and a first set of file nodes. The second data tree may include a second set of directory nodes and a second set of file nodes. A delta between the first data tree and the second data tree may be generated based on a first classification of similarity between the first set of file nodes and the second set of file nodes, a second classification of similarity between the first set of directory nodes and the second set of directory nodes, and file-node delta(s) between file node(s) of the first set of file nodes and file node(s) of the second set of file nodes. The file-node delta(s) determined based on two or more of the fingerprints.
Embodiments of the disclosure provide a micromachined mirror assembly having multiple coating layers. In one example, the micromachined mirror assembly includes a micro mirror having a first thermal expansion coefficient, a reflective layer having a second thermal expansion coefficient, and a compensation layer having a third thermal expansion coefficient. The reflective layer is disposed on a top surface of the micro mirror and is reflective to incident light of the micromachined mirror assembly. The compensation layer is disposed on the reflective layer and is transparent to the incident light of the micromachined mirror assembly. The first thermal expansion coefficient is between the second thermal expansion coefficient and the third thermal expansion coefficient.
B81B 7/02 - Systèmes à microstructure comportant des dispositifs électriques ou optiques distincts dont la fonction a une importance particulière, p.ex. systèmes micro-électromécaniques (SMEM, MEMS)
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
Exception lists may be generated by combing a standard list and a client list. Standard benign file information identifying a set of standard benign files may be obtained. A set of standard signatures for the set of standard benign files may be obtained. Client benign file information identifying a set of client benign files for a client may be obtained. A set of client signatures for the set of client benign files for the client may be obtained. A client exception list for the client may be generated based on the set of standard signatures and the set of client signatures.
G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
59.
BIPOLAR STAGGERED COMB DRIVE FOR BIDIRECTIONAL MEMS ACTUATION
Embodiments of the disclosure provide a comb drive, a comb drive system, and a method of operating the comb drive to rotate bi-directionally in a MEMS environment. An exemplary comb drive system may include a comb drive, at least one power source, and a controller. The comb drive may include a stator comb having a first electrically conductive layer spaced apart from a second electrically conductive layer. The comb drive may also include a rotor comb having a first electrically conductive layer spaced apart from a second electrically conductive layer. The controller may be configured to apply first and second voltage levels having opposite polarities to the first and second electrically conductive layers of the rotor comb, respectively. The controller may also be configured to apply an intermediate voltage level to one of the first or second electrically conductive layers of the stator comb.
Systems and methods are provided for forming a vehicle train. An exemplary method may comprise: detecting, by a first vehicle, a second vehicle traveling in the same direction as the first vehicle on a road; receiving travel information of the second vehicle; determining, by the first vehicle, a lead vehicle of the vehicle train between the first vehicle and the second vehicle based on travel information of the first vehicle and the travel information of the second vehicle; and connecting the first vehicle and the second vehicle to form the vehicle train.
Sensor information and map information may be obtained. The sensor information may characterize positions of objects in an environment of a sensor. The map information may characterize a road configuration in an environment of a vehicle. A sensor range configuration for the vehicle may be determined based on the road configuration in the environment of the vehicle. A portion of the sensor information may be processed for vehicle navigation based on the sensor range configuration.
G01C 21/26 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
G01S 13/36 - Systèmes pour mesurer la distance uniquement utilisant la transmission d'ondes continues, soit modulées en amplitude, en fréquence ou en phase, soit non modulées avec comparaison en phase du signal reçu avec le signal transmis au même moment
G01S 17/02 - Systèmes utilisant la réflexion d'ondes électromagnétiques autres que les ondes radio
G01S 17/93 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour prévenir les collisions
62.
PASSWORD AUTHENTICATION WITH INPUT PATTERN ANALYSIS
Password information and password input pattern information for a user may be obtained. The password information may define a password submitted by the user. The password input pattern information may define an input pattern with which the password was inputted by the user. The password may be compared with a predefined password for the user. The input pattern may be compared with a predefined input pattern for the user. The password may be authenticated based on a first match between the password and the predefined password and a second match between the input pattern and the predefined input pattern.
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Embodiments of the disclosure provide receivers for a light detection and ranging (LiDAR) scanner. The receiver includes a photodetector configured to receive a laser beam, and convert the received laser beam to an electrical signal including a plurality of pulses. The receiver also includes an amplifier configured to amplify the electrical signal. The receiver further includes a pulse equalizer configured to sharpen the plurality of pulses in the amplified electrical signal. Each pulse is sharpened to have a narrower width and an increased amplitude.
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 17/88 - Systèmes lidar, spécialement adaptés pour des applications spécifiques
A method for ride order dispatching comprises: obtaining a current location of a current vehicle from a computing device associated with the current vehicle; obtaining a current list of available orders nearby based on the current location; feeding the current location, the current list of available orders nearby, and a current time to a trained Markov Decision Process (MDP) model to obtain action information, the action information being repositioning the current vehicle to another current location or completing a current ride order by the current vehicle; and transmitting the generated action information to the computing device to cause the current vehicle to reposition to the another current location, stay at the current location, or accept the current ride order by proceeding to a pick-up location of the current ride order.
G06N 7/00 - Agencements informatiques fondés sur des modèles mathématiques spécifiques
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
A method for operating a LiDAR system in an automobile that can include receiving noise data corresponding to an ambient noise level, receiving false positive data corresponding to a rate of false positive object detection occurrences; determining an object detection range spanning a distance defined by a minimum range of object detection and a maximum range of object detection for the LiDAR system; generating an object detection threshold value for detecting objects based on the noise data and the rate of false positive data; applying the object detection threshold value to each of a plurality of range values within the object detection range; and applying a gain sensitivity profile to the object detection threshold value at each of a plurality of range values.
Methods and systems for light steering are proposed. In one example, an apparatus comprises: a light source; a receiver; a microelectromechanical system (MEMS) and a controller. The MEMS comprises: an array of first rotatable mirrors to receive and reflect the light beam from the light source and a second rotatable mirror to receive the light beam reflected by the array of first rotatable mirrors. The controller is configured to rotate, respectively, the array of first rotatable mirrors and the second rotatable mirror to set a first angle of light path with respect to a first dimension and to set a second angle of the light path with respect to a second dimension orthogonal to the first dimension to perform at least one of: reflecting light from the light source along the light path, or reflecting input light propagating along the light path to the receiver.
An array of micro mirrors is used to beam steer a laser for Light Detection and Ranging (LiDAR) applications. The micro mirrors in the array are driven in a nonlinear motion to synchronize motion. The system comprises a spring, a combdrive actuator with stator and rotor fingers, a shaft, a limiter to limit a range of mirror motion. A method of using the array comprises steps of providing drive signals, determining oscillation of mirrors out of sync, altering the drive signal to change phase difference. The method comprises steps of identifying a steady state of operation and starting to rotate the system at an initial phase to operate at the steady state. The method comprises steps of moving mirrors having first and second steady states of operations and configuring the mirrors to have starting parameters to operate at the first steady state.
Embodiments of the disclosure provide transmitters for light detection and ranging (LiDAR). The transmitter includes a plurality of laser sources and a light modulator. Each of the laser sources includes interleaved emitting regions and gaps and is configured to provide a native laser beam in a respective incident direction. The light modulator is configured to receive the native laser beams from the plurality of laser sources in different incident directions and combine the native laser beams into a combined laser beam in a diffraction direction.
Embodiments of the disclosure provide an apparatus for adjusting a light beam that includes a microelectromechanical system (MEMS), a non-MEMS system. The MEMS may include: an array of first rotatable mirrors to receive and reflect the light beam and an array of first actuators configured to rotate each rotatable mirror of the array of first rotatable mirrors. The non-MEMS system may include a second adjustable mirror to receive and reflect the light beam and a second actuator configured to adjust the second adjustable mirror. The light beam received by the array of first rotatable mirrors is the light beam reflected by the second adjustable mirror or the light beam received by the second adjustable mirror is reflected by the array of first rotatable mirror.
Some embodiments include a MEMS apparatus configured to redirect light in a LiDAR system and includes a support frame and a plurality of mirror elements disposed in a linear array within the support frame including a first mirror element and a second mirror element. Each of the plurality of mirror elements can be rotatable on a rotational axis that is perpendicular to a line defined by the linear array of the plurality of mirror elements and bisects the corresponding mirror element into a first portion and a second portion. The apparatus can include a coupling element having a distal end physically coupled to a first portion of the first mirror element and a proximal end physically coupled to a second portion of the second mirror element such that a rotation of the first mirror element causes a synchronous and equal rotation of the second mirror element.
A lever is used to rotate a microelectromechanical systems (MEMS) mirror. The lever can be used to provide more torque from a vertical comb drive. The MEMS mirror can be part of an array of micro mirrors used for beam steering a laser in a Light Detection and Ranging (LiDAR) system for an autonomous vehicle.
Systems and methods for operating an array of micro-mirror assemblies are provided. In one example, an apparatus comprises: a light source; a receiver; and a semiconductor integrated circuit comprising a microelectromechanical system (MEMS) and a controller, the MEMS comprising an array of micro-mirror assemblies, each micro-mirror assembly comprising: a micro-mirror connected to a substrate of the semiconductor integrated circuit via an elastic connection structure and rotatable around the connection structure to perform at least one of: reflect light from the light source along an output projection path, or reflect input light propagating along an input path to the receiver. The controller is configured to generate a control signal to rotate the micro-mirrors based on a target rotation angle and a spring stiffness of one or more connection structures of the array of micro-mirror assemblies.
Xtt t ,Zaa ,Y,Y] from a pool of historical users and historical activities to obtain a trained BTS model; obtaining an activity rendering request from a computing device associated with a current user; obtaining the user response prediction for each of a pool of current candidate activities based on the trained BTS model, current user feature data of the current user, and current activity feature data of the candidate activities to determine a predicted activity from the candidate activities; and causing the computing device to render the predicted activity.
Methods and systems for improving security of a vehicle are disclosed. In one embodiment, a method comprises receiving, from a requester, a request to access a vehicle compartment of a vehicle; determining a scope of access of the vehicle compartment for the requester based on an operation of the vehicle; and configuring a lock mechanism of the vehicle compartment based on the scope of access.
B60R 25/01 - VÉHICULES, ÉQUIPEMENTS OU PARTIES DE VÉHICULES, NON PRÉVUS AILLEURS Équipements ou systèmes pour interdire ou signaler l’usage non autorisé ou le vol de véhicules agissant sur des systèmes ou des équipements de véhicules, p.ex. sur les portes, les sièges ou les pare-brises
B60R 25/34 - Détection relative au vol ou autres événements relatifs aux systèmes antivol de l’état des composants du véhicule, p.ex. des fenêtres, des serrures des portes ou des appareils de sélection de changement de vitesse
E05B 77/22 - Fonctions relatives à l’actionnement des serrures depuis l'habitacle du véhicule
Disclosed are techniques for mutual authentication between a passenger that has requested a transportation service and a dispatched vehicle for providing the requested transportation service. A user device associated with the passenger verifies the dispatched vehicle using a vehicle access token generated by a transportation service platform and sends a secret key to the dispatched vehicle. The dispatched vehicle uses the secret key to recover passenger biometric information from a passenger secret received from the user device through the transportation service platform, captures passenger biometric information on-site, and compares the recovered passenger biometric information and the passenger biometric information collected on-site to verify the passenger.
B60R 25/01 - VÉHICULES, ÉQUIPEMENTS OU PARTIES DE VÉHICULES, NON PRÉVUS AILLEURS Équipements ou systèmes pour interdire ou signaler l’usage non autorisé ou le vol de véhicules agissant sur des systèmes ou des équipements de véhicules, p.ex. sur les portes, les sièges ou les pare-brises
H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
One aspect of the invention relates to a method for securing a vehicle compartment, comprising: setting a mode of operation of an access element based on authorization data, wherein a first mode of operation that allows the access element to control the locking mechanism; and a second mode of operation that prevents the access element from controlling the locking mechanism; in response to the authorization data corresponding to the second mode of operation and sensor data indicating that the vehicle compartment is opened, initiating a security protocol. Another aspect of the invention relates to a security system for a vehicle comprising an access control module configured to receive security data corresponding to a security privilege for a user and trigger an alarm in response to the security data indicating that the user does not have a security privilege and detected movement of an electronic control unit.
B60R 25/01 - VÉHICULES, ÉQUIPEMENTS OU PARTIES DE VÉHICULES, NON PRÉVUS AILLEURS Équipements ou systèmes pour interdire ou signaler l’usage non autorisé ou le vol de véhicules agissant sur des systèmes ou des équipements de véhicules, p.ex. sur les portes, les sièges ou les pare-brises
B60R 25/34 - Détection relative au vol ou autres événements relatifs aux systèmes antivol de l’état des composants du véhicule, p.ex. des fenêtres, des serrures des portes ou des appareils de sélection de changement de vitesse
E05B 77/22 - Fonctions relatives à l’actionnement des serrures depuis l'habitacle du véhicule
77.
SYSTEM AND METHOD FOR RIDE ORDER DISPATCHING AND VEHICLE REPOSITIONING
Systems and methods are provided for ride order dispatching and vehicle repositioning. A method for ride order dispatching and vehicle repositioning, comprises: obtaining information comprising a location of a vehicle, current orders, and a current time; inputting the obtained information to a trained model; and determining action information for the vehicle based on an output of the trained model, the action information comprising: re-positioning the vehicle or accepting a ride order. The model is configured with: receiving information of drivers and information of orders as inputs; obtaining a global state based on the information of drivers, the information of orders, and a global time; and querying a plurality of driver-order pairs and driver-reposition pairs based at least on the obtained global state to determine the action information as the output.
Systems and methods are provided for ride order dispatching and vehicle repositioning. A method for ride order dispatching and vehicle repositioning, comprises: obtaining information comprising a location of a vehicle, current orders, and a current time; inputting the obtained information to a trained model; and determining action information for the vehicle based on an output of the trained model, the action information comprising: re-positioning the vehicle or accepting a ride order. The model is configured with: receiving information of drivers and information of orders as inputs; obtaining a global state based on the information of drivers, the information of orders, and a global time; and querying a plurality of driver-order pairs and driver-reposition pairs based at least on the obtained global state to determine the action information as the output.
A data risk value for data of an endpoint may be determined. An endpoint risk value for the endpoint may be determined. A channel risk value for a set of channels through which the data is conveyable by the endpoint may be determined. A data security risk value may be determined based on the data risk value, the endpoint risk value, and the channel risk value.
G06F 12/14 - Protection contre l'utilisation non autorisée de mémoire
G06F 21/53 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p.ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p.ex. "boîte à sable" ou machine virtuelle sécurisée
G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
H04L 12/24 - Dispositions pour la maintenance ou la gestion
H04L 12/26 - Dispositions de surveillance; Dispositions de test
Event information of a computing device is obtained. The event information characterizes events occurring at the computing device. Two or more of the events are grouped into an event group. The event group defines an activity. The event group is classified to classify the activity. The activity and one or more related activities are chained into a sequence. The sequence defines a behavior. Context is added to the sequence to determine a contextual behavior. A security threat is detected based on the contextual behavior.
Embodiments of the disclosure provide an apparatus for emitting laser light and a system and method for detecting laser light returned from an object. The system includes a transmitter and a receiver. The transmitter includes one or more laser sources, at least one of the laser sources configured to provide a respective native laser beam having a wavelength above 1,100 nm. The transmitter also includes a wavelength converter configured to receive the native laser beams provided by the laser sources and convert the native laser beams into a converted laser beam having a wavelength below 1,100 nm. The transmitter further includes a scanner configured to emit the converted laser beam to the object in a first direction. The receiver is configured to detect a returned laser beam having a wavelength below 1,100 nm and returned from the object in a second direction.
G01S 7/481 - Caractéristiques de structure, p.ex. agencements d'éléments optiques
G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie
G02F 1/00 - Dispositifs ou dispositions pour la commande de l'intensité, de la couleur, de la phase, de la polarisation ou de la direction de la lumière arrivant d'une source lumineuse indépendante, p.ex. commutation, ouverture de porte ou modulation; Optique non linéaire
A computer-implemented method for domain analysis comprises: obtaining, by a computing device, a domain; and inputting, by the computing device, the obtained domain to a trained detection model to determine if the obtained domain was generated by one or more domain generation algorithms. The detection model comprises a neural network model, a n-gram-based machine learning model, and an ensemble layer. Inputting the obtained domain to the detection model comprises inputting the obtained domain to each of the neural network model and the n-gram-based machine learning model. The neural network model and the n-gram-based machine learning model both output to the ensemble layer. The ensemble layer outputs a probability that the obtained domain was generated by the domain generation algorithms.
G06F 21/50 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation
G06N 20/20 - Techniques d’ensemble en apprentissage automatique
A method for point-to-point traffic prediction comprises: obtaining, from a plurality of computing devices, time-series locations of a plurality of vehicles respectively associated with the computing devices, wherein: the time-series locations form first trajectory data comprising corresponding trajectories at least passing from a first point O to a second point D within a first time interval; obtaining a traffic volume between O and D for a second time interval that is temporally after the first time interval; training one or more weights of a neural network model by inputting the first trajectory data and the traffic volume to the neural network model and using the obtained traffic volume as ground truth to obtain a trained neural network model; and inputting second trajectory data between O and D to the trained neural network model to predict a future traffic volume between O and D for the a future time interval.
Embodiments of the disclosure provide systems and methods for ballistically estimating vehicle data. The system may include a communication interface configured to receive a first vehicle measurement taken at a first time point and a second vehicle measurement taken at a second time point. The system may further include at least one processor. The at least one processor may be configured to compute a first set of vehicle data based on the first vehicle measurement, and estimate a second set of vehicle data for the second time point based on the first set of vehicle data and a model. The at least one processor may be further configured to compute a third set of vehicle data based on the second vehicle measurement. The at least one processor may also be configured to update the model based on a comparison between the second set of vehicle data and the third set of vehicle data. The system may also include a storage configured to store the first and second vehicle measurements, the model, and the first, second, and third sets of vehicle data.
B60W 40/10 - 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 au mouvement du véhicule
Systems and methods are provided for smart-landmark-based positioning. Such methods may include detecting, using a sensor mounted on a vehicle, a landmark object, obtaining landmark information of the detected landmark object, the landmark information including identification of the landmark object and an encrypted location of the landmark object, transmitting, from the vehicle over a wireless network, a query including at least part of the obtained landmark information, receiving, by the vehicle over the wireless network, a query response including additional information of the landmark.
G01C 21/26 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
G08G 1/123 - Systèmes de commande du trafic pour véhicules routiers indiquant la position de véhicules, p.ex. de véhicules à horaire déterminé
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
H04W 4/02 - Services utilisant des informations de localisation
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p.ex. véhicule à nuage ou véhicule à domicile
Systems and methods are provided for data security grading. An exemplary method for data security grading, implementable by a computer, may comprise receiving a request to access a query data field, searching for the query data field from a security level table, in response to finding the query data field from the security level table, obtaining from the security level table a security level corresponding to the query data field, and in response to not finding the query data field from the security level table, determining a security level corresponding to the query data field based at least on a lineage tree and the security level table. The lineage tree may trace the query data field to one or more source data fields, and the security data level table may comprise one or more security levels corresponding to the one or more source data fields.
File classification information for a set of files are obtained. The file classification information defines (1) a number of classified files within the set of files, (2) a number of classification categories associated with the classified files, (3) a number of unauthorized classified files that do not match an access privilege of a user, and (4) a number of unauthorized classification categories associated with the unauthorized classified files. A violation of an access control policy is determined based on the file classification information.
G06F 17/30 - Recherche documentaire; Structures de bases de données à cet effet
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
H04L 9/14 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité utilisant plusieurs clés ou algorithmes
H04L 9/18 - Chiffrement par modification sérielle et continue du flux d'éléments de données, p.ex. systèmes de codage en continu
H04L 15/06 - Appareils ou circuits à l'extrémité d'émission avec un nombre limité de clés, p.ex. clé séparée pour chaque type d'élément de code
Multiple search patterns may be obtained. Characters within the multiple search patterns may be included within multiple alphabets. A pool including the characters within the multiple search patterns may be defined. A pointer for text to be searched may be set. Whether a character of the text corresponding to the pointer matches any character within the pool may be determined. Based on the character of the text corresponding to the pointer matching any character within the pool, a first portion of the text may be selected for a search of the multiple search patterns. Based on the character of the text corresponding to the pointer not matching any character within the pool, a second portion of the text may be skipped from the search of the multiple search patterns.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
A string of characters within a file may be obtained. A first sequence may be selected from the string of characters. A first hash may be generated based on the first sequence. A second sequence may be selected from the string of characters based on the first sequence. The second sequence may be shifted from the first sequence. A second hash may be generated based on the second sequence. A fingerprint for the file may be generated based on the first hash and the second hash.
Embodiments of the disclosure provide an apparatus, system, and method for detecting light returned from an object. The apparatus includes a plurality of lenses. Each lens is configured to collect light from a respective direction. The apparatus also includes a plurality of receivers. At least one of the plurality of receivers corresponds to one of the plurality of lenses and is configured to convert the light collected by the corresponding lens into an electrical signal. The apparatus further includes a multiplexer operatively coupled to the plurality of receivers and configured to select at least one of the plurality of receivers to output the corresponding electrical signal. The selected at least one receiver corresponds to the lens collecting the light returned from the object.
A method may comprise recursively performing: (1) providing one or more states of a simulation environment to a simulated vehicle, and the states comprise a first current time and a first current location of the simulated vehicle; (2) obtaining an action by the simulated vehicle when the simulated vehicle has reached a milestone, wherein: the action is selected from: waiting at the first current location of the simulated vehicle, picking up a passenger group A at an origin of passenger group A's transportation, and dropping off a passenger group B at a destination of passenger group B's transportation, and the milestone is an origin or a destination of any passenger group's transportation; (3) determining a reward to the simulated vehicle for the action; and (4) updating the one or more states based on the action to obtain one or more updated states for providing to the simulated vehicle.
B60K 35/00 - Agencement ou adaptations des instruments
G01C 21/26 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier
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
92.
METHOD AND DEVICE FOR PROVIDING VEHICLE NAVIGATION SIMULATION ENVIRONMENT
A method for providing vehicle navigation simulation environment may comprise recursively performing steps (1)-(4) for a time period: (1) providing one or more states of a simulation environment to a simulated agent, wherein: the simulated agent comprises a simulated vehicle, and the states comprise a first current time and a first current location of the simulated vehicle; (2) obtaining an action by the simulated vehicle when the simulated vehicle has no passenger, wherein the action is selected from: waiting at the first current location of the simulated vehicle, and transporting M passenger groups; (3) determining a reward to the simulated vehicle for the action; and (4) updating the one or more states based on the action to obtain one or more updated states for providing to the simulated vehicle, wherein: the updated states comprise a second current time and a second current location of the simulated vehicle.
A method for operating a ride-share-enabled vehicle includes determining a target location of the ride-share-enabled vehicle, determining a ride-sharing policy algorithm to determine a behavior of the ride-share-enabled vehicle including whether to accept a multiple shared ride or maintain a single shared ride and a route of the multiple shared ride, if any, based on the determined target location of the ride-share-enabled vehicle, determining a behavior of the ride-share-enabled vehicle based on a current location of the ride-share-enabled vehicle and the determined ride-sharing policy algorithm, and causing the ride-share-enabled vehicle to be operated according to the determined behavior of the ride-share-enabled vehicle.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
H04W 4/02 - Services utilisant des informations de localisation
G08G 1/0968 - Systèmes impliquant la transmission d'indications de navigation au véhicule
Incentive distribution may be determined by obtaining feature information for entities. The feature information may characterize features of individual entities. Predicted returns from providing individual incentives associated with different costs to the individual entities may be determined based on the feature information. Return metric from providing the individual incentives to the individual entities may be determined based on the predicted returns and the costs of the individual incentives. A set of incentives to be provided to one or more of the entities may be identified based on the return metric.
Systems and methods are provided for kernel routine callbacks. Such methods may include hooking a pre-callback handler and a post-callback handler to a pre-existing operating system of a computing device. According to the pre-callback handler, a kernel routine request for a kernel routine to be performed in a kernel mode of the operating system is obtained, whether to allow the kernel routine to be performed is determined, and the kernel routine is caused to be performed in the kernel mode to generate kernel routine results. According to the post-callback handler, whether to allow the kernel routine results of the kernel routine to be returned is determined, and the kernel routine results of the kernel routine is caused to be returned to an application that is executed in a non-kernel mode of the operating system.
Systems and methods are provided for near real-time IP user mapping. Such methods may include obtaining IP address assignment data points from different sources including an authentication, authorization, and accounting (AAA) server of a private network, a service provider that provides a computer-based service within the private network, and user devices that have access to the private network. The methods may also include applying an IP mapping rule to the obtained IP address assignment data points to generate IP address mapping.
Malicious processes may be tracked by obtaining process history information of a computing device and obtaining an identification of a malicious software on the computing device. An associated process of the malicious software and actions of the associated process may be identified based on the process history information. Related processes of the associated process and actions of the related processes may be iteratively identified based on the process history information. Tracking information for the malicious software may be generated based on the associated process, the actions of the associated process, the related processes, and the actions of the related processes.
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
G06F 21/52 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p.ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données
G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus
Malicious programs may be detected by obtaining program information of a program. A control flow graph may be generated based on the program information. The program may be identified as being potentially malicious based on one or more portions of the control flow graph.
G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
Process states of computing devices may be obtained and processed. Process event information of a computing device may be obtained. The process event information may characterize states of processes of the computing device. The process event information may be stored within a queue. Graph information may be determined based on the process event information within the queue. The graph information may characterize states of processes of the computing device using nodes and edges. The graph information may be stored within a graph database.
G06F 11/32 - Surveillance du fonctionnement avec indication visuelle du fonctionnement de la machine
G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p.ex. des interruptions ou des opérations d'entrée–sortie
G06F 21/34 - Authentification de l’utilisateur impliquant l’utilisation de dispositifs externes supplémentaires, p.ex. clés électroniques ou cartes à puce intelligentes
Process states of computing devices may be obtained and processed. Process event information of a computing device may be obtained. The process event information may characterize states of processes of the computing device. The process event information may be stored within a queue. Graph information may be determined based on the process event information within the queue. The graph information may characterize states of processes of the computing device using nodes and edges. The graph information may be stored within a graph database.
G06F 21/50 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation
G06F 11/32 - Surveillance du fonctionnement avec indication visuelle du fonctionnement de la machine
brevets