Argo Ai Gmbh

Volkswagen Group of America Investments, LLC

Lg Innotek Co., Ltd.

Michel Laverne

Ilan Biala

Dane P Bennington

Brett Browning

Morgan M Wagner

Casey J Sennott

James Hays

Matthew Puchalski

Elizabeth Ballard

Sean Foley

Stephen Ressler

Anthony R McAlexander

A system including a first unit configured to: receive a LiDAR output signal, compare a time-delayed LiDAR output signal to the LiDAR output signal, and provide a digital output signal, and a second unit configured to generate LiDAR data including a distance and an amplitude based on the digital output signal.

System and method for differential comparator-based time-of-flight measurement with amplitude estimation

Systems, methods, and computer-readable media for receiving, by a smart infrastructure device and from a first vehicle, first information associated with the first vehicle in a first format associated with a first communication protocol. The first information is converted from the first format into an agnostic format. An image, video, or real-time feed of an environment of the smart infrastructure device is captured. The first vehicle and a second vehicle in the image, video, or real-time feed is identified. It is determined that the second vehicle is temporarily or permanently incapable of performing a communication with the smart infrastructure device based on the image, video, or real-time feed. The image, video, or real-time feed is analyzed to generate second information associated with the second vehicle. The second information is converted into the agnostic format.

Systems and methods for multi-modal transfer capabilities for smart infrastructure

A fleet management system will receive, from each vehicle of a fleet of vehicles, a vehicle identification number (VIN). The system also will receive data elements that comprise: (a) vehicle operational parameters gathered during a run of the vehicle; (b) a hardware identification code that identifies a hardware component of the vehicle; and/or (c) a software identification code that identifies an installed software component in the vehicle. The processor will generate a data block that comprises the VIN and the one or more data elements. The processor will then save the data block to a shared digital ledger that includes VINs and data elements for a plurality of the vehicles in the fleet.

Distributed method and system for vehicle identification tracking

A method of operating a vehicle having a roof-mounted sensor apparatus includes, by a retractable sensor, capturing data about an environment along a path on which the vehicle is traveling. The method includes, by a location sensor, determining a location of the vehicle along the path. By a computing device of the vehicle, the method includes accessing a map that corresponds to the location and the path, determining that a structure having a minimum clearance is ahead at an imminent location on the path, and determining that the minimum clearance is less than or equal to an elevation of the retractable sensor. The method includes prior to the vehicle arriving at the imminent location, automatically operating a lifting element of the sensor apparatus to withdraw the retractable sensor into the sensor apparatus so that the elevation of the retractable sensor is less than the minimum clearance of the structure.

System and method for operating a retractable sensor of an autonomous vehicle

Methods, systems, and products for parallax estimation for sensors for autonomous vehicles may include generating a two-dimensional grid based on a field of view of a first sensor. For each respective point in the grid, a three-dimensional position of an intersection point between a first ray from the first sensor and a second ray from a second sensor may be determined. For each respective intersection point, a respective solid angle may be determined based on a first three-dimensional vector from the first sensor and a second three-dimensional vector from the second sensor to the intersection point. A matrix may be generated based on a distance from the first sensor, a distance from the second sensor, and the solid angle for each respective intersection point. At least one metric may be extracted from the matrix. An arrangement of the first and second sensors may be adjusted based on the metric(s).

Method, system, and computer program product for parallax estimation for sensors for autonomous vehicles

A signal delay component may be configured to receive a LiDAR output signal including an analog waveform from a LiDAR system, and provide a time-delayed LiDAR output signal including a time-delayed analog waveform. A differential comparator may be configured to receive the LiDAR output signal including the analog waveform and the time-delayed LiDAR output signal including the time-delayed analog waveform, and to provide a digital output signal. A processor may be configured to generate LiDAR data including a distance associated with the LiDAR output signal and an amplitude associated with the LiDAR output signal, the distance being based on a first time associated with a rising edge of the digital output signal, and the amplitude being based on a time difference between the first time associated with the rising edge of the digital output signal and a second time associated with a falling edge of the digital output signal.

A time master and sensor data collection module for a robotic system such as an autonomous vehicle is disclosed. The module includes a processing device, one or more sensors, and programming instructions that are configured to cause the processing device to operate as a timer that generates a vehicle time, receive data from the one or more sensors contained within the housing, and synchronize the data from the one or more sensors contained within the housing with the vehicle time. The integrated sensors may include sensors such as a global positioning system (GPS) unit and/or an inertial measurement unit (IMU). The module may interface with external sensors such as a LiDAR system and/or cameras.

Time master and sensor data collection for robotic system

A method of transferring data between an autonomous vehicle and a vehicle traffic control infrastructure system. The method includes receiving, by a communication device of a vehicle, a data payload for a smart traffic control infrastructure node. The method includes, by a computing device of the vehicle: determining that the vehicle is or will be within a communication range of the smart traffic control infrastructure node, determining a length of time that the vehicle will be in the communication range of the smart traffic control infrastructure node, and assembling a communication package with at least a portion of the data payload that can be transferred in the determined length of time. The method includes, by a communication device of the vehicle when the vehicle has an ad hoc communication link with the smart traffic control infrastructure node, transmitting the assembled communication package to the smart node.

System and method for data offloading and uploading to exchange data between nodes of a vehicle traffic infrastructure system

A system provides navigational control information to a fleet of vehicles and includes a network of nodes within a geographical area. Each node is located at a different intersection in the geographical area. Each node includes a node vision range and a processor which generates augmented perception data (APD) for each moving object of interest monitored in the node vision range. The system includes a remote server system that includes a database of the APD and receives a query from a vehicle of the fleet for the APD associated with an imminent path of the vehicle. The server system, in response to the query, searches the database for APD associated with the imminent path, and communicates, over a communication network, the resultant APD associated with the imminent path to the vehicle. The APD controls navigation of the vehicle through one or more imminent intersections along the imminent path.

System for augmenting autonomous vehicle perception using smart nodes

A node is provided for capturing information about moving objects at an intersection. The node includes a plurality of first cameras that are positioned to capture first digital images of an intersection from different fields of view and a second camera positioned to capture second digital images in a field of view that is wider than that of each first camera. The node includes a processor that detects in the first and second digital images a set of objects of interest of the intersection, determines motion of each detected object of interest in the set from consecutive images of the first digital images or the second digital images. The node generates, for each object of interest of the set, augmented perception data that includes location data in the global coordinate system and the determined motion of each object of interest in the set.

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Pittsburgh, PA, United States of America

Michel Laverne