Ford Global Technolgoies, LLC

Faraday & Future Inc.

Lsi Corporation

Avago Technologies General IP (singapore) Pte. Ltd.

Argo Ai Gmbh

Xiufeng Song

George Mathew

Eui Seok Hwang

Richard Rauschmayer

Jun Xiao

Lu Lu

Jianzhong Huang

Avinash Ajit Nargund

Shubhendra Chauhan

Fan Zhang

Haitao Xia

Luke M Ekkizogloy

Matthew Joseph Coburn

Lu Pan, Sr

Fnu Ratnesh Kumar

Nicholas William Dazé

Serge Nikulin

Sethu Hareesh Kolluru

Eric Ryan Evenchick

Yinguang Li

Minhan Li

Carlos John Rosario

Juan Pablo Samper

Disclosed herein are systems, methods, and computer program products for operating a sensor system. The methods comprise: receiving, by a computing device, a track for an object; classifying, by the computing device, the track as an infant track or a mature track based on a type of sensor detection used to generate the track, a total number of cycles in which the lidar detections were generated, a total number of sensor detections included in the track, an object type associated with the track, an object speed, and/or a distance between the object and the sensor system; using, by the computing device, radar data to modify a speed of the track in response to the track being classified as an infant track.

Systems and methods for infant track association with radar detections for velocity transfer

Systems and methods for detecting and tracking objects using radar data are disclosed. The methods include receiving measurement data corresponding to an environment of a vehicle from a radar sensor associated with the vehicle, and identifying one or more object tracks of a plurality of object tracks that lie within an extended field of view (FOV) of the radar sensor. The extended FOV may be determined based on an original FOV of the radar sensor. The methods further include performing association of the measurement data with the one or more object tracks to identify an associated object track, and outputting the associated object track and the measurement data to a navigation system of the vehicle.

Systems and methods for onboard analysis of sensor data for sensor fusion

This document discloses system, method, and computer program product embodiments for mitigating the addition of false object information to a track that provides a spatial description of an object, such as a track of radar data or lidar data. The system will analyze two or more frames captured in a relatively small time period and determine whether one or more parameters of an object detected in the frames remain consistent in a specified model. Models that the system may consider include a constant velocity model, a surface model, a constant speed rate model or a constant course rate model. If one or more parameters of the detected object are not consistent over the sequential frames in the specified model, the system may prune the track to exclude one or more of the sequential frames from the track.

False track mitigation in object detection systems

Systems may include at least one processor configured to determine a predicted value of an unwrap factor using a machine learning model, wherein the machine learning model is a trained machine learning model configured to provide a predicted value of an unwrap factor for dealiasing a measurement of range rate of a target object as an output, dealiase a measurement value of range rate from a radar of an autonomous vehicle (AV) based on the predicted value of the unwrap factor to provide a true value of range rate, and control an operation of the AV in a real-time environment based on the true value of range rate. Methods, computer program products, and autonomous vehicles are also disclosed.

Methods and systems for dealiasing radar range rate measurements using machine learning

Methods, systems, and products for resolving level ambiguity for radar systems of autonomous vehicles may include detecting a plurality of objects with a radar system. Each first detected object may be associated with an existing tracked object based on a first position thereof. First tracked object data based on a first height determined for each first detected object may be stored. The first height may be based on the position of the detected object, the existing tracked object, and a tile map. Second tracked object data based on a second height determined for each second detected object not associated with the existing tracked object(s) may be stored. The second height may be based on a position of each second detected object, a vector map, and the tile map. A command to cause the autonomous vehicle to perform at least one autonomous driving operation may be issued.

Method, system, and computer program product for resolving level ambiguity for radar systems of autonomous vehicles

Systems and methods for operating radar systems. The methods comprise, by a processor: receiving point cloud information generated by at least one radar device; generating a radar track initializer using the point cloud information; determining whether the radar track initializer includes false information; generating a radar track for a detected object when a determination is made that the radar track initializer does not include false information; and/or using the radar track to control operations of a vehicle.

Systems and methods for radar false track mitigation with camera

Systems and methods for operating radar systems. The methods comprise, by a processor: receiving point cloud information generated by at least one radar device and a spatial description for an object; generating a plurality of point cloud segments by grouping data points of the point cloud information based on the spatial description; arranging the point cloud segments in a temporal order to define a radar tentative track; performing dealiasing operations using the radar tentative track to generate tracker initialization information; and using the tracker initialization information to generate a track for the object.

Systems and methods for range-rate dealiasing using position consistency

A method and system for detecting signal spoofing are disclosed. According to certain embodiments, the spoofing detection method may include receiving one or more position signals indicative of a first position of a vehicle at a first time. The method may also include receiving one or more reference signals indicative of a second position of the vehicle at the first time. The method may also include determining a difference between the first position and the second position. The method may also include determining that the difference is above a predetermined tolerance. The method may further include notifying the vehicle positioning system.

Methods and systems for detecting signal spoofing

Systems and methods for operating radar systems. The methods comprise, by a processor: receiving point cloud information generated by radar devices; grouping data points of the point cloud to form at least one segment; computing possible true range-rate values for each data point in the at least one segment; identifying a scan window including possible true range-rate values for a largest number of data points; determining whether at least two modulus of the data points associated with the possible true range-rate values included in the identified scan window have moduli values that are different by a certain amount; determining a new range-rate value for each data point of the segment, when a determination is made that at least two modulus of the data points do have moduli values that are different by the certain amount; and modifying the point cloud information in accordance with the new range-rate value.

Systems and methods for simultaneous range-rate unwrapping and outlier removal for radar

A method for improved position estimation. The method includes: receiving first position information from a first GNSS receiver of a vehicle dashboard camera, receiving second position information from a second GNSS receiver of a mobile device carried by a user and proximate the first GNSS receiver, and, when it is determined that the vehicle dashboard camera and the mobile device share the same inertial reference frame and are within the first distance and that the accuracy of either the first position information or the second position information falls beneath the threshold and that the predicted course of either the vehicle dashboard camera and the mobile device is calculated to pass through the region of poor satellite reception, time synchronizing the second position information with the first position information, and combining the first position information with the second position information to determine third position information.

Geo-fusion between imaging device and mobile device

A system for providing media content to an occupant of a vehicle may include a user interface configured to provide the media content to the occupant and a controller coupled to the user interface and to a database configured to store media content. The controller may be configured to receive vehicle navigation data, select a subset of media content from the media content stored in the database based on the vehicle navigation data, and provide the subset of media content through the user interface.

Infotainment based on vehicle navigation data

Methods, systems, computer-readable media, and apparatuses for executing an event pertaining to a vehicle and a user of the vehicle are presented. In some embodiments, a includes (a) detecting that a motion state of the vehicle is in a first state, (b) detecting a condition that warrants a change in the motion state of the vehicle to a second state, and (c) detecting the user of the vehicle's engagement in an activity that potentially impairs the user from performing an action to change the motion state of the vehicle to the second state. The method also includes, detecting the condition, and (c) detecting the user of the vehicle's engagement in the activity, executing an event to facilitate the change in the motion state of the vehicle to the second state.

Activate/deactivate functionality in response to environmental conditions

Various techniques related to determining whether mobile devices are associated are described. The techniques can include receiving first position information from a first device and receiving second position information from a second device. The techniques can also include comparing the first position information to the second position information over an overlapping time period. The techniques can additional include determining, based on the comparing, whether first position information and the second position information indicate that the first device and the second device are collocated during the overlapping time period. The techniques can include, upon determining that the first position information and the second position information indicate that the first device and the second device are collocated during the overlapping time period, determining that the first device and the second device are associated.

Geo-pairing detection

Various embodiments are presented for providing customized and adaptive massaging in vehicle seats. A method for providing customized and adaptive massaging in vehicle seats is disclosed. The method includes the steps of receiving profile information associated with an occupant of a seat of a vehicle; receiving a current driving mode of the vehicle, selecting a massage setting for the seat based on the profile information and the current driving mode, and massaging the occupant of the seat based on the massage setting.

Systems and methods for providing customized and adaptive massaging in vehicle seats

Certain embodiments use image-based technologies (e.g., digital cameras, light detection and ranging (LIDAR) systems, etc.) to monitor a driver-side floor space in a vehicle cabin and warn the driver when a foreign object is blocking or may potentially block a vehicle control (e.g., brake pedal). A foreign object can include a bottle, can, electronic device, keys, books, or the like. In some cases, foreign objects are detected by comparing a current image of the driver-side floor space with a reference image that is known to be free of foreign objects. The difference image can be used to identify any foreign objects in the driver-side floor space, and a corrective action can be taken to address the potential danger. Some corrective actions may include an audio and/or video alert to the driver, or in some cases, the vehicle may autonomously guide the vehicle to a safe location and stop.

Growing community of inventors

San Jose, CA, United States of America

Xiufeng Song