Lyft, Inc.

Woven Planet North America, Inc.

Woven by Toyota, U.s., Inc.

Nio USA, Inc.

Farzad Cyrus Foroughi Abari

Romain Clément

Alexander Thomas Starns

Helen Ruth Lurie

Adam Hart Reis

Aaron Jacob Levine Friedman

John S Houston

Forrest Samuel Briggs

Corey Frederick Bangs

Nathan Rolander

Roxie Lynn Paine

Veera Ganesh Yalla

Xu Chen

Tong Lin

John Christopher Houston

Hiu Hong Yu

Mayur Nitinbhai Shah

John Rogers Houston

Andre Michelin

In particular embodiments, a computing system may determine a predicted amount of ride requests for a plurality of collectively-managed vehicles and determine an availability of the collectively-managed vehicles to satisfy the predicted amount of ride requests. Subsequent to determining that the availability fails to satisfy one or more predetermined criteria for servicing the predicted amount of ride requests, the system may determine status information associated with the collectively-managed vehicles and determine, based on at least the status information, one or more minimum services for servicing one or more vehicles among the plurality of collectively-managed vehicles at one or more service centers such that the availability satisfies the one or more predetermined criteria. The system may instruct the one or more vehicles that are to receive the one or more minimum services to travel to the one or more service centers to be serviced.

Fleet maintenance management for autonomous vehicles

In one embodiment, a method includes determining a fleet-level objective for a vehicle associated with instructing the vehicle to travel a route according to route criteria based on the fleet-level objective. The method includes receiving a ride request from a ride requestor associated with ride criteria including a pick-up location and a drop-off location. The method includes determining that the ride requestor is a passenger for the vehicle to satisfy the fleet-level objective contingent on modifications to the ride criteria. The method includes providing incentives to the ride requestor contingent on acceptance of the modifications to the ride criteria. The method includes, after receiving the acceptance of the modifications to the ride criteria, modifying the ride criteria in accordance with the route criteria. The method includes instructing the vehicle to transport the ride requestor based on the modified ride criteria so as to fulfill the fleet-level objective.

Autonomous-vehicle dispatch based on fleet-level target objectives

In one embodiment, an apparatus includes a first stage and a second stage. The first stage may include a micro light-directing unit that is operable to receive a light beam from a light source and direct the light beam along one dimension to discrete input locations of a second stage. The second stage may be operable to receive the light beam from the first stage at the discrete input locations along the one dimension and direct the light beam through two dimensions to discrete output locations of the second stage to scan a three-dimensional space.

Apparatus and method for a beam-directing system using a gated light valve

In one embodiment, a method includes providing instructions to broadcast a modulated radar chirp signal from a radar antenna of a vehicle. The modulated radar chirp signal includes data associated with the vehicle. The method includes receiving a first return signal whose waveform substantially matches the modulated chirp signal. The first return signal is the modulated radar chirp signal after reflecting off of an object in an environment surrounding the vehicle. The method includes calculating a location for the object using the first return signal, receiving, from a base station antenna, a second return signal that indicates the modulated chirp signal was received by the base station antenna, and providing instructions to establish a wireless communication session with the base station antenna.

Simultaneous object detection and data transfer with a vehicle radar

In one embodiment, a computing system may transmit, using one or more light emitters, light beams of different wavelengths simultaneously into a surrounding environment. The system may determine a characteristic of the surrounding environment based on reflections of the light beams. In response to a determinization that the characteristic of the surrounding environment satisfies a criterion, the system may configure the one or more light emitters to transmit light beams of different wavelengths sequentially into the surrounding environment for measuring distances to one or more objects in the surrounding environment.

Adaptive LiDAR system

In one embodiment, a method includes receiving an image of an object captured in a geographic location. The method includes determining the geographic location associated with the image. The geographic location is represented in a map that includes one or more ambient light measurements corresponding to one or more geographic locations. The method includes using the one or more ambient light measurements corresponding to the geographic location in the map associated with the image to generate a color corrected image. The method includes determining a classification of the object using the color corrected image.

Monitoring ambient light for object detection

In one embodiment, a method includes determining an operational status of a vehicle including a radar antenna. The operational status is related to autonomous-driving operations of the vehicle in an environment. The method includes determining an expected amount of signaling resources associated with the radar antenna to be utilized by the vehicle while the vehicle performs the autonomous-driving operations, based at least on the operational status of the vehicle and the environment. The method includes determining to switch one or more of the signaling resources associated with the radar antenna from a first mode to a second mode based on the expected amount of signaling resources to be utilized by the radar antenna while the vehicle performs the autonomous-driving operations. The method includes causing the one or more of the signaling resources associated with the radar antenna to switch from the first mode to the second mode.

Switching between object detection and data transfer with a vehicle radar

Systems, methods, and other embodiments relate to determining the speed of a vehicle. In one embodiment, a method includes receiving a first frame of data generated by a first sensor of a vehicle, the first frame of data including a first set of angular positions associated with a first set of objects in the environment. The method includes receiving a second frame of data generated by a second sensor of the vehicle, the second frame of data including a second set of angular positions associated with a second set of objects in the environment. The method includes generating a speed estimate for the vehicle in relation to the first set of objects and the second set of objects based at least in part on the first set of angular positions of the first frame of data and the second set of angular positions of the second frame of data.

Systems and methods for estimating vehicle speed based on radar

In one embodiment, a facility for calibrating sensors of an autonomous vehicle (AV) includes a camera calibration target configured to be measured by and used for calibrating an optical camera of the AV; a light detection and ranging (LiDAR) calibration target configured to be measured by and used for calibrating a LiDAR transceiver of the AV; and a platform configured to allow the AV to drive onto and park on the platform. The camera calibration target and the LiDAR calibration target are positioned to be detectable by the optical camera and the LiDAR transceiver while the AV is parked on the platform. The platform is further configured to modify a lateral position, height, or orientation of the optical camera and the LiDAR transceiver relative to the camera calibration target and the LiDAR calibration target while the AV is parked on the platform.

Sensor calibration facility

In one embodiment, a method includes receiving sensor data from one or more sensors of an autonomous vehicle (AV); determining that a first sensor of the one or more sensors needs recalibration based on the sensor data. The first sensor being of a first sensor type. The method also includes sending a request to a remote management system indicating that one or more of the sensors of the AV need recalibration and a location of the AV; determining the presence of a service vehicle having a calibration target configured to calibrate sensors of the first sensor type; and initiating a calibration routine using the calibration target.

Mobile sensor calibration

In one embodiment, a method includes emitting, by an automotive vehicle, one or more light beams from a LiDAR system toward an environment surrounding the automotive vehicle, receiving one or more return light beams at the LiDAR system of the automotive vehicle, detecting one or more objects located in the environment surrounding the automotive vehicle based on the return light beams, and simultaneously measuring one or more air characteristics of the environment surrounding the automotive vehicle. The simultaneous detecting of the one or more objects and measuring of the one or more air characteristics may be performed by the LiDAR system. The method may further include sending, by the automotive vehicle, location information to a server associated with vehicle navigation, and sending information of the detected objects and measured air characteristics to the server associated with vehicle navigation, the server configured to update a vehicle-navigation map based on the information.

Tunable LiDAR for simultaneous ranging and environmental monitoring

Methods and systems include localization of a vehicle localize precisely and in near real-time. As described, localization of a vehicle using a Global Navigation Satellite System (GNSS) can comprise receiving a signal from each of a plurality of satellites of a GNSS constellation and receiving input from one or more sensors of the vehicle. The input from the sensors can indicate current physical surroundings of the vehicle. A model of the current physical surrounding of the vehicle can be generated based on the input from the one or more sensors of the vehicle. One or more multipath signals received from the plurality of satellites can be mitigated based on the model and the vehicle can be localized using the received signals from the plurality of satellites of the GNSS constellation and based on the mitigation of the one or more multipath signals.

Methods to improve location/localization accuracy in autonomous machines with GNSS, LIDAR, RADAR, camera, and visual sensors

In one embodiment, an apparatus includes a transmitter operable to transmit a first light beam from a light source. The apparatus also includes a receiver operable to receive a plurality of return light beams and direct the plurality of return light beams through a first beam splitter to an imaging sensor and a LiDAR sensor. The imaging sensor may be operable to process a first portion of the return light beams into image profile data, and the LiDAR sensor may be operable to process a second portion of the return light beams into depth profile data. In addition, the first and second portions of the return light beams may be received from a shared field of view.

Image sensor processing using a combined image and range measurement system

In one embodiment, a method includes, determining multiple data packets for transmission. The method includes generating a log that includes a sequence identifier associated with each data packet. The method includes transmitting the data packets via a first radar antenna coupled with a vehicle and associated with the computing system. The method includes receiving an acknowledgement from a second radar antenna that identifies at least one sequence identifier associated with at least one of the data packets. The method includes identifying one or more data packets that were not received by the second radar antenna by comparing the at least one sequence identifier in the acknowledgment and the sequence identifier associated with each data packet in the log. The method includes retransmitting the one or more identified data packets that were not received by the second radar antenna via the first radar antenna.

Growing community of inventors

San Bruno, CA, United States of America

Farzad Cyrus Foroughi Abari