Other

Toyota Jidosha Kabushiki Kaisha

Toyota Motor Engineering & Manufacturing North America, Inc.

Gaurav Bansal

John P Kenney

Hongsheng Lu

Takayuki Shimizu

Toru Nakanishi

Vutha Va

Sergei S Avedisov

Ahmed Hamdi Sakr

Onur Altintas

Yoshiharu Doi

Roger D Melen

Rui Guo

Vladimeros Vladimerou

Miles J Johnson

Bin Cheng

Ryan Matthew Yee

Ellick Ming Huen Chan

Carmine Senatore

Embodiments for improving driving commands for vehicular end-to-end driving include a method for a connected vehicle that includes receiving command data describing one or more driving commands for the connected vehicle. The method includes correcting the one or more driving commands to generate modified command data that describes one or more modified driving commands. The one or more modified driving commands control an operation of the connected vehicle to satisfy a trajectory safety requirement. The method includes modifying an operation of a vehicle control system of the connected vehicle based on the modified command data so that the connected vehicle operates based on the one or more modified driving commands.

Feedback system for vehicular end-to-end driving

The disclosure includes implementations for providing a recommendation to a driver of a second DSRC-equipped vehicle. The recommendation may describe an estimate of how long it would take the second DSRC-equipped vehicle to receive a roadside service from a drive-through business. A method according to some implementations may include receiving, by the second DSRC-equipped vehicle, a Dedicated Short Range Communication message ('DSRC message') that includes path history data. The path history data may describe a path of a first DSRC-equipped vehicle over a plurality of different times while the first DSRC-equipped vehicle is located in a queue of the drive-through business. The method may include determining delay time data for the second DSRC-equipped vehicle based on the path history data for the first DSRC-equipped vehicle. The delay time data may describe the estimate. The method may include providing the recommendation to the driver. The recommendation may include the estimate.

Roadside service estimates based on wireless vehicle data

The disclosure includes embodiments for a sensor system for multiple perspective sensor data sets. In some embodiments, a method executed by an ego vehicle includes receiving, from a set of remote vehicles, a set of sensor data describing a set of preliminary heatmaps for a roadway environment. The method includes reconciling discrepancies in the set of heatmaps and a preliminary heatmap of the ego vehicle to form a combined heatmap that describes the objects in the roadway environment as collectively observed by the onboard sensors of the set of remote vehicles and the ego vehicle. The method includes providing the combined heatmap to one or more of the remote vehicles included in the set of remote vehicles. The method includes modifying an operation of the ego vehicle based on the combined heatmap. For example, an operation of an autonomous driving system of the ego vehicle is modified.

Sensor system for multiple perspective sensor data sets

The disclosure describes embodiments for vehicle-to-everything (V2X) data transfer for automated vehicles. In some embodiments, a method includes providing or attempting to provide, by a communication unit of an ego vehicle, digital data to a communication device based on a mode of the communication unit, where the digital data is relayed by the communication device to be received by a server. The method includes determining, by a processor of the ego vehicle, feedback that describes a bandwidth constraint of the communication unit. The method includes modifying, by the processor, the mode based on the feedback so that the mode is consistent with the bandwidth constraint and the digital data is successfully received by the server.

Vehicle-to-everything data transfer for automated vehicles

The disclosure includes embodiments for modifying the acceleration of an ego vehicle based on wireless vehicle data included in a wireless message. A method includes receiving the wireless message that includes wireless vehicle data that describes one or more physical properties of a downstream vehicle. The wireless vehicle data indicates a presence of a traffic obstruction. The method includes determining a modification for an acceleration of the ego vehicle based on the wireless vehicle data and the indication of the traffic obstruction. The method includes modifying the acceleration of the ego vehicle based on wireless vehicle data compliant with the DSRC standard. The modified acceleration causes the ego vehicle to travel at a velocity consistent with a preceding vehicle and the downstream vehicle so that the ego vehicle does not collide with the preceding vehicle or the other downstream vehicle, which are in the same lane as the ego vehicle.

Vehicular mitigation system based on wireless vehicle data

The disclosure describes a method for an ego vehicle. The method includes receiving a vehicle-to-everything (V2X) message that describes an object that is within proximity of an ego vehicle. The method further includes generating a set of data-to-camera (D2C) filters that are specific to the object described by the V2X message. The method further includes applying the set of D2C filters to image data that describes an initial image of the object. The method further includes generating a modified image, based on applying the set of D2C filters to the image data, wherein the modified image includes an indication of (1) a location and a size of the object in the initial image and (2) a type of object in the initial image.

Data-to-camera (D2C) based filters for improved object detection in images based on vehicle-to-everything communication

The disclosure includes embodiments for providing augmented graphical data on a user device. In some embodiments, a method includes receiving, by the user device, a Vehicle-to-Everything (V2X) wireless message transmitted by a ride share vehicle and including V2X data describing the ride share vehicle. The method includes generating augmented graphical data based on the V2X data, where the augmented graphical data describes an augmented version of an image captured by the user device and depicting a real-life environment that includes the ride share vehicle, where the augmented version highlights a position of the ride share vehicle within the real-life environment. The method includes presenting the augmented graphical data on the user device so that the ride share vehicle is more easily located in the real-life environment.

AR/VR/MR ride sharing assistant

The disclosure includes embodiments for performing beam alignment for non-line of sight (NLOS) scenarios. The method includes receiving, at a first vehicle, one or more wireless messages that include vehicle data, wherein the vehicle data describes a second vehicle position, a second vehicle speed, and a second vehicle heading. The method also includes determining sensor data. The method also includes determining an NLOS path based on the vehicle data and the sensor data so that the NLOS path avoids a potential blockage. The method also includes determining whether the NLOS path is predicted to succeed based on a beam transmission percentage satisfying a threshold percentage. The method also includes responsive to the NLOS path being predicted to succeed, performing beam alignment between the first vehicle and the second vehicle based on the NLOS path before the potential blockage is predicted to occur.

Vehicular millimeter wave communication for non-line of sight scenarios

The disclosure includes embodiments for generating a real-time high-definition (HD) map for an ego vehicle using wireless vehicle data of a remote vehicle. In some embodiments, a method includes receiving a V2X wireless message which includes remote GPS data and remote road parameter data of the remote vehicle. The method includes retrieving ego GPS data of the ego vehicle. The method includes generating ego road parameter data describing an initial estimate of a geometry of a road on which the ego vehicle is located. The method includes fusing the ego road parameter data and the remote road parameter data to form fused road parameter data which describes an improved estimate of the geometry of the road that is more accurate than the initial estimate. The method includes generating a real-time HD map based on the remote GPS data, the ego GPS data, and the fused road parameter data.

Generating real-time high-definition (HD) maps using wireless vehicle data of a remote vehicle

The disclosure includes implementations for determining a position of a vehicle using millimeter wave narrow beamforming. A method may include receiving a set of training packets that each uniquely identify a position on a portion of a roadway where the vehicle is located. Each of the training packets included in the set may be associated with only one of the millimeter wave narrow beams. The method may include identifying a training packet included in the set of training packets that has a highest receive power level among the set of training packets. The method may include determining the position uniquely identified by the training packet having the highest receive power level. The method may include determining positional information for the vehicle based on the position uniquely identified by the training packet having the highest receive power level. The positional information may describe a location of the vehicle on the roadway.

Precise positioning using millimeter wave narrow beamforming

System, methods, and other embodiments described herein relate to detecting a lane change of a target vehicle ahead of an ego vehicle. In one approach, a method includes receiving communications from a target vehicle specifying state information about the target vehicle. The method includes determining a location of a first decision point at a first distance ahead of an ego vehicle and acquiring sensor data about the target vehicle. The method includes determining motion information about the target vehicle based on the sensor data. The motion information includes positions that the target vehicle occupied relative to the ego vehicle. The method includes storing the state information and motion information for a first amount of time, and determining whether the target vehicle has changed lanes based on the state information and the motion information that has been stored once the ego vehicle has reached the first decision position.

System and method for determining a lane change of a preceding vehicle

The disclosure includes embodiments for theft deterrent for a connected vehicle using Basic Safety Message (BSM)-based Vehicle-to-Anything (V2X) communication. In some embodiments, a method includes receiving, by a V2X radio, a wireless message that is transmitted by a first connected vehicle whose ignition is disengaged. In some embodiments, the method includes determining, based on a payload of the wireless message, that the first connected vehicle is being subjected to criminal activity. In some embodiments, the method includes taking a remedial action responsive to determining that the first connected vehicle is being subjected to criminal activity. In some embodiments, the remedial action is operable to deter the occurrence of the criminal activity (i.e., stop the first connected vehicle from being stolen) or gather visual evidence of the criminal activity.

Theft deterrent system for connected vehicles based on wireless messages

The disclosure describes a method for an ego vehicle. The method includes providing roaming data to a server, the roaming data describing a roaming pattern of the ego vehicle in a geographic area as a function of time. The method further includes providing a request to the server that describes a need for the ego vehicle to park. The method further includes receiving, from the server, a geographic location of an available parking spot and an estimated length of time the available parking spot will remain available.

Vehicle parking spot availability prediction based on vehicle-to-anything enabled machine learning

The disclosure includes embodiments for adaptively controlling a beamwidth setting for a millimeter wave (mmWave) communication between a first endpoint and a second endpoint. In some embodiments, a method for the first endpoint includes exchanging position data and position accuracy data with a second endpoint via a non-mmWave type channel of a vehicle-to-everything (V2X) radio. The method includes adjusting a beamwidth setting for a mmWave channel of the V2X radio based on the position data and the position accuracy data. The method includes performing a beam alignment for the mmWave channel of the V2X radio based on the beamwidth setting to modify an operation of the V2X radio so that the V2X radio exchanges a mmWave communication with the second endpoint using the beam alignment indicated by the beamwidth setting.

Adaptive beamwidth control for millimeter wave V2X communications

The disclosure includes embodiments for estimating pedestrian density data based on one or more Personal Safety Messages (PSM message). A method includes, according to some embodiments, receiving, by a first dedicated short range communication (DSRC) chip of a DSRC-enabled vehicle, a PSM message including an instance of pedestrian safety message data (PSM data) describing a geographic location of a pedestrian. The method includes executing an analysis of the instance of PSM data to determine that the pedestrian is present at a business based on the geographic location being within a known geographic area for the business. In some embodiments, this analysis is executed for a plurality of instances of PSM data. The method includes generating pedestrian density data for the business that describes how many pedestrians are present at the business based on executing the analysis for the plurality of instances of PSM data.

Growing community of inventors

Mountain View, CA, United States of America

Gaurav Bansal