Lyft, Inc.

John Robert Tighe

Robert Earl Rasmusson, Jr

Frank Taehyun Yoo

Taggart Matthiesen

Linda L Dong

Jisi Guo

Craig Dehner

Karina Van Schaardenburg

Eli Guerron

Matt Vitelli

Oleg Vadim Panichev

Adam Alexander Wolf

Jonathan Patrick O'Keefe

Gavin Sebastian Hurley

Leighton Kamaile Jen

Jody Metzenbaum Kelman

Arkesh Jagdish Patel

Rex See Chun Lam

Alexis Weill

Jessica Yunan Chen

The disclosed computer-implemented method may include identifying and notifying requestors that may be candidates for a particular autonomous vehicle in order to find those candidates that may be willing or able to relax their travel constraints to match the autonomous vehicle. A request flow may involve surfacing the potential option of matching to an autonomous vehicle before setting a specific destination. For example, the request flow may involve determining that an autonomous vehicle is sufficiently near an in-session potential requestor. Before the potential requestor enters a specific destination, the request flow may present the possibility of the potential requestor being matched with the autonomous vehicle. In some examples, the request flow may then provide available drop-off locations that are compatible with the autonomous vehicle for selection by the potential requestor. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for matching transportation requestor devices with autonomous vehicles

In one embodiment, a method includes determining a plurality of available locations for a vehicle to pick up or drop off a user in an area based on sensor data that is captured by the vehicle and is associated with physical characteristics of the area. The method includes calculating a viability value for each of the plurality of available locations. The viability value is calculated based on the physical characteristics of the area as determined from the sensor data. The method includes ranking the plurality of available locations according to the viability values of the plurality of available locations. An available location with a higher viability value is ranked above an available location with a lower viability value. The method includes sending instructions to present, on a computing device, one or more selectable locations of the plurality of available locations based on the ranking.

Evaluating and presenting pick-up and drop-off locations in a situational awareness view of an autonomous vehicle

In one embodiment, a method includes receiving sensor data associated with an object external to a vehicle. The sensor data includes a sequence of data packets. Each data packet corresponds to a time frame in a sequence of time frames. The method includes determining a classification of the object based at least on the sensor data, determining that a particular data packet corresponding to a particular time frame in the sequence of time frames is corrupt or missing, generating a replacement data packet based on one or more data packets that correspond to one or more time frames adjacent to the particular time frame, generating a sequence of visual representations of the object corresponding to the sequence of time frames. At least one visual representation in the sequence of visual representations corresponding to the particular time frame is generated based on the replacement data packet.

Identifying objects for display in a situational-awareness view of an autonomous-vehicle environment

In one embodiment, a method includes receiving sensor data from a sensor array of a vehicle while traveling on a road. The method includes determining a confidence score for a classification of an object based on the sensor data. The method includes generating an object graphic corresponding to the object based on the confidence score for the classification of the object. The method includes retrieving, from one or more third-party systems, third-party data associated with an environment in proximity to the object and associated with the road based on the classification. The method includes generating an overlay graphic corresponding to the environment in proximity to the object based on the third-party data. The method includes providing for display the object graphic rendered in association with the overlay graphic corresponding to the environment.

Rendering a situational-awareness view in an autonomous-vehicle environment

In one embodiment, a method includes sending a set of instructions to present, on a computing device, one or more available locations for a vehicle to pick-up or drop-off a user in an area. The one or more available locations are based on sensor data of the area that is captured by the vehicle. The method includes receiving a user selection to select a location associated with the area for the vehicle to pick-up or drop-off the user. The method includes adjusting a viability value of one or more locations to pick-up or drop-off the user. The viability value is adjusted based at least on the selected location. The method includes, based on the adjusted viability value of the one or more locations, determining a location from the one or more locations. The method includes instructing the vehicle to travel to the determined location.

In one embodiment, a method includes receiving sensor data corresponding to an environment external of a vehicle. The sensor data include data points. The method includes determining one or more subsets of the data points. The method includes comparing the one or more subsets of the data points to one or more predetermined data patterns. Each of the one or more predetermined data patterns corresponds to an object classification. The method includes computing a confidence score for each subset of data points of the one or more subsets of the data points as corresponding to each of the one or more predetermined data patterns based on the comparison. The method includes generating a classification for an object in the environment external of the vehicle based on the confidence score.

The disclosed computer-implemented method may determine one or more characteristics of an autonomous vehicle, determine one or more characteristics of one or more road segments of a geographic area, determine at least one geographic zone for the autonomous vehicle within the geographic area based at least on the characteristics of the autonomous vehicle and the characteristics of the one or more road segments of the at least one geographic area, and match a request with the autonomous vehicle within the at least one geographic zone based at least in part on a request location and a destination location of the request being associated with the at least one geographic zone. Other methods, systems, and computer-readable media are disclosed.

Systems and methods for matching autonomous transportation provider vehicles and transportation requests in transportation management systems

In one embodiment, a method includes receiving autonomous-vehicle sensor data from a sensor array of an autonomous vehicle. The autonomous-vehicle sensor data indicates an object in an external environment of the autonomous vehicle. The method also includes accessing secondary data associated with the object from one or more secondary-data sources that are independent of the sensor array of the autonomous vehicle. The method also includes determining, based on the autonomous-vehicle sensor data and the secondary data, an object graphic to visually represent the object. The method also includes providing for display a visual representation of the external environment of the autonomous vehicle that includes the determined object graphic to visually represent the object.

In one embodiment, a method includes receiving autonomous-vehicle sensor data from a sensor array of an autonomous vehicle. The autonomous-vehicle sensor data indicates an object in an external environment of the autonomous vehicle. The method further includes determining a confidence score for a classification of the object. The method further includes determining an object graphic with a level of detail to visually represent the object. The level of detail of the object graphic is based on the confidence score. The method further includes providing for display a visual representation the object graphic.

In one embodiment, a method includes identifying, based on map data, an area for pick-up or drop-off of a user by an autonomous vehicle. The method also includes determining, based on autonomous-vehicle sensor data that represents an external environment of the autonomous vehicle, one or more potential pick-up or drop-off locations within the area. The method also includes calculating, based at least in part on the autonomous-vehicle sensor data and historical data a viability score for each of the potential pick-up or drop-off locations. The historical data includes past pick-up or drop-off locations for one or more past users. The method also includes providing for display a visual representation of at least a portion of the area for pick-up or drop-off that indicates at least one of the one or more potential pick-up or drop-off locations.

Growing community of inventors

San Francisco, CA, United States of America

John Robert Tighe