Lyft, Inc.

Salesforce Com, Inc.

Taggart Matthiesen

Robert Earl Rasmusson, Jr

Jisi Guo

Ethan Duncan Eyler

Jesse Jones McMillin

Frank Taehyun Yoo

Linda L Dong

Craig Dehner

John Robert Tighe

Karina Van Schaardenburg

Eli Guerron

Sebastian Rolf Johan Brannstrom

Matt Vitelli

Martin Conte MacDonell

Sean Patrick Murphy

Jess Garms

Sebastian Brannstrom

Mark David Teater

Sergey Shlykovich

Peter S Wisnovsky

Richard Unger

Christopher Kuh

Sang Ik Lee

Edward Stephen Lowe

Jody Metzenbaum Kelman

Nicholas Robert Barrett

Craig David Weissman

Luc Vincent

Sameer Qureshi

Fiaz Hossain

Logan Green

Sebastian Rolf Brannstrom

In one embodiment, a method includes determining, based on vehicle status information associated with a vehicle, that the vehicle is to be serviced at a service facility. The method includes identifying multiple routes between a current location of the vehicle and the service facility. Each of the multiple routes includes a multiple road segments that connect the current location to the service facility. The method includes selecting a route from the multiple routes based at least on the vehicle status information associated with the vehicle and at least one condition associated with one or more of the road segments of each of the multiple routes. The method includes instructing the vehicle to travel from the current location to the service facility along the selected route.

Dynamic autonomous vehicle servicing and management

The present disclosure is directed toward systems and methods for an augmented reality transportation system. For example, the systems and methods described herein present an augmented reality environment for a driver or a passenger including augmented reality elements to mark specific locations within a display of real-world surroundings. Additionally, the systems and methods described herein analyze historical information to determine placements for augmented reality elements. The systems and methods also enable a user to share an augmented reality or virtual reality environment with another user.

Providing information to users of a transportation system using augmented reality elements

In one embodiment, a method includes receiving, using one or more sensors of a first vehicle, sensor data associated with an environment surrounding the first vehicle. The method includes detecting, using the sensor data, a second vehicle in the environment surrounding the first vehicle. The method includes determining, based on the sensor data, a first movement context associated with the first vehicle and a second movement context associated with the second vehicle. The method includes coordinating, via a ride matching system, movements between the first vehicle and the second vehicle based on the first movement context associated with the first vehicle and the second movement context associated with the second vehicle.

Autonomous vehicle notification system

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

Embodiments provide techniques, including systems and methods, for locating and navigating to the location of a requestor based on proximity between a requestor device and a provider device. For example, embodiments display proximity indicators to allow a provider to quickly, easily, and safely locate a requestor upon arrival near a request location. Further, in some embodiments, graphics associated with a proximity vector may be presented on a provider communication device to clearly display the navigation directions to the provider so that the provider may easily find their matched requestor without requiring additional communication between the provider and the requestor. Additionally, embodiments provide efficient navigation to riders by limiting display of proximity indicators for navigation until the provider is within a threshold distance to the request location to conserve system resources and communication between an on-demand matching system and the provider computing device.

Navigation using proximity information

Embodiments provide techniques, including systems and methods, for identifying and matching requestors and providers. For example, embodiments can display an identification pattern that is unique for a matched requestor and provider to allow the providers and requestors to quickly, easily, and accurately validate one another's identities prior to a service being provided. In some embodiments, the identification element may be presented on a provider communication device to clearly display graphics associated with an identification element to all requestors in an area so that the requestors may easily identify a matched provider.

Identifying matched requestors and providers

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.

Embodiments provide systems, methods and computer-readable medium to manage rider pickup and drop-off for autonomous vehicles. In one embodiment, a method includes receiving a ride request and an associated pickup location from a requestor computing device, matching the ride request to a vehicle, and instructing the vehicle to travel towards the pickup location. When the vehicle reaches the pickup location, an unlock request is received from the requestor computing device to unlock the vehicle. In response to receiving the unlock request, a verification is made that one or more unlock criteria associated with the vehicle are satisfied. If satisfied, a door of the vehicle is unlocked.

Autonomous vehicle pickup and drop-off management

Embodiments provide techniques, including systems and methods, for improving the accuracy of location information for requestor and provider devices in an dynamic transportation matching system using local communications between computing devices. For example, embodiments allow a provider computing device to identify, pair, and/or communicate with a requestor computing device upon arrival near a request location for a ride matching request. The provider computing device may use signal strength measurements associated with signals received from the requestor computing device to identify a proximity to the requestor computing device and/or to triangulate an accurate location of the requestor computing device. Additionally, the provider computing device may use a combination of the location reported by the ride matching system and the signal strength of the paired connection to identify the location of the requestor computing device.

Location accuracy using local device communications

In one embodiment, a method includes detecting, using one or more sensors of a vehicle, an entity in an environment surrounding the vehicle. The method includes determining a position of the entity relative to the vehicle. The method includes determining that a message is to be provided to the entity. The method includes selecting at least one of multiple notification devices of the vehicle based on the position of the entity relative to the vehicle. The method includes providing the message to the entity using the selected notification device.

Growing community of inventors

San Francisco, CA, United States of America

Taggart Matthiesen