Example aspects of the present disclosure relate to a hybrid approach for scheduling delivery services that seamlessly integrates real-time courier matching with pre-matching batch analysis to optimize courier time. An example method includes accessing delivery data for a subset of a plurality of delivery services that are available for batch delivery assessment. The method includes generating a batched route for at least two delivery services of the subset of delivery services based on the delivery data. The method includes detecting a state change that is associated with a delivery service of the batched route. In response to the state change, the method includes accessing real-time vehicle data indicative of an availability of one or more vehicles and communicating data indicative of the batched route to at least one vehicle of the plurality of vehicles.
An online system performs load shedding in case of system overloads. The system maps each request to a tier and a cohort. The tier is determined based on a type of request and the cohort is determined based on the user. Each tier includes multiple cohorts. The tiers and cohorts are ranked by priority. If the system determines that the system is overloaded, the system determines a threshold tier and a threshold cohort for load shedding. The threshold tier and threshold cohort indicate a threshold priority of requests that are processed. If the system determines that the unprocessed request has a priority below the threshold priority indicated by the threshold tier and the threshold cohort, the system rejecting the unprocessed request. The system executes unprocessed requests that are not rejected.
A computer-implemented method includes accessing data descriptive of a plurality of freight lanes, each freight lane being associated with a pickup region and a dropoff region for one or more loads; determining that two or more freight lanes of the plurality of freight lanes satisfy at least one clustering criteria indicative of a similarity between the two or more freight lanes based at least in part on the one or more freight lane attributes; in response to determining that the two or more freight lanes meet the at least one clustering criteria; receiving a request from a carrier computing device to associate a carrier with the clustered freight lane; and assigning at least one load of the one or more loads to the carrier based at least in part on the request from the carrier.
Systems and method for dynamically managing add-on orders within a delivery service application. For example, a computer-implemented method includes obtaining data indicative of a primary order request. The method includes selecting, ranking, and displaying menu items for add-on orders associated with a primary order. The method includes obtaining user data provided by a user through a user interface associated with a delivery service application. The method includes determining, in response to obtaining the user data, that the primary order request is eligible for an add-on order. The method includes determining merchants for the add-on order. The selected merchants can be determined from a plurality of candidate merchants based at least in part on analysis of merchant-specific data relative to the user data indicative of the primary order request. The method includes updating the user interface to display data associated with the one or more selected merchants for the add-on order.
Systems and methods for displaying corresponding content for vehicle services using a distributed set of electronic devices are provided. For example, a computer-implemented method includes obtaining data associated with a vehicle service instance. The vehicle service instance is associated with a request for a vehicle service for a user. The method includes determining, based on the data associated with the vehicle service instance, a first advertisement content item for a display device positioned on an exterior of a vehicle assigned to the vehicle service instance and a second advertisement content item for a user device associated with the vehicle service instance. The method includes communicating data that initiates the display of the first advertisement content item for the display device positioned on the exterior of the vehicle and data that initiates the display of the second advertisement content item for the user device.
Systems and methods for advertisement-based vehicle matching and routing. For example, a computer-implemented method includes obtaining data associated with a vehicle service request. The data associated with the vehicle service request is indicative of a pick-up location and a destination location associated with the vehicle service request. The method includes determining, from among a plurality of candidate vehicles, a selected vehicle for the vehicle service request based on the data indicative of the vehicle service request, candidate advertisement content items, and candidate routes for the plurality of candidate vehicles. The method includes communicating data that initiates display of a selected advertisement content item by a display device positioned on an exterior of the selected vehicle. The method includes communicating data indicative of route information to a computing device associated with the selected vehicle. The route information includes a selected route to the pick-up location.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
B60Q 1/50 - Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic for indicating other intentions or conditions, e.g. request for waiting or overtaking
7.
MANAGEMENT OF OPERATIONS USING ELECTRIC VEHICLE DATA
A system can receive EV data of an EV operated by a driver, where the EV data comprises at least one of a current electric charge of the EV or a current range of the EV. The system can further receive service requests from requesting users, where a subset of the service requests correspond to one or more item pickup locations within a predetermined distance or estimated time of travel of an EV charging station. Based at least in part on the EV data, the system (i) assigns the driver to the subset of service requests, and (ii) determines a route from a location of the EV to the EV charging station, and transmits information corresponding to the subset of service requests and data corresponding to the route to at least one of a computing device operated by the driver or a computing system associated with the EV.
B60L 58/12 - Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
8.
DYNAMIC DETERMINATION AND NOTIFICATION FOR ALTERNATION OF FULFILLMENT MODE FOR A NETWORKBASED SERVICE
This application describes a system associated with a network-based delivery service that receives item delivery requests from various individuals. The system determines whether the item(s) in the item delivery requests can be delivered. If not, the system generates and provides a selectable notification the various individuals. The selectable notification prompts the various individuals to pick up the item(s) in the item delivery request instead of waiting for delivery of the item(s).
A network system can receive a first request for a transport service and a second request for the transport service. The system can identify, from a plurality of service providers, a first set of service providers for the first request, and a second set of service providers for the second request. Based on a first set of predictive parameters for the first set of service providers, the system implements a multi-invite mode by transmitting a first invitation data set to service the first request to a plurality of provider devices of the first set of service providers. Based on a second set of predictive parameters for the second set of service providers, the system implements an exclusive-invite mode by transmitting a second invitation data set to a provider device of a selected service provider of the second set of service providers.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
A computing system can facilitate an on-demand delivery service by receiving menu item requests and transmit corresponding order requests to menu item preparers. The system can execute one or more trained predictive models using a set of current predictive metrics for the menu item preparer to generate probability curves for driver wait time and menu item sit time against a logical cost to the on-demand delivery service. The system may then utilize the curves to determine an optimal arrival time for a selected delivery provider to pick up the menu items for delivery.
A computing system can receive transport requests from requesting users and attempt to match each transport request with a transport provider to transport the requesting user to a destination. Based on a cancelation request from the requesting user received prior to a match being made, the system can determine one or more alternative options for fulfilling the transport request based on one or more attributes indicated in a user profile of the requesting user, and cause a service application executing on the computing device of the requesting user to initiate an interactive mode to display contextual information associated with the matching process, and provide of the one or more alternative options for fulfilling the transport request.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
Systems and methods for dynamic data buffering and provision for vehicle remote assistance are provided. An example computer-implemented method includes obtaining, by a computing system, data associated with an autonomous vehicle. The example method includes detecting, by the computing system, a potential remote assistance event based at least in part on the data associated with the autonomous vehicle. The example method includes initiating, by the computing system, a preliminary remote assistance action based at least in part on the potential remote assistance event. The preliminary remote assistance action includes at least one of transmitting sensor data acquired by the autonomous vehicle to a remote computing system or storing the sensor data onboard the autonomous vehicle. The example method includes communicating, by the computing system after the initiation of the preliminary remote assistance action, a request for remote assistance of the autonomous vehicle.
Systems and methods for autonomous vehicle state management are provided. An offboard state service can obtain a vehicle command associated with changing an onboard-defined state of an autonomous vehicle. Data indicative of the command can be provided to a computing system onboard the autonomous vehicle. The onboard computing system can initiate a vehicle action in accordance with the command and provide a command response indicative of an updated vehicle status for the onboard-defined state to the state service. In response, the state service can update a current status for the onboard-defined state as represented by a vehicle profile corresponding to the autonomous vehicle. The state service can generate an update event indicative of the vehicle state and the updated current status and publish the update event to a distributed event stream such that a number of devices subscribed to the event stream can receive data indicative of the update event.
Systems and methods of generating active notifications for users of a networked computer system using transportation service prediction are disclosed herein. In some example embodiments, a computer system uses a prediction model to generate a transportation service prediction for a user based on an identification of the user, location data for the user, prediction time data, and historical user data for instances of the user using the transportation, and then causes a notification to be displayed on a computing device of the user based on the transportation service prediction, with the notification indicating a recommended use of the transportation service in association with the place for the time of day and the day of the week, and the notification comprising a selectable user interface element configured to enable the user to submit an electronic request for the recommended use of the transportation service.
Systems and methods for tracking objects throughout a multi-modal transportation service are provided. A system can obtain itinerary data identifying a number of transitioning point along a multi-leg transportation service. The system can obtain object data and associate a number of objects identified by the object data with a rider travelling along the multi-leg transportation service. The system can periodically determine the location of the objects while the rider transitions between each leg of the transportation service. The system can determine and initiate an object-check action based on the location of the objects. The object-check action can include facilitating a subsequent leg of the transportation service by providing information corresponding the subsequent leg when the objects are not separated from the rider or blocking the initiation of the subsequent leg or the termination of the current leg when an object is separated from the rider.
Systems and methods of the present disclosure are directed to a method for facilitating pairing of multiple entities. The method can include obtaining a vehicle pairing request for an autonomous vehicle of a vehicle provider comprising vehicle identification data. The method can include determining a temporary pairing code associated with the autonomous vehicle. The method can include providing the temporary pairing code to the vehicle provider. The method can include obtaining a device pairing request via an application executed by a user device, the device pairing request comprising the temporary pairing code and an operational certificate, the operational certificate comprising device identification data associated with the user device. The method can include pairing the user device and the autonomous vehicle based at least in part on the device pairing request.
Example embodiments are directed to systems and methods for providing end of route navigation. In example embodiments, a network system identifies a destination of a route and retrieves a display template based on the destination. The display template provides guidelines for display of end of route content, whereby the display of the end of the route content is different than display of content during a middle of the route. The network system identifies, based on the display template, a display time to trigger the display of the end of the route content. The display time may be associated with a threshold distance to the destination. The network system monitors a location of a vehicle along the route and accesses end of route content. Responsive to detecting that the location of the vehicle is at the threshold distance to the destination, the network system causes presentation of the end of the route content on a device associated with the vehicle.
Various examples are directed to systems and methods for providing transportation services. A service assignment system may receive a transportation service request from a user. The transportation service request may describe a transportation service having a start location and an end location. The service assignment system may select a first autonomous vehicle (AV) of a first AV type and determine a first predicted route for the first AV using vehicle capability data describing the first AV type and first difference data describing a difference between a previous predicted route for a previous AV of the first AV type and a previous planned route received from the previous AV of the first AV type. The service assignment system may receive, from the first AV, a first planned route for executing the transportation service and instruct the first AV to begin executing the transportation service.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
Various examples are directed to a service assignment system for providing transportation services. The service assignment system may receive a transportation service request from a user. The transportation service request may describe a transportation service having a service start location and a service end location. The service assignment system may generate a plurality of routes for executing the transportation service. The service assignment system may send proposed route data describing at least a portion of the plurality of routes to a first autonomous vehicle (AV). The service assignment system may receive, from the first AV, route data describing a first route to execute the transportation service and send, to the first AV, instruction data instructing the first AV to begin executing the transportation service.
Systems and methods herein describe accessing a set of feature flags, a first feature flag in the set of feature flag describing vehicle navigation behavior on a routing graph, the routing graph representing the roadway, associating the set of feature flags with a vehicle, applying the associated set of feature flags to a graph traversal algorithm to generate a modified graph traversal algorithm, generating the route using the modified graph traversal algorithm; and transmitting instructions to the vehicle to begin executing the route.
Systems and methods are directed using a machine learning model to determine content to display on a map. The system detects an event associated with a transportation service being requested via an application on a user device of a user. The system accesses real-time data (e.g., sensor data indicating location of the user device) and historical data associated with the user. The system also determines connectivity for a location of the client device. The connectivity can include one or more of a load time for an area that the user device is located, battery life of the user device, or network strength of a connection. Next, the system analyzes the accessed data and the connectivity to identify display elements to present on the client device based on the event. The system then causes presentation of the display elements on the client device.
A system can receive input data from an application running on a computing device of a requesting user. The input data can correspond to a set of alphanumeric characters provided in a search box presented on a user interface of the application. In response to receiving the input data, the system can execute a federated search by providing search data corresponding to the set of alphanumeric characters to multiple search engines operated by the computing system, each search engine pertaining to a specific service option of multiple service options that are accessible via the application. The system can obtain and process search results from the multiple search engines based on the search data in accordance with a unification protocol to generate a unified search result. The system may then transmit data enabling the application to present a selectable user interface feature for each result of the unified search result.
Systems and methods for autonomous vehicle operations are provided. An example computer-implemented method includes obtaining data indicative of vehicle fleet feature(s) associated with an autonomous vehicle fleet. The method includes obtaining data indicative of a vehicle service request associated with a user, the vehicle service request indicating a request for a vehicle service. The method includes determining user feature(s) associated with the user. The method includes determining a compatibility of the user and the autonomous vehicle fleet for the vehicle service based at least in part on the fleet feature(s) and the user feature(s). Determining the compatibility can include predicting how the autonomous vehicle fleet will perform the vehicle service associated with the vehicle service request based at least in part on the fleet's autonomy capabilities. The method includes communicating data associated with the vehicle service request to a computing system associated with the autonomous vehicle fleet.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
A vehicle navigation system may include a data pipeline that proposes routing graph modifications from automatically ingested data sources and that provides enough context to suggest an expiration time to remove the routing graph modifications once imposed. The system and method receives from at least one data source routing graph modification data including geographic location data identifying a location to which a routing graph modification applies. The routing graph modification data is associated with one or more roadway elements in a routing graph of a navigation constraints system, and the routing graph modification data associated with the one or more roadway elements is classified as a routing graph modification. The routing graph modification is added to or, if expired, removed from the navigation constraints system.
Various examples are directed to systems and methods for routing autonomous vehicles. A system may receive vehicle capability data describing autonomous vehicles of a first type. The vehicle capability data may comprise geofence data describing a first geographic area. The system may generate first routing graph modification data comprising a first graph element descriptor based at least in part on the first geographic area and a first constraint. The system may access routing graph data describing a plurality of graph elements. The system may generate a first route for an autonomous vehicle of the first type. The generating may be based at least in part on the first routing graph modification data and the routing graph data.
The present disclosure is directed to using anomaly data detected in traffic data to efficiently initiate remote assistance sessions. In particular, a computing system can receive, from a computing device associated with a human-driven vehicle, travel data for the human-driven vehicle. The computer system can identify a navigation anomaly associated with the human-driven vehicle based on the travel data. The computer system can generate, based on the identified navigation anomaly, an anomaly entry for storage in an anomaly database, the anomaly entry comprising geofence data describing a geographic area associated with the navigation anomaly. The computer system can determine, based on location data received from an autonomous vehicle and the geofence data, that the autonomous vehicle is entering the geographic area associated with the navigation anomaly. The computer system can initiate a remote assistance session with the autonomous vehicle.
G05D 1/00 - Control of position, course, altitude, or attitude of land, water, air, or space vehicles, e.g. automatic pilot
B60W 50/00 - CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - Details of control systems for road vehicle drive control not related to the control of a particular sub-unit
A document transcription application receives an image of a document that comprises structured data. The document transcription application performs optical character recognition upon the image of the document to produce a block of text. The document transcription application applies the block of text to a first machine learning model to determine a heat map for a class of data in the structured data in the image of the document. The document transcription application applies the image of the document and the heat map to a second machine learning model to identify a region of the image of the document representing the class of data. The document transcription application generates, using the identified region and the block of text, a structured data file.
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
28.
SYSTEMS AND METHODS FOR FACILITATING A MULTI-MODAL TRANSPORTATION SERVICE
Systems and methods for facilitating a multi-modal transportation service are provided. The method includes obtaining a request for an aerial transport from a user via user device and generating a multi-modal transportation itinerary for the user to facilitate the aerial transport of the user. The method includes determining a state change indicative of the progress of the user through the transportation service and adjusting an aerial software application running on an aerial device associated with an aerial service provider based on the state change. The method includes determining a subsequent state change occurring after the state change, determining a ground vehicle to provide a ground transportation for the user during another leg of the multi-modal transportation service based on the subsequent state, and adjusting a ground software application running on a ground device associated with the ground vehicle service provider based on the subsequent state change.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
A network system can communicate with user and provider devices to facilitate the provision of a network-based service. The network system can identify optimal service providers to provide services requested by users. The network can utilize context data in matching service providers with users. In particular, the network system can determine, based on context data associated with a user, whether to perform pre-request matching for that user. A service provider who is pre-request matched with the user can be directed by the network system to relocate via a pre-request relocation direction. When the user submits the service request after the pre-request match, the network system can either automatically transmit an invitation to the pre-request matched service provider or can perform post-request matching to identify an optimal service provider for the user.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
A battery pack includes a cassette stack comprising a plurality of battery cell cassettes, each of the cassettes including a plurality of support structures. Each support structure comprises an electrically and thermally conductive frame for receiving at least one battery cell having a first terminal and a second terminal, and a heat pipe. The first terminal is electrically coupled to the frame when the at least one battery cell is mounted in the frame. The heat pipe provides thermal conductivity between the frame and a cooling surface. A method of cooling an electric vehicle including a battery pack comprises aligning the battery pack and a cooling structure, moving the cooling structure into contact with the electric vehicle, and circulating coolant through the cooling structure.
H01M 10/6552 - Closed pipes transferring heat by thermal conductivity or phase transition, e.g. heat pipes
H01M 10/6569 - Fluids undergoing a liquid-gas phase change or transition, e.g. evaporation or condensation
H01M 50/202 - Casings or frames around the primary casing of a single cell or a single battery
H01M 50/204 - Racks, modules or packs for multiple batteries or multiple cells
H01M 50/249 - Mountings; Secondary casings or frames; Racks, modules or packs; Suspension devices; Shock absorbers; Transport or carrying devices; Holders specially adapted for aircraft or vehicles, e.g. cars or trains
A delivery management system may select a set of preparation sites for the user using preparation site location data and a delivery site associated with the user. The set of preparation sites may comprise a virtual preparation site that is associated with a second preparation site. The delivery management system may serve menu data to a user computing device. The menu data may indicate at least a first item associated with the virtual preparation site. The delivery management system may receive, from the user computing device, a first order indicating the first item. The delivery management system may send a second order for the first item to the second preparation site, where the second order indicates delivery to the virtual preparation site. The delivery management system may request a vehicle to deliver the first item to the virtual preparation site.
Systems and methods for improving aerial ride quality based on user feedback accessed from an aerial vehicle and devices associated with passengers are provided. A network system receives, from one or more devices associated with a passenger on an aerial vehicle, feedback data regarding a flight, whereby the feedback data is associated with an issue experienced by the passenger. The network system then identifies a root cause of the issue experienced by the passenger on the aerial vehicle. The identifying may include correlating the feedback data with other data associated with the flight. A mitigation action to mitigate the issue is determined. The network system may determine whether to trigger the mitigation action based on a corresponding threshold and can trigger the mitigation action to occur accordingly.
Systems and methods for determining appropriate energy replenishment and controlling autonomous vehicles are provided. An example computer-implemented method can include obtaining one or more energy parameters associated with an autonomous vehicle. The method can include determining a refueling task for the autonomous vehicle based at least in part on the energy parameters associated with the autonomous vehicle. The refueling task comprises a first refueling task that is interruptible by a vehicle service assignment or a second refueling task that is not interruptible by the vehicle service assignment. The method can include communicating data indicative of the refueling task to the autonomous vehicle or to a second computing system that manages the autonomous vehicle. The method can include determining whether the refueling task for the autonomous vehicle has been accepted or rejected.
A computing system can detect high capacity vehicles (HCVs) coming online to provide transport services. The computing system monitors transport demand for HCV corridors throughout a geographic region. Each HCV corridor comprises a plurality of possible rendezvous locations and a plurality of possible routes that can be traveled by individual HCVs through the HCV corridor, as opposed to having fixed routes with fixed stops. The computing system can determine a schedule for each HCV corridor, and monitor supply flow of HCVs traveling through each HCV corridor. Based on (i) the transport demand, (ii) the schedule, and (iii) the supply flow of the HCVs for each of the HCV corridors, the computing system can match the HCV with a specified HCV corridor, and transmit match data indicating a start zone of the matching HCV corridor to the computing device of the HCV.
H04W 4/42 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for mass transport vehicles, e.g. buses, trains or aircraft
G08G 1/09 - Arrangements for giving variable traffic instructions
Disclosed are methods and systems for predicting time varying loudness in a geographic region. Training data, including noise information, weather information, and traffic information is collected from a plurality of sensors located in a plurality of geographic regions. The information is collected during multiple time periods. The noise information includes time varying loudness. Static features of the geographic regions are also defined and included in the training data. The static and time varying dynamic features train a model. The model is used predict time varying loudness within a different region and at a time later than times the training data is collected. The predicted loudness levels are utilized, in some aspects, to determine a route for an aircraft.
G10K 11/00 - Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
Example embodiments are directed to generating an optimized network of flight paths and an operations volume around each of these flight paths. A network system creates a source network of paths, whereby the source network comprises a set of possible paths between two locations. The network system assigns a cost for traversing each edge of each path of the source network and aggregates the cost for traversing each edge of each path to obtain a cost for each path of the source network. Based on the cost for each path, the network system identifies a path having the lowest cost, whereby the path having the lowest cost is the optimized route between the two locations. The network system then generates an operations volume for the optimized route. The operations volume represents airspace surrounding the optimized route. The operations volume is transmitted to a further system for use.
Disclosed herein are systems and methods for planning a multimodal itinerary. The systems and methods may include receiving a transportation request (702). The transportation request may include a starting location, a final destination, and an estimated payload data. During a first leg of the multimodal itinerary (704), an updated payload data may be received. An aerial vehicle may be assigned to a subsequent leg of the multimodal itinerary (708) based on the updated payload data (706).
A computing system computes a timing interval between high-capacity vehicles (HCVs) for each HCV corridor within a geographic region to control rates of HCVs entering and exiting each of the HCV corridors. For each of the HCV corridors, the computing system schedules a first HCV to provide a transport service along the corridor beginning at a first starting time, transmits first schedule data for the corridor to the first HCV, schedules a second HCV to provide the transport service along the corridor beginning at a second starting time after the first starting time according to the timing interval for the corridor, and transmits second schedule data for the corridor to the second HCV.
H04W 4/42 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for mass transport vehicles, e.g. buses, trains or aircraft
G08G 1/09 - Arrangements for giving variable traffic instructions
Aerial vehicles are assigned to routes within a transportation network based on a state of charge, state of power, and/or state of health for the aerial vehicle. Such aspects can be modeled based on one or more statistical models and/or machine-learned models, among other examples. As another example, an energy budget is used to ensure that the state of charge, state of power, and/or state of health of the aerial vehicle during and/or after traveling the route remains within the energy budget. A payload is assigned to a route and an associated aerial vehicle, thereby generating an itinerary. In examples, the itinerary is validated by the aerial vehicle to ensure that the aerial vehicle is capable of traveling the route with the payload. In examples where the aerial vehicle rejects the itinerary, the itinerary is assigned to another aerial vehicle and a new itinerary is identified for the aerial vehicle.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
A computing system can assign a transport request to a high capacity vehicle (HCV) corridor of a plurality of HCV corridors, where the HCV corridor is associated with a plurality of possible rendezvous locations and a plurality of possible routes that can be traveled by individual HCVs. The computing system can determine, from the transport request of the requesting user, an optimal pick-up location from the plurality of possible rendezvous locations of the HCV corridor for an HCV to rendezvous with the requesting user.
The present disclosure is directed to configuring vehicle communications. In particular, a computing system comprising one or more computing devices physically located onboard a vehicle can communicate a plurality of different and distinct types of information associated with the vehicle to a remotely located computing system via a data stream transmitted from the vehicle to the remotely located computing system. The computing system can determine one or more changes in at least one of a mode, state, or context of the vehicle, and responsive to determining the change(s), the computing system can modify one or more parameters of the data stream transmitted from the vehicle to the remotely located computing system.
The present disclosure is directed to managing network resources of a vehicle. In particular, for each application of a plurality of different and distinct applications executed by a computing system comprising one or more computing devices physically located onboard a vehicle, the computing system can: determine, from amongst a plurality of different and distinct interface identifiers, an interface identifier associated with the application; communicate, based at least in part on the interface identifier associated with the application, data associated with the application and destined for a remotely located computing system; and manage, based at least in part on the interface identifier associated with the application, utilization by the application of network resources interfacing the computing system and the remotely located computing system to communicate the data associated with the application and destined for the remotely located computing system.
Systems and methods are provided for determining location data corresponding to a location of a user, retrieving candidate locations for pickup or drop-off locations based on the location data corresponding to the location of the user, and determining a safety score for each of the candidate locations. The systems and methods further select a best candidate location using the safety score associated with each of the candidate locations and provide a recommendation for a pickup or drop-off location comprising the best candidate location.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
The present disclosure provides systems and methods for real-time planning and fulfillment of multi-modal transportation services in a multi-modal ride sharing network. In particular, aspects of the present disclosure are directed to a computing system that creates an end-to-end multi-modal itinerary responsive to a user request for transportation service between an origin and a destination. The multi-modal itinerary can include two or more transportation legs that include travel via two or more different transportation modalities such as, as examples, via a car and via an aircraft.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
A proximity alert system tracks geographic locations of riders and drivers using global navigation satellite system receivers in their mobile devices or in a device such as a beacon or dashcam. The proximity alert system compares the location data received from the riders' and drivers' devices and determines whether a service-requesting user is within a threshold distance of one of the driver devices that does not belong to the driver assigned to provide transport service for the rider. If so, the proximity alert system can communicate a notification message to the rider to confirm whether the rider is in the correct car. The proximity alert system can also communicate a message to the driver asking the driver to double-check the identity of the rider.
H04W 4/02 - Services making use of location information
G08B 19/00 - Alarms responsive to two or more different undesired or abnormal conditions, e.g. burglary and fire, abnormal temperature and abnormal rate of flow
Systems and methods for providing user control of alternate routes are provided. In example embodiments, a networked system identifies a current location of a vehicle of a driver and a destination of the driver. The networked system accesses driving preferences of the driver, whereby the driving preferences including preferences derived from past selection of routes by the driver. The networked system then determines, a plurality of routes from the current location of the vehicle to the destination based on the driving preferences. The plurality of routes is then displayed on a user interface of a device of the driver.
Aspects of the present disclosure include systems, methods, and devices to facilitate pick-up/drop-off zone (PDZ) handoffs between autonomous vehicles. Consistent with some embodiments, a pick-up/drop-off zone (PDZ) is located based on detecting a first autonomous vehicle stopped at a stopping location. A system determines, based on one or more criteria, whether to request the first autonomous vehicle to remain stopped at the stopping location to create an opportunity for a second autonomous vehicle to claim the PDZ. An amount of time for the first autonomous vehicle to remain stopped at the stopping location is determined based on the one or more criteria. A request to remain stopped at the stopping location is transmitted to a vehicle autonomy system of the first autonomous vehicle based on satisfaction of the one or more criteria. The request specifies the amount of time for the first autonomous vehicle to remain at the stopping location.
This disclosure describes a rechargeable battery for a light electric vehicle. More specifically, this disclosure describes a rechargeable battery and a rechargeable battery holster that may be used to removably couple the rechargeable battery to a light electric vehicle.
A computing device can monitor a set of memory usage metrics of the computing device. Based on historical memory usage data and the set of memory usage metrics, the computing device can determine whether memory usage will exceed a critical memory threshold at a future instance in time. In response to determining that the memory usage will exceed the critical memory threshold at the future instance in time, the computing device can degrade one or more application features of an application executing on the computing device.
A network system, such as a transport management system, generates a mutual augmented reality (AR) experience for a user and a provider associated with a service. Responsive to receiving a service request, a service management module matches the user with an available provider and monitors the location of the user and provider client devices as the user and provider travel to the pickup location. When the devices are within a threshold distance of each other, an image recognition module monitors live video streams on the devices for the vehicle and the user. Responsive to the vehicle and user entering the field of view of the devices, an AR control module selects computer-generated AR elements and instructs the devices to visually augment the video streams to identify the user and provider to each other and to allow the user and provider to communicate and share data with each other.
G01C 21/36 - Input/output arrangements for on-board computers
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
G06T 19/00 - Manipulating 3D models or images for computer graphics
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G08G 1/00 - Traffic control systems for road vehicles
A network computer system that determines metrics related to effort and cost on the part of deliverers who deliverer items for delivery orders. The network computer system can implement operations to facilitate or mitigate features that cause deliverers to expend effort or cost when completing delivery tasks.
Service providers can be identified to fulfill service requests of a network-based service. A network system is configured to generate, based on historical data associated with the network-based service, a machine-learned service provider optimization (MLSPO) model for generating service provider optimizations. The optimizations can include action recommendations that optimize one or more service metrics. The MLSPO model can be a reinforcement learning model generated by performing a plurality of simulations utilizing one or more virtual agents. A provider device of a service provider can transmit a set of data to the network system that indicates a current location of the service provider. Based on the current location and the MLSPO model, the network system can generate service provider optimizations. Optimization data can be transmitted to the provider device so that the provider device can display information corresponding to the service provider optimizations.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
53.
LOCATION-SPOOFING DETECTION SYSTEM FOR A NETWORK SERVICE
A computing system can receive, over one or more networks, location data from the computing devices of user as the user operate throughout a region. For each user, the computing system can determine whether the user is operating a location-spoofing application on the computing device of the user based, at least in part, on the location data received from the computing device of the user.
A mobile computing device can capture a plurality of images of an object to be verified using a camera of the mobile computing device. A first image of the plurality of images is captured while a flash of the mobile computing device is deactivated and a second of the plurality of images is captured while the flash is activated. The verification data can include a first set of verification metrics, which is representative of the light reflectivity of the object, and can be generated by the mobile computing device or a network service by analyzing the first and second images.
G06K 9/46 - Extraction of features or characteristics of the image
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
55.
SELECTIVELY HIGHLIGHTING MAP FEATURES ASSOCIATED WITH PLACES
Systems and methods of providing a user interface in which map features associated with places are selectively highlighted are disclosed herein. In some example embodiments, a computer system receives a request for a transportation service associated with a place, retrieves an entrance geographic location for the place from a database, with the entrance geographic location being stored in association with the place in the database and representing an entrance for accessing the place, generating route information based on the retrieved entrance geographic location, with the route information indicating a route from an origin geographic location of a computing device of a user to the entrance geographic location of the place, and causing the generated route information to be displayed within a user interface on a computing device of the user.
In some example embodiments, a computer system performs operations comprising: receiving a request for a transportation service associated with a place; determining a type of the transportation service from among a plurality of types of transportation services based on the request; retrieving an entrance geographic location for the place from a database based on the type of the transportation service, the entrance geographic location being stored in association with the place in the database, and the entrance geographic location representing an entrance for accessing the place; generating route information based on the retrieved entrance geographic location, the route information indicating a route from an origin geographic location of a computing device of a user to the entrance geographic location of the place; and causing the generated route information to be displayed within a user interface on a computing device of the user.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
A network computer system for managing a network service (e.g., a transport service) can include a voice-assistant subsystem for generating dialogues and performing actions for service providers of the network service. The network computer system can receive, from a user device, a request for the network service. In response, the network computer system can identify a service provider and transmit an invitation to the provider device of the service provider. In response to the identification of the service provider for the request, the voice-assistant subsystem can trigger an audio voice prompt to be presented on the provider device and a listening period during which the provider device monitors for an audio input from the service provider. Based on the audio input captured by the provider device, the network computer system can determine an intent corresponding to whether the service provider accepts or declines the invitation.
Disclosed are methods, systems, and non-transitory computer readable media that control an autonomous vehicle via at least two sensors. One aspect includes capturing an image of a scene ahead of the vehicle with a first sensor, identifying an object in the scene at a confidence level based on the image, determining the confidence level of the identifying is below a threshold, in response to the confidence level being below the threshold, directing a second sensor having a field of view smaller than the first sensor to generate a second image including a location of the identified object, further identifying the object in the scene based on the second image, controlling the vehicle based on the further identification of the object.
Systems and methods for controlling autonomous vehicles are provided. In one example embodiment, a computing system can obtain data indicative of a service assignment associated with an autonomous vehicle. The service assignment is indicative of a destination location. The computing system can determine a checklist associated with the destination location. The computing system can provide, for display via a display device, data indicative of a user interface. The user interface can present the checklist associated with the destination location. The computing system can obtain data indicative of user input associated with the checklist. The computing system can determine that the checklist has been completed based at least in part on the user input associated with the checklist. The computing system can, in response to determining that the checklist has been completed, cause the autonomous vehicle to initiate a motion control to travel to the destination location.
Aspects of the present disclosure involve systems, methods, and devices for mitigating Lidar cross-talk. Consistent with some embodiments, a Lidar system is configured to include one or more noise source detectors that detect noise signals that may produce noise in return signals received at the Lidar system. A noise source detector comprises a light sensor to receive a noise signal produced by a noise source and a timing circuit to provide a timing signal indicative of a direction of the noise source relative to an autonomous vehicle on which the Lidar system is mounted. A noise source may be an external Lidar system or a surface in the surrounding environment that is reflecting light signals such as those emitted by an external Lidar system.
In one example embodiment, a computer-implemented method for transporting cargo using smart palettes includes determining receipt of a first cargo onto a platform of a first smart palette at a first distribution hub. The method includes generating one or more signals that control a loading of the first smart palette and the first cargo onto a trailer located at the first distribution hub. The method includes determining a coordination with one or more second smart palettes associated with the trailer to determine a first position inside the trailer for the first smart palette and the first cargo. The method includes generating one or more signals that position the first smart palette and the first cargo at the first position inside the trailer.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/08 - Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
Systems and methods are directed to facilitating secure, bidirectional communications between autonomous vehicles associated with a plurality of entities and a provider infrastructure. In one example, a computer-implemented method for facilitating communications with a vehicle includes obtaining, by a computing system comprising one or more computing devices, a communication associated with an autonomous vehicle via an application programming interface platform, wherein the application programming interface platform comprises a plurality of vehicle services interfaces. The method further includes determining, by the computing system, an entity-type of the autonomous vehicle. The method further includes determining, by the computing system, a vehicle services interface of the plurality of vehicle services interfaces based at least in part on the communication associated with the autonomous vehicle and the entity-type. The method further includes providing, by the computing system, the communication associated with the autonomous vehicle to a system client via the vehicle services interface.
Systems and methods for controlling an autonomous vehicle to reduce wasteful data usage are provided. In one example embodiment, a computing system can determine that a first autonomous vehicle is in an idle state in which the first autonomous vehicle is online with a service entity and is not performing a vehicle service. The computing system can obtain vehicle parameter(s) associated with the first autonomous vehicle that is in the idle state and environmental parameter(s). The computing system can determine a task for the first autonomous vehicle to perform while the first autonomous vehicle is in the idle state based at least in part on at least one of the vehicle parameter(s) or the environmental parameter(s). The computing system can communicate data indicative of the task for the first autonomous vehicle to perform while the first autonomous vehicle is in the idle state.
Systems and methods are provided for detecting objects of interest. A computing system can input sensor data to one or more first machine-learned models associated with detecting objects external to an autonomous vehicle. The computing system can obtain as an output of the first machine-learned models, data indicative of one or more detected objects. The computing system can determine data indicative of at least one uncertainty associated with the one or more detected objects and input the data indicative of the one or more detected objects and the data indicative of the at least one uncertainty to one or more second machine-learned models. The computing system can obtain as an output of the second machine-learned models, data indicative of at least one prediction associated with the one or more detected objects. The at least one prediction can be based at least in part on the detected objects and the uncertainty.
A network system implementing or managing a network-based service is configured to receive a query from a user device, the query indicating a start location and a service location. Based on the start location, service location, and the time of receipt of the query, the network system can determine whether to perform request optimization for the user. In response to determining to perform request optimization and if the user accepts request optimization, the network system can schedule or queue the request for service from the user for processing during an optimization time window. The request optimization can improve the probability that the request from the user is matched with other requests from other users for a rideshare-pooling service class of the network-based service. In some circumstances, the network system can determine to automatically perform request optimization without prompting the user to accept or decline the request optimization.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
Systems and methods of pre-fetching map data are disclosed herein. In some example embodiments, a computer system determines that a network connectivity metric of a geographic area satisfies predetermined criteria, with the network connectivity metric comprising a metric of ability of a computing device to communicate with a remote server via a network connection while the computing device is within the geographic area. The computer system causes a map data item corresponding to the geographic area to be downloaded from the remote server onto the computing device during a time at which the computing device is not located within the geographic area based on the determination that the network connectivity metric of the geographic area satisfies the predetermined criteria. The map data item is configured to be used by the computing device to display a visual representation of the geographic area on the computing device.
A communication system develops an activity profile for multiple operators, where the activity profile of each operator is based, at least in part, on a recent location of the operator, as well as a set of transport parameters for the current assignment of the respective operator. A candidate set of operators can be matched to an open request, where the determination for each operator of the candidate set is based on the activity profile developed for that operator. When the candidate set of operators is determined, the communication system transmits a communication to at least one operator of the candidate set that identifies the at least one matched request.
Systems and methods for determining object intentions through visual attributes are provided. A method can include determining, by a computing system, one or more regions of interest. The regions of interest can be associated with surrounding environment of a first vehicle. The method can include determining, by a computing system, spatial features and temporal features associated with the regions of interest. The spatial features can be indicative of a vehicle orientation associated with a vehicle of interest. The temporal features can be indicative of a semantic state associated with signal lights of the vehicle of interest. The method can include determining, by the computing system, a vehicle intention. The vehicle intention can be based on the spatial and temporal features. The method can include initiating, by the computing system, an action. The action can be based on the vehicle intention.
In one example embodiment, a computer-implemented method includes obtaining sensor data from a sensor, the sensor data corresponding to an image frame, and the sensor data including a first portion that corresponds to a portion of the image frame. The method includes pipelining the first portion of the sensor data into a machine-learned model before the sensor data corresponding to the entire image frame is transferred from the sensor to a memory device, to perform one or more inference operations on the first portion of the sensor data. The method includes generating as an output of the machine-learned model, in response to pipelining the sensor data corresponding to each portion of the image frame into the machine-learned model, a detection or classification of the one or more objects indicated within the sensor data.
The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a motion planning system that solves gridlock as part of determining a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can determine one or more keep clear areas associated with the lane sequence, each keep clear area indicative of a region along the nominal path in which gridlock prevention is desired. A gridlock constraint can be generated for each of the one or more keep clear areas, each constraint being defined as a constraint area in a multi-dimensional space. A low-cost trajectory path can be determined through a portion of the multi-dimensional space that minimizes exposure to the constraint areas and that is consistent with all constraints generated for the one or more objects of interest and the one or more keep clear areas.
B60W 50/00 - CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - Details of control systems for road vehicle drive control not related to the control of a particular sub-unit
G01C 21/26 - Navigation; Navigational instruments not provided for in groups specially adapted for navigation in a road network
G05D 1/02 - Control of position or course in two dimensions
G08G 1/00 - Traffic control systems for road vehicles
71.
AUTOMOBILE ACCIDENT DETECTION USING MACHINE LEARNED MODEL
A system detects whether an automobile was involved in an accident. The system receives sensor data detecting motion of the automobile, for example, acceleration or location of the automobile. The system aggregates features describing the impact event including contextual features, for example, type of roadway, speed limit, and points of interest near the location of impact and event features, for example, force of impact, distance travelled since impact, speed before the impact, and so on. The system provides the features as input to a machine-learned model. The system determines using the machine-learned model whether the automobile was involved in an accident. The system may provide sensor data describing the impact to a neural network to generate feature vectors describing the sensor data. The system uses the feature vector for determining whether an impact occurred.
Systems and methods are directed to automated delivery systems. In one example, a vehicle is provided including a drive system, a passenger cabin; and a delivery service pod provided relative to the passenger cabin. The delivery service pod includes an access unit configured to allow for loading and unloading of a plurality of delivery crates into the delivery service pod. The delivery service pod further includes a conveyor unit comprising multiple delivery crate holding positions, the delivery crate holding positions being defined by neighboring sidewalls spaced apart within the delivery service pod such that a respective delivery crate of the plurality of delivery crates can be positioned between neighboring sidewalls, wherein the conveyor unit is configured to be rotated to align each of the delivery crate holding positions with the access unit.
B60P 1/36 - Vehicles predominantly for transporting loads and modified to facilitate loading, consolidating the load, or unloading using endless chains or belts thereon
B60P 3/00 - Vehicles adapted to transport, to carry or to comprise special loads or objects
B60S 1/64 - Other vehicle fittings for cleaning for cleaning vehicle interiors, e.g. built-in vacuum cleaners
73.
NETWORK SERVICE FOR DYNAMIC SELECTION OF VOICE COMMUNICATION MEDIUM FOR CALL CONNECTIONS
A network computer system can respond to a call connection signal by making a determination as to whether the call connection is likely to be supported for at least one of the caller or receiver using a first voice communication medium, as compared to an alternative voice communication medium. Based on the determination, the network computer system can cause the call connection to be established using the voice communication medium of the determination.
A light detection and ranging (LIDAR) sensor assembly can comprise an optics assembly that includes a LIDAR sensor and a set of dovetail joint inserts. The LIDAR sensor assembly can further include a frame comprising a set of dovetail joint septums coupled to the set of dovetail joint inserts of the optics assembly.
Systems and methods can generate and/or implement coverage plans for vehicle navigation. Such coverage plans can be descriptive of a travel route for a vehicle to navigate a set of travel way portions within a map of a geographic area. The coverage plan can include a travel route that traverses each travel way portion at least once while reducing total travel cost (e.g., defined by a travel distance, number and/or types of turns, etc.) over all travel way portions. The coverage plan can also reduce turn angles and/or eliminate u-turns in order to provide a coverage plan that is safer and easier for implementation by vehicles controlled to navigate along the travel route.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G01C 21/32 - Structuring or formatting of map data
G05D 1/02 - Control of position or course in two dimensions
A request for transport services that identifies a rider, an origin, and a destination is received from a client device. Eligibility of the request to be serviced by a vertical take-off and landing (VTOL) aircraft is determined based on the origin and the destination. A transportation system determines a first and a second hub for a leg of the transport request serviced by the VTOL aircraft and calculates a set of candidate routes from the first hub to the second hub. A provisioned route is selected from among the set of candidate routes based on network and environmental parameters and objectives including pre-determined acceptable noise levels, weather, and the presence and planned routes of other VTOL aircrafts along each of the candidate routes.
G01C 23/00 - Combined instruments indicating more than one navigational value, e.g. for aircraft; Combined measuring devices for measuring two or more variables of movement, e.g. distance, speed or acceleration
A computing system for landing and storing vertical take-off and landing (VTOL) aircraft (208) can be configured to receive aircraft data, passenger data, or environment data associated with a VTOL aircraft and determine a landing pad (212) location within a landing facility (202) based on the aircraft data, passenger data, and/or environment data. The landing facility (202) can include a lower level (205) and an upper level (216). The lower level (205) can include a lower landing area and a lower storage area. The upper level (216) can include an upper landing area. At least a portion of the upper level can be arranged over the lower storage area. The landing pad location (212) can include a location within the lower landing area or the upper landing area of the landing facility. The computing system can communicate the landing pad location (212) to an operator or a navigation system of the VTOL aircraft.
Systems and methods for controlling an autonomous vehicle to reduce idle data usage and vehicle downtime are provided. In one example embodiment, a computing system can obtain data associated with autonomous vehicle(s) that are online with a service entity. The computing system can obtain data indicative of the geographic area with an imbalance in a number of vehicles associated with the geographic area. The computing system can determine a first autonomous vehicle for re-positioning with respect to the geographic area based at least in part on the data associated with the one or more autonomous vehicles and the data indicative of the geographic. The computing system can communicating data indicative of a first re-positioning assignment associated with the first autonomous vehicle. In some implementations, the computing system can generate vehicle service incentive to entice a vehicle provider to re-position its autonomous vehicles with respect to the geographic area.
A vertical takeoff and landing (VTOL) aircraft, configured to transport passengers and/or cargo, uses propellers during vertical flight and wings during forward flight to generate lift. The VTOL aircraft includes a front wing and a rear wing connected by inboard booms. The rear wing may include a wingtip boom attached to each free end of the wing. A propeller may be attached to each inboard boom and each wingtip boom. The propellers attached to the inboard booms may be stacked propellers including at least two co-rotating propellers. The aircraft can also include a cruise propeller attached to the tail region of the fuselage, where the cruise propeller is configured to rotate in a plane approximately perpendicular to the fuselage to generate thrust during forward flight.
A request for transport services that identifies a rider, an origin, and a destination is received from a client device. Eligibility of the request to be serviced by a vertical take-off and landing (VTOL) aircraft is determined based on the origin and the destination. The client device is sent an itinerary for servicing the transport request including a leg serviced by the VTOL aircraft. Confirmation is received that the rider has boarded the VTOL aircraft and determination made as to whether the VTOL aircraft should wait for additional riders. Instruction are sent to the VTOL aircraft to take-off if one or more conditions are met.
A mobile computing device can operate as a user device or a service provider device for a network-based service. The mobile computing device can transmit location data to a network system to aid in the network system's management of the network-based service. The mobile computing device can dynamically adjust the location data transmission rate at which location data is transmitted to the network system based on various parameters, including one or more of: a power status, information related to the network-based service, network connectivity metrics, and the like. By dynamically adjusting the location data transmission rate based one or more of these parameters, the mobile computing device can conserve battery power without adversely affecting the provisioning of the network-based service.
A computer-implemented method for controlling one or more assets using a vehicle-based service provided based on monitoring an available capacity at a location, wherein the one or more assets are autonomous vehicles, the method comprising: identifying, by a computing system that includes one or more computing devices, one or more assets that will arrive at a first location within a first transfer hub at an arrival time; sending, by the computing system, data indicative of the one or more assets to a transportation network computing system associated with the first transfer hub; obtaining, by the computing system, data indicative of an available capacity at the first location for receiving the one or more assets at the arrival time; and controlling, by the computing system, the one or more assets based at least in part on the available capacity, so as to cause at least one of the one or more assets to: adjust an arrival time of the at least one of the one or more assets, and drive so as to arrive at the adjusted arrival time; and/or adjust a destination of the at least one of the one or more assets, and drive to the adjusted destination.
In one example embodiment, a computer-implemented method for controlling the movement of assets at transfer hubs includes determining one or more assets to move from a first location associated with a transfer hub. The method also includes assigning a jockey to move the one or more assets to a second location associated with the transfer hub based at least in part on an availability of the jockey. The method further includes directing the jockey to move the one or more assets from the first location to the second location.
A computer-implemented method for controlling an arrival of an asset at a location, wherein the asset is an autonomous vehicle, the method comprising: identifying, by a computing system that includes one or more computing devices, one or more assets arriving at a transfer hub, based at least in part on one or more attributes associated with the one or more assets; determining, by the computing system, an arrival time for the one or more assets, based at least in part on an available capacity associated with the transfer hub for receiving the one or more assets; and controlling, by the computing system, the one or more assets to arrive at the determined arrival time wherein the controlling of the asset comprises transmitting data indicative of one or more control signals to the one or more assets, wherein the one or more control signals are configured to cause at least one of the one or more assets to adjust a driving parameter and operate in accordance with the adjusted driving parameter so as to arrive at the determined arrival time.
A network computing system can coordinate an on-demand transport service utilized by internal autonomous vehicles (AVs), third-party AVs, and human-driven vehicles. The system can receive transport requests from requesting users, where each transport request can indicate a pick-up location and a destination. The system can determine a plurality of candidate transport providers to service the respective transport request, in which the plurality of candidate transport providers can comprise at least one third-party AV. The system can determine a capability of the at least one third-party AV in servicing the respective transport request, and, based at least in part on the capability of the at least one third-party AV, select a transport provider from the plurality of transport providers to service the transport request.
Systems and methods for controlling an autonomous vehicle and the service selection for an autonomous vehicle are provided. In one example embodiment, a computing system can obtain data indicative of a first vehicle service assignment for an autonomous vehicle. The first vehicle service assignment can be associated with a first service entity and indicative of a first vehicle service. The computing system can determine that the autonomous vehicle is available to perform a second vehicle service concurrently with the first vehicle service. The computing system can obtain data indicative of a second vehicle service assignment for the autonomous vehicle. The second vehicle service assignment can be associated with a second service entity that is different than the first service entity and is indicative of the second vehicle service. The computing system can cause the autonomous vehicle to concurrently perform the first vehicle service with the second vehicle service.
A network computer system operates to generate synthetic messages based on service-specific information. The network computer system communicates with user devices, including requester devices and provider devices, to match service requests generated by the requester devices to respective service provider entities associated with the provider devices. For a given service request generated by a respective requester device, the network computer system determines service-specific information using device data communicated by at least one of the respective requester device and a respective provider device. The respective provider device is associated with a service provider entity that is matched to the given service request. The network computer system detects a trigger based on the service-specific information. In response to detecting the trigger, the network computer system generates, based on the service-specific information, a synthetic message from a first device to a second device selected from the respective requester device and the respective provider device.
Systems and methods for controlling an autonomous vehicle and the service selection for an autonomous vehicle are provided. In one example embodiment, a computing system can obtain data indicative of a plurality of plurality of service entities. The computing system can determine a first service entity of the plurality of service entities for which an autonomous vehicle is to perform a first vehicle service. The computing system can indicate that the autonomous vehicle is available to perform the first vehicle service for the first service entity. In some implementations, this indication can be done while the autonomous vehicle is already providing a vehicle service. The computing system can obtain data indicative of a vehicle service assignment associated with the first service entity and cause the vehicle to travel accordingly. In some implementations, the computing system can select a vehicle service assignment from among a plurality of different vehicle service assignments.
An image quality scorer machine accesses a candidate image to be analyzed for visual quality. The image quality scorer machine generates a visual quality score of the candidate image by first generating a prediction of a similarity score for the candidate image. The predicted similarly score of the candidate image may be generated by a process including inputting the candidate image into a neural network that has been trained to detect a set of image features in the candidate image and then to generate a corresponding predicted similarity score based on degrees to which the image features in the set are present in the candidate image. The image quality scorer machine derives the visual quality score based on the predicted similarity score outputted by the neural network. Accordingly, the image quality score machine may provide or store the generated visual quality score of candidate image for subsequent usage.
The housing of a lock assembly for securing a wheeled vehicle contains a cable which is wound around a cable reel within the housing. The cable reel rotates around a reel axis and has two ends. The first end of the cable is connected to the cable reel while the second end of the cable has a locking feature. A lock core has a receptacle configured to receive the locking feature at the end of the cable. An axis of the core is substantially parallel to the reel axis.
A mobile device mounting system includes two jaws. The first jaw is generally fixed in position to a wheeled vehicle. The second jaw is pivotably connected to the first jaw via a hinge. The second jaw can be positioned into a closed or open position relative to the first jaw. A biasing element is used to move the second jaw towards the closed position. A support element spans the first and second jaws and may be used to support the mobile device when the mobile device is placed in the mounting system.
B62J 11/00 - Supporting arrangements specially adapted for fastening specific devices to cycles, e.g. supports for attaching maps
F16M 13/02 - Other supports for positioning apparatus or articles; Means for steadying hand-held apparatus or articles for supporting on, or attaching to, an object, e.g. tree, gate, window-frame, cycle
B62J 99/00 - Subject matter not provided for in other groups of this subclass
92.
ROUTE COORDINATION AND NAVIGATION BASED ON USER PROXIMITY TO POINTS OF INTEREST
A network computing system can receive transport requests from user computing devices of requesting users of an on-demand carpool service. The system can further receive sensor data from the user computing devices of each carpool passenger of a vehicle. Based on the sensor data, the system can determine a relative position of each carpool passenger within the vehicle, and based on the relative position of each carpool passenger within the vehicle, the system can transmit route data to a transport provider device of the vehicle to rendezvous with a next carpool passenger at an upcoming pick-up location such that an open seat within the vehicle is adjacent to the next carpool passenger.
The present disclosure is directed to state-based autonomous-vehicle operations. In particular, the methods, devices, and systems of the present disclosure can: determine, based at least in part on one or more actions of a passenger associated with a trip of an autonomous vehicle, a current state of the trip from amongst a plurality of different predefined states of the trip; identify, based at least in part on the current state of the trip, one or more computing devices associated with the passenger; generate, based at least in part on the current state of the trip, data describing one or more interfaces for display by the computing device(s) associated with the passenger; and communicate, to the computing device(s) associated with the passenger, the data describing the interface(s) for display. The displays may in particular be a mobile phone and a screen installed in the vehicle.
B60W 50/14 - Means for informing the driver, warning the driver or prompting a driver intervention
B60W 50/00 - CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - Details of control systems for road vehicle drive control not related to the control of a particular sub-unit
A sensor assembly includes a first body that rotates a sensor component about an axis, and a second body coupled to the first body to form a separation gap. The separation gap extends radially inward from a gap inlet to a sealed barrier of the second body. The separation gap may be configured with a set of air guide structural features, to induce formation of eddies from air intake received through the gap inlet, as air from the air intake moves inward towards the sealed barrier.
F03D 9/32 - Wind motors specially adapted for installation in particular locations on moving objects, e.g. vehicles
B06B 3/00 - Processes or apparatus specially adapted for transmitting mechanical vibrations of infrasonic, sonic or ultrasonic frequency
G01S 3/00 - Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
G01S 7/00 - RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - Details of systems according to groups , ,
95.
SYSTEMS AND METHODS FOR ON-SITE RECOVERY OF AUTONOMOUS VEHICLES
Systems and methods for recovering an autonomous vehicle in a fleet of vehicles are provided. In one example embodiment, a computer-implemented method includes detecting an existence of an adverse condition associated with an autonomous vehicle in the fleet. The method includes determining in response to detecting the adverse condition, a recovery plan for the first autonomous vehicle based at least in part on one or more attributes associated with the adverse condition, the recovery plan including one or more actions to recover the first autonomous vehicle at a remote location. The method includes initiating the recovery plan to recover the first autonomous vehicle at the remote location.
Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system (e.g., of a vehicle) can generate a first communication associated with an autonomous vehicle. The computing system can provide the first communication to an application programming interface gateway that is remote from the autonomous vehicle. Another computing system can obtain, via an application programming interface gateway, the first communication associated with the autonomous vehicle. The other computing system can determine a first frontend interface of the application programming interface gateway based at least in part on the first communication associated with the autonomous vehicle. The computing system can provide, via the first frontend interface, the first communication associated with the autonomous vehicle to a first system client associated with the first frontend interface.
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
97.
SYSTEMS AND METHODS FOR IMPLEMENTING VEHICLE ASSIGNMENTS USING VEHICLE STATE INFORMATION
Systems and methods for managing a fleet of vehicles are provided. In one example embodiment, a computer-implemented method includes obtaining data representing vehicle state information associated with one or more vehicles among a fleet of vehicles at one or more times. The method includes predicting a future vehicle state associated with the one or more vehicles at one or more future times. The method includes scheduling a vehicle assignment in a predetermined set of vehicle assignments for a selected vehicle among the one or more vehicles before a first future time among the one or more future times. The method includes transmitting a command signal to a computing system associated with the selected vehicle based at least in part on the scheduled vehicle assignment.
Systems and methods for controlling an autonomous vehicle in response to vehicle instructions from a remote computing system are provided. In one example embodiment, a computer-implemented method includes controlling a first autonomous vehicle to provide a vehicle service, the first autonomous vehicle being associated with a first convoy that includes one or more second autonomous vehicles. The method includes receiving one or more communications from a remote computing system associated with a third-party entity, the one or more communications including one or more vehicle instructions. The method includes coordinating with the one or more second autonomous vehicles to determine one or more vehicle actions to perform in response to receiving the one or more vehicle instructions from the third-party entity. The method includes controlling the first autonomous vehicle to implement the one or more vehicle actions.
A multi-leg transport system receives a transport request and determines a number of transfer locations between the origin location and the destination. The system selects a first provider to transport the user from the origin location to a transfer location and remotely monitors the position of the user as the user travels to the transfer location. In response to determining that the travel time to the transfer location is within a threshold, the system selects a second provider to transport the user from the transfer location to either the next transfer location or the destination for the transport request.
The present disclosure provides systems and methods for communicating between control systems via hydraulic fluid. In one example embodiment, a computer-implemented method includes operating a first pressure regulating device associated with a first control system to regulate a fluid pressure of hydraulic fluid being supplied through a hydraulic line, the first pressure regulating device being in fluid communication with a hydraulically actuated component via the hydraulic line. The method includes controlling the operation of the first pressure regulating device to generate a fluid-pressure based signal within the hydraulic line, the signal providing an indication of an operational status of at least one of the first control system or the hydraulically actuated component. The method includes detecting pressure changes within the hydraulic line associated with the signal to allow a second control system to monitor the operational status of the first control system and/or the hydraulically actuated component.
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