Abstract:
A system and method for providing a map via a cloud-based system is disclosed. The method includes requesting, by a controller of an autonomous vehicle, a map data from a cloud-based server. The map data is stored on the cloud-based server. The method also includes receiving map data from the cloud-based server. The method also includes autonomously navigating the autonomous vehicle based on the received map data.
Abstract:
Methods and systems for communicating data between a network and devices of a vehicle are provided. A method includes: determining, by a processor, a value associated with a round trip time based on vehicle information; adjusting, by the processor, a size of a window used in communication with the network based on the value; and communicating data at least one of to and from the network based on the size of the window.
Abstract:
Systems and method are provided for implementing selective crowd sourcing. In one embodiment, a processor-implemented method for obtaining data from vehicles includes calculating a greedy parameter value for each of a plurality of vehicles in a geographical area; selecting no more than a predetermined number of the plurality of vehicles having a greedy parameter value in a greedy parameter threshold range; instructing the selected vehicles to transmit data while in the geographical area; and receiving the data from the selected vehicles. In another embodiment, a vehicle including a crowd sourcing selection module is provided. The crowd sourcing selection module is configured to retrieve consensus information from a central repository; calculate greedy parameter information regarding the vehicle using the consensus information; and determine whether to transmit an event observation to the central repository based on the greedy parameter information.
Abstract:
A crowd sensing system includes a central entity and remote entities. The remote entities receive queries from the central entity and transmit data to the central entity in response to the query. The sample data obtained from the queried remote entity is analyzed and an average value for the sample data is determined for a current time interval. The central entity determines whether a difference between the average values for the current time interval and a previous time interval is greater than a predetermined threshold. The central entity increases the number of entities in response to the difference being greater than the predetermined threshold, and decreases the respective number of remote entities sampled in response to the difference being less than the predetermined threshold. The central entity queries a number of remote entities in the plurality of regions equal to the adjusted number of samples identified by the central entity.
Abstract:
A positioning method for a mobile platform includes acquiring GPS position data associated with the mobile platform from a plurality of GPS satellites observable by the mobile platform. A set of wireless range measurements associated with the mobile platform and a plurality of wireless access points in communication with the mobile platform are received (e.g., via time-of-flight measurements). Wireless position data associated with the plurality of wireless access points is received from a server communicatively coupled to the mobile platform over a network. A corrected position of the mobile platform based on the wireless position data, the wireless range measurements, and the GPS position data.
Abstract:
A vehicle system virtualizing add-on device hardware for a vehicle application. The system includes a computer-readable storage device comprising a client application, middleware components, kernel-space components, and a vehicle application. The client application communicates with an add-on-device server application for virtualizing the add-on-device hardware component at the vehicle. The middleware, in various embodiments, includes an emulated system-call application-program-interface module that receives add-on-device-hardware data from the client application, sends the data to the kernel-space components after processing, and receives the data having been processed at the kernel space. The middleware includes a frameworks-and-abstraction module that receives add-on-device-hardware data, having been processed at the kernel space and the emulated system-call-application-program-interface module and after processing sends the data for use at the vehicle application. In some implementations the middleware and kernel space includes universal-serial-bus components configured to emulate analogous components of the add-on device.
Abstract:
A method of determining ride share compatibility. Vehicle data acquisition devices are employed to collect user attribute information relating to a travel route and locations traveled by the operator. The attribute information includes regularity data, frequency data, and duration data. A regression analysis is applied by a processor for using the regularity data, the frequency data, and the duration data, for identifying an importance probability of each of the locations visited by the operator. A match is determined between the operator and a potential travel partner traveling to locations in proximity to the locations traveled by the operator.
Abstract:
A system and method for sharing information from a vehicle for comparison to information from other vehicles. The system and method include collecting vehicle trace data and sharing the vehicle trace data using a communications network such that the vehicle trace data is compared and ranked relative to the vehicle trace data of other vehicles.
Abstract:
A system and method for using data that is external to a vehicle in vehicular applications. The system and method include determining data that is external to the vehicle is available for use, comparing the external data to data that is available from a vehicle system, and determining whether the external data has a higher utility function compared to data that is available from a vehicle system. The system and method further include using the external data to enhance a vehicular application if the external data has a higher utility function.
Abstract:
A method and system for recommending applications to users of in-vehicle infotainment systems are disclosed. Application rating data from many road vehicle infotainment system users are collected on a central server, including both explicit ratings and implicit ratings. Implicit ratings may be calculated based on application usage data. The user/application rating data is filtered for relevance, and then analyzed to determine inferred ratings for user/application relationships where no rating exists. The inferred ratings are calculated using both a user-driven consensus rating calculation and an application-driven consensus rating calculation. The inferred ratings, along with optional cyberspace-based external inputs, are used to synthesize application recommendations for users. The synthesized recommendations for application consideration are provided to the appropriate user via downloading from the central server to the infotainment system in the user's vehicle.