Calculating traffic flow changes due to traffic events

    公开(公告)号:US12254766B2

    公开(公告)日:2025-03-18

    申请号:US17198893

    申请日:2021-03-11

    Abstract: A method for calculating traffic flow changes includes detecting a traffic event. The method further includes determining an affected area of the traffic event and determining an investigation area based on the affected area. The method further includes selecting at least one vehicle located within the investigation area and calculating a change in traffic flow due to the traffic event based on a comparison of a predicted traffic flow with a current traffic flow, wherein the current traffic flow is based on information received from the at least one vehicle. The method further includes updating the affected area based on the change in traffic flow and calculating an updated change in traffic flow based on the updated affected area when the updated affected area is larger than a predetermined threshold area.

    Grouping of moving objects
    4.
    发明授权

    公开(公告)号:US11200798B2

    公开(公告)日:2021-12-14

    申请号:US16780997

    申请日:2020-02-04

    Abstract: The present invention may be a method, a computer system, and a computer program product for grouping a plurality moving objects capable of communicating with a server computer. The server computer performs the method comprising: predicting travel routes of the plurality of moving objects, using current traveling data and travel history data; grouping the plurality of moving objects into at least one group, using the predicted travel routes; determining a representative moving object in each group; and communicating with the representative moving object.

    SUPPLEMENTING LEARNING DATA TO DETERMINE MOST PROBABLE PATH

    公开(公告)号:US20200326198A1

    公开(公告)日:2020-10-15

    申请号:US16379766

    申请日:2019-04-09

    Abstract: A method, computer system, and a computer program product for supplementing learning data to determine a Most Probable Path (MPP) for a user driver is provided. The present invention may include determining a change associated with a set of map data. The present invention may then include extracting a set of trajectory data in response to the determined change associated with the set of map data. The present invention may also include performing a rerouting calculation for the extracted set of trajectory data, wherein the performed rerouting calculation generates a rerouting result, wherein the generated rerouting result is added to a set of learning data in a learning data database. The present invention may further include adding one or more trajectory patterns to the learning data based on an increase frequency after the determined change associated with the set of map data.

    EVENT DETECTION WITH CONVERSATION
    7.
    发明申请

    公开(公告)号:US20200151257A1

    公开(公告)日:2020-05-14

    申请号:US16190535

    申请日:2018-11-14

    Abstract: A method, system, and computer program product are provided. At least some received event candidate information concerning a possible event is stored as an event candidate in a database. A dialogue is generated with an occupant of a vehicle located in a vicinity of the possible event to obtain and store information to resolve any insufficiency or ambiguity regarding the event candidate in the database. When the information stored in the database regarding the event candidate is determined to be sufficient and unambiguous the event candidate is made into an event in the database. The event is reported to at least one vehicle approaching a location corresponding to the event.

    SOCIAL MEDIA SEARCH ASSIST
    9.
    发明申请

    公开(公告)号:US20170161272A1

    公开(公告)日:2017-06-08

    申请号:US14962357

    申请日:2015-12-08

    CPC classification number: G06F16/435 G06F16/248

    Abstract: A computer identifies social media displayed by a social media platform. The computer determines that a user has viewed the social media and saves the viewed social media in associated with the view date/time. The computer identifies and saves the interests associated with the user at the date/time the social media post was viewed by referencing the user profile and recent social media activity of both the user and associated users. The computer receives a social media query and cluster period from the user in regards to a previously viewed social media post. The computer displays the viewed social media that matches the search query as well as the interests associated with the user during each cluster period in which a matching social media post was viewed.

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