SYSTEM TO PREDICT VEHICLE PARKING BUNCHING
    2.
    发明公开

    公开(公告)号:US20240203255A1

    公开(公告)日:2024-06-20

    申请号:US18085398

    申请日:2022-12-20

    CPC classification number: G08G1/146 G01C21/3685 G01C21/3691

    Abstract: A system, a method and a computer program product are provided to predict vehicle parking bunching in a geographic region. For example, the system is configured to obtain a plurality of contextual features and/or a plurality of sensor data related to parking information in the geographic region. The system is configured to predict a vehicle parking bunching based on a vehicle unparking threshold, a vehicle separation distance cluster threshold and/or unparking vehicle information. The system may also be configured to alert a vehicle of the vehicle parking bunching with a vehicle parking bunching notification.

    APPARATUS AND METHODS FOR PREDICTING EVENTS IN WHICH DRIVERS FAIL TO SEE CURBS

    公开(公告)号:US20230360532A1

    公开(公告)日:2023-11-09

    申请号:US17735922

    申请日:2022-05-03

    CPC classification number: G08G1/165

    Abstract: An apparatus, method and computer program product are provided for predicting events in which drivers fail to see curbs while the drivers are maneuvering vehicles. In one example, the apparatus receives vehicle attribute data associated with a first vehicle, map data indicating one or more attributes of a road portion including a first curb, and sensor data indicating an orientation of a first driver within the first vehicle. The apparatus causes a machine learning model to render an output as a function of the vehicle attribute data, the map data, and the sensor data. The output indicates a likelihood of which the first driver will not be able to see the first curb at the road portion when the first driver is maneuvering the first vehicle. The machine learning model is trained to predict the output based on historical data indicating events in which second drivers maneuvered second vehicles to encounter the first curb or one or more second curbs.

    APPARATUS AND METHODS FOR PREDICTING TIRE TEMPERATURE LEVELS

    公开(公告)号:US20240174032A1

    公开(公告)日:2024-05-30

    申请号:US18071258

    申请日:2022-11-29

    CPC classification number: B60C23/0476 B60C23/0481 G01C21/3453

    Abstract: An apparatus, method and computer program product are provided for predicting tire temperature levels. In one example, the apparatus receives input data indicating a target route for a target vehicle, attributes associated with the target vehicle, and attributes of the target route and causes a machine learning model to generate output data as a function of the input data. The output data indicate prediction of tire temperature levels of the target vehicle during a period in which the target vehicle traverses the target route. The machine learning model is trained to generate the output data as a function of the input data based on training data indicating events in which vehicles traversed routes. Specifically, the training data include tire temperature levels of the vehicles, vehicle data associated with the vehicles, map data associated with the routes, and environmental data associated with the routes.

    METHOD AND APPARATUS FOR DETERMINING APPOINTMENT ATTENDANCE PROBABILITY

    公开(公告)号:US20240037510A1

    公开(公告)日:2024-02-01

    申请号:US17874612

    申请日:2022-07-27

    CPC classification number: G06Q10/1095 G01C21/36

    Abstract: A method, apparatus, and user interface for determining appointment attendance probability comprising obtaining an indication of least a first location and second location of an end user; wherein the first location and second location are obtained at a predefined time interval, obtaining end user driving profile data, obtaining end user appointment data, determining appointment attendance probability based, at least in part, on the obtained first location, second location, end user appointment data, and end user driving profile data, and updating at least one database with the determined appointment attendance probability.

    METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR DETERMINING FAMILIARITY OF A PERSON WITHIN A GEOGRAPHIC REGION

    公开(公告)号:US20220333943A1

    公开(公告)日:2022-10-20

    申请号:US17301924

    申请日:2021-04-19

    Abstract: Provided herein is a method for determining the familiarity of a person with a geographic area based on their mobility data compared against baseline mobility data, and leveraging the familiarity to inform those less familiar and to inform travel within the geographic area. Methods may include: receiving probe data from a plurality of first probe apparatuses within a geographic region; determining, from the probe data, a baseline mobility model; receiving probe data from a second probe apparatus within the geographic region; determining a second mobility model of the second probe apparatus; determining, based at least in part on the baseline mobility model, a mobility efficiency of the second mobility model; and providing, to a user of the second probe apparatus, instructions relating to mobility to improve mobility efficiency of the user of the second probe apparatus.

    METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR ROAD NOISE MAPPING

    公开(公告)号:US20210166719A1

    公开(公告)日:2021-06-03

    申请号:US16699907

    申请日:2019-12-02

    Abstract: A method, apparatus, and computer program product are provided for encoding audio events as geo-referenced audio events for use in location establishment. Methods may include: receiving first audio data from a first sensor; identifying, within the first audio data, a first audio event, where the first audio event satisfies at least one predefined criteria; identifying a location corresponding to the first audio event; encoding the first audio event in a database to correspond to the location; receiving second audio data from a second sensor; identifying, within the second audio data, a second audio event; correlating the second audio event with the first audio event; and providing the location in response to the second audio data. The at least one criteria may include a statistically significant change in amplitude in the audio data.

    METHOD, APPARATUS, AND COMPUTER PROGRAM PRODUCT FOR ROAD NOISE MAPPING

    公开(公告)号:US20210164786A1

    公开(公告)日:2021-06-03

    申请号:US16699921

    申请日:2019-12-02

    Abstract: A method, apparatus, and computer program product are provided for encoding audio events as geo-referenced audio events for use in location establishment. Methods may include: receiving first audio data from a first sensor; establishing a baseline frequency profile; identifying, within the first audio data, a first audio event, where the first audio event satisfies at least one predefined criteria relative to the baseline frequency profile; identify a location corresponding to the first audio event; encoding the first audio event in a database to correspond to the location; receiving second audio data from a second sensor; identifying, within the second audio data, a second audio event; correlating the second audio event with the first audio event; and providing the location in response to the second audio data. The at least one criteria may include a statistically significant change in a prominent frequency in the audio data.

    APPARATUS AND METHODS DETERMINING A NEWLY ESTABLISHED VEHICLE-RELATED RULE WITHIN AN AREA

    公开(公告)号:US20240233535A1

    公开(公告)日:2024-07-11

    申请号:US18094843

    申请日:2023-01-09

    CPC classification number: G08G1/096791 G08G1/0112 G08G1/0129 G08G1/0141

    Abstract: An apparatus, method and computer program product are provided for determining a newly established vehicle-related rule within an area. In one example, the apparatus receives sensor data indicating attributes of an area for a first period. The attributes indicate a number of vehicle-related tickets issued within the area, a parking orientation of each vehicle within the area, or a combination thereof. The apparatus compares the sensor data to historical data associated with the area. The historical data indicate the attributes of the area for one or more second periods preceding the first period. Based on comparison of the sensor data and the historical data, the apparatus determines a likelihood of a vehicle-related rule established for the area, where the vehicle-related rule did not exist during the one or more second periods. The apparatus causes a notification indicating the likelihood at a user interface.

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