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    Propagation of alerts regarding traffic events
    52.
    发明授权
    Propagation of alerts regarding traffic events 有权

    公开(公告)号：US10403140B2

    公开(公告)日：2019-09-03

    申请号：US16087181

    申请日：2016-03-21

    Applicant: Ford Global Technologies, LLC

    Inventor： Harpreetsingh Banvait ,  Jinesh J. Jain ,  Surjya Sarathi Ray

    IPC: G08G1/0967 ,  H04W4/46 ,  G08G1/16 ,  B60W30/12 ,  G08G1/01

    Abstract: In response to detecting a traffic event such as a motorcycle lane splitting or an accident, a vehicle broadcasts a notification over a V2V communication channel. Traffic events may be detected using sensor systems of the vehicle or in response to messages reporting the event. Notifications may be received from the vehicle over a cellular communication channel. Roadside infrastructure, such as DSRC or cellular communication installations receive the notification and may rebroadcast it to adjacent vehicles. A DSRC installation may broadcast the message by way of a cellular communication installation and vice versa. The vehicle may provide a cellular notification by way of a driver's mobile device connected to a controller of the vehicle.

    Detecting available parking spaces
    53.
    发明授权
    Detecting available parking spaces 有权

    公开(公告)号：US10304335B2

    公开(公告)日：2019-05-28

    申请号：US15096803

    申请日：2016-04-12

    Applicant: Ford Global Technologies, LLC

    Inventor： Jinesh J Jain ,  Sneha Kadetotad ,  Harpreetsingh Banvait ,  Vidya Nariyambut Murali ,  Peter Gyumyeong Joh

    IPC: G08G1/14 ,  G01S7/41 ,  G01S13/91 ,  G01S13/93 ,  G06K9/00 ,  G01S7/295 ,  G01S13/90

    Abstract: The present invention extends to methods, systems, and computer program products for detecting available parking spaces in a parking environment. Radar systems are utilized to gather data about a parking lot environment. The radar data is provided to a neural network model as an input. Algorithms employing neural networks can be trained to recognize parked vehicles and conflicting data regarding debris, shopping carts, street lamps, traffic signs, pedestrians, etc. The neural network model processes the radar data to estimate parking space boundaries and to approximate the parking space boundaries as splines. The neural network model outputs spline estimations to a vehicle computer system. The vehicle computer system utilizes the spline estimates to detect available parking spaces. The spline estimates are updated as the vehicle navigates the parking environment.

    Collision avoidance using auditory data
    56.
    发明授权
    Collision avoidance using auditory data 有权

    公开(公告)号：US09996080B2

    公开(公告)日：2018-06-12

    申请号：US15054602

    申请日：2016-02-26

    Applicant: Ford Global Technologies, LLC

    Inventor： Harpreetsingh Banvait ,  Jinesh J Jain ,  Kyu Jeong Han

    IPC: G05D1/00 ,  G05D1/02

    CPC classification number: G05D1/0088 ,  G01S2013/9367 ,  G05D1/0214 ,  G05D1/0221 ,  G05D1/0246 ,  G05D1/0255 ,  G05D1/0274 ,  G05D2201/0213

    Abstract: A controller for an autonomous vehicle receives audio signals from one or more microphones. The audio signals are input to a machine learning model that classifies the source of the audio features. For example, features may be classified as originating from a vehicle. A direction to a source of the audio features is determined based on relative delays of the audio features in signals from multiple microphones. Where audio features are classified with an above-threshold confidence as originating from a vehicle, collision avoidance is performed with respect to the direction to the source of the audio features. The direction to the source of the audio features may be correlated with vehicle images and/or map data to increase a confidence score that the source of the audio features is a parked vehicle with its engine running. Collision avoidance may then be performed with potential paths of the parked vehicle.

    Using Virtual Data To Test And Train Parking Space Detection Systems
    59.
    发明申请
    Using Virtual Data To Test And Train Parking Space Detection Systems 审中-公开

    公开(公告)号：US20180025640A1

    公开(公告)日：2018-01-25

    申请号：US15214269

    申请日：2016-07-19

    Applicant: Ford Global Technologies, LLC

    Inventor： Ashley Elizabeth Micks ,  Jinesh J. Jain ,  Vidya Nariyambut Murali ,  Harpreetsingh Banvait ,  Sneha Kadetotad ,  Peter Gyumyeong Joh

    IPC: G08G1/14 ,  G06N99/00 ,  G06F17/50

    Abstract: The present invention extends to methods, systems, and computer program products for using virtual data to test and train parking space detection systems. Aspects of the invention integrate a virtual driving environment with sensor models (e.g., of a radar system) to provide virtual radar data in relatively large quantities in a relatively short amount of time. The sensor models perceive values for relevant parameters of a training data set. Relevant parameters can be randomized in the recorded data to ensure a diverse training data set with minimal bias. Since the driving environment is virtualized, the training data set can be generated alongside ground truth data. The ground truth data is used to annotate true locations, which are used to train a parking space classification algorithms to detect the free space boundaries.

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