System and method for a vehicle proximity alert

    公开(公告)号:US12051331B2

    公开(公告)日:2024-07-30

    申请号:US17848658

    申请日:2022-06-24

    CPC classification number: G08G1/161

    Abstract: A method and system for a target vehicle that includes an extra-vehicle communication system, a passenger cabin including an interior audio system and a visual display, and a controller is described. The controller is in communication with the extra-vehicle communication system, and operably connected to the interior audio system and the visual display. The controller includes algorithmic code that is executable to receive a proximity alert from a second vehicle via the extra-vehicle communication system, determine a location vector between the second vehicle and the target vehicle based upon the proximity alert, and control the interior audio system and the visual display to generate an alarm in response to the proximity alert, wherein the alarm generated by the interior audio system and the visual display is directionally controlled based upon the location vector. The proximity alert may be generated by an operator, or by a spatial monitoring system.

    METHOD AND APPARATUS FOR DETERMINING DRIVING RISKS BY USING DEEP LEARNING ALGORITHMS

    公开(公告)号:US20240212361A1

    公开(公告)日:2024-06-27

    申请号:US18241210

    申请日:2023-08-31

    Inventor: Sougjun KANG

    Abstract: An apparatus and method for determining driving risks of a driver using deep learning algorithms and a vehicle including the same are provided. The apparatus comprises a processor, a network interface, a memory, and a computer program loaded to the memory and executed by the processor, wherein the processor is configured to receive image data and CAN data obtained by a vehicle equipped with a lidar sensor or a camera sensor while the vehicle is driving, input the obtained image data and CAN data to a first deep learning algorithm trained through pre-stored image data to output image features related to driving risks of a driver driving the vehicle, output image features related to the driver's driving risk by the first deep learning algorithm, and capture a first image corresponding to the output image features and transmit the captured first image to a connect program.

    PREDICTION-BASED SYSTEM AND METHOD FOR TRAJECTORY PLANNING OF AUTONOMOUS VEHICLES

    公开(公告)号:US20240168478A1

    公开(公告)日:2024-05-23

    申请号:US18431194

    申请日:2024-02-02

    Applicant: TuSimple, Inc.

    Abstract: A prediction-based system and method for trajectory planning of autonomous vehicles is configured to: receive data from a training data collection system, the training data including perception data and context data corresponding to human driving behaviors; perform a training phase for training a trajectory prediction module using the training data; receive perception data associated with a host vehicle; and perform an operational phase for extracting host vehicle feature data and proximate vehicle context data from the perception data, generating a proposed trajectory for the host vehicle, using the trained trajectory prediction module to generate predicted trajectories for each of one or more proximate vehicles near the host vehicle based on the proposed host vehicle trajectory, determining if the proposed trajectory for the host vehicle will conflict with any of the predicted trajectories of the proximate vehicles, and modifying the proposed trajectory for the host vehicle until conflicts are eliminated.

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