Abstract: Methods and systems for assisting a vehicle to park using mixed-domain image data. Image-domain data is generated based on raw image data received from a plurality of cameras mounted on a vehicle. A bird's-eye-view (BEV) image is generated based on the raw image data. BEV-domain data associated with the BEV image is generated, which includes data associated with parking landmarks in the parking zone. A tri-perspective view (TPV) and associated data can be generated. A computing system localizes the vehicle within the parking zone based on the BEV-domain data, the image-domain data, and the TPV-domain data to generate localization data. The computing system performs mapping of the parking zone based on all three image-domain data and the localization data. A motion sensor such as an inertial measurement unit (IMU) can generate data that is used to compensate the various domain data.

Abstract: Methods and systems for assisting a vehicle to park using mixed-domain image data. Image-domain data is generated based on raw image data received from a plurality of cameras mounted on a vehicle. The raw image data is associated with a parking zone outside the vehicle, and the image-domain data is generated by a feature-detection machine learning model. A bird's-eye-view (BEV) image is generated based on the raw image data, wherein the BEV image is a projected image of the parking zone. BEV-domain data associated with the BEV image is generated. The BEV-domain data includes data associated with parking landmarks in the parking zone. A computing system localizes the vehicle within the parking zone based on the BEV-domain data and the image-domain data to generate localization data. The computing system performs mapping of the parking zone based on the BEV-domain data, the image-domain data, and the localization data.

Abstract: A method that includes obtaining a first image from a first camera disposed on a vehicle and generating a birds-eye view (BEV) image using the first image. The method further includes processing, with a machine-learned model, the BEV image to produce parking slot prediction data. The parking slot prediction data includes a first center coordinate for a first available parking slot, a first parking slot confidence, and a first corner displacement data. The first corner displacement data includes a first relative coordinate pair that locates a first corner relative to the first center coordinate and a second relative coordinate pair that locates a second corner relative to the first center coordinate. The method further includes determining a first location of the first available parking slot using the parking slot prediction data and parking the vehicle in the first available parking slot when the first parking slot confidence meets a threshold.

Abstract: A method that includes obtaining a first image from a first camera disposed on a vehicle and generating a birds-eye view (BEV) image using the first image. The method further includes processing, with a machine-learned model, the BEV image to produce parking slot prediction data. The parking slot prediction data includes a first center coordinate for a first available parking slot, a first parking slot confidence, and a first corner displacement data. The first corner displacement data includes a first relative coordinate pair that locates a first corner relative to the first center coordinate and a second relative coordinate pair that locates a second corner relative to the first center coordinate. The method further includes determining a first location of the first available parking slot using the parking slot prediction data and parking the vehicle in the first available parking slot when the first parking slot confidence meets a threshold.

Abstract: The subject matter of the invention is a method for detecting faults related to wheels of a motor vehicle in a driving situation, comprising: —a step (S1) of automatically determining a first series of corrective steering wheel angles applied successively to force the vehicle to follow a path parallel to a first rectilinear portion of a traffic lane; —a step (S2) of automatically detecting, from the corrective steering wheel angles of the first series, the presence of a fault affecting a pair of steering wheels of the vehicle; and, optionally: —a step (S3) of estimating a type of fault associated with the detected fault, a step (S4) of identifying the steering wheel of the pair of wheels affected by the fault; and —a step (S5) of generating a warning message for the attention of the driver of the motor vehicle, the message including the estimated type of fault and the wheel identified as having the fault.

Abstract: The subject matter of the invention is a method for detecting faults related to wheels of a motor vehicle in a driving situation, comprising: a step (S1) of automatically determining a first series of corrective steering wheel angles applied successively to force the vehicle to follow a path parallel to a first rectilinear portion of a traffic lane; a step (S2) of automatically detecting, from the corrective steering wheel angles of the first series, the presence of a fault affecting a pair of steering wheels of the vehicle; and, optionally: a step (S3) of estimating a type of fault associated with the detected fault, a step (S4) of identifying the steering wheel of the pair of wheels affected by the fault; and a step (S5) of generating a warning message for the attention of the driver of the motor vehicle, the message including the estimated type of fault and the wheel identified as having the fault.