Faraday & Future Inc.

Gentex Corporation

Oliver Max Jeromin

Aziz Umit Batur

Paul Alan Theodosis

Hong S Bae

Michael Venegas

David M Falb

Jeremy A Schut

Evan Roger Fischer

Joseph S Stam

Eric Jon Walstra

Gregory S Bush

David J Wright

Sergio E Murillo Amaya

Sowmya Gade

Steven M Currie

Timothy S Cornell

A vehicle control system for moving a vehicle to a target location is disclosed. According to examples of the disclosure, a camera captures one or more images of a known object corresponding to the target location. An on-board computer having stored thereon information about the known object can process the one or more images to determine vehicle location with respect to the known object. The system can use the vehicle's determined location and a feedback controller to move the vehicle to the target location.

Camera based auto drive auto charge

A system that performs a method is disclosed. Image data from a first camera mounted on a vehicle is received, the vehicle including a first element configured to open into a first space external to the vehicle, and the image data indicative of motion of a first object during a first time period, the first object located outside of the first space. Whether the motion of the first object during the first time period indicates that the first object will interfere with operation of the first element during a second time period, after the first time period, is determined. In accordance with a determination that the motion of the first object indicates that the first object will interfere with the operation of the first element during the second time period, an action that avoids the interference is performed.

System and method for tracking moving objects to avoid interference with vehicular door operations

A system that performs a method is disclosed. The system receives information about a map, which includes information about one or more zones in the map. While navigating a vehicle along a driving path within the map, the system receives information about the location of the vehicle in the map. The system estimates an error bounds of the location of the vehicle, and determines in which of the one or more zones in the map the error bounds is located within. In response to the determination: in accordance with a determination that the error bounds is located within a first zone in the map, the system causes the vehicle to perform a driving operation. In accordance with a determination that the error bounds is located within a second zone of the one or more zones in the map, the system causes the vehicle to perform a different driving operation.

Using position estimate error bounds for safe vehicle navigation

A method for autonomously controlling a vehicle is disclosed. In some examples, a vehicle can maneuver out of a parking space in an autonomous and unmanned operation. While parking, the vehicle can capture first one or more images of its surroundings and store the images in a memory included in the vehicle. Upon starting up, the vehicle can capture second one or more images of its surroundings and compare them to the first one or more images to determine if there is an object, person, or animal proximate to the vehicle, for example. In some examples, in accordance with a determination that there is no object, person, or vehicle present that was not present during parking, the vehicle can autonomously move from the parking space with or without a user present in the vehicle.

Using cameras for detecting objects near a vehicle

A system is disclosed. The system includes one or more processors, and a memory including instructions, which when executed by the one or more processors, cause the one or more processors to perform a method. The method includes receiving first image data from a first image sensor mounted on a vehicle and second image data from a second image sensor mounted on the vehicle, the vehicle including an element configured to open into a space external to the vehicle; generating a depth map from a comparison of the first image data and the second image data, the depth map including an object; in accordance with a determination that the object, in the depth map, is within the space into which the element is configured to open, determining that the object will interfere with opening of the element into the space; and in accordance with a determination that the object, in the depth map, is not within the space into which the element is configured to open, determining that the object will not interfere with opening of the element into the space.

Stereo camera-based detection of objects proximate to a vehicle

The present invention is generally directed to optical data processing or objects in proximity to an optical sensor or camera, such as a camera mounted on a vehicles. Image data is received from a camera mounted on a vehicle, the image data indicative of a motion of the camera with respect to a detected object within a proximity of the camera or the vehicle on which the camera may be mounted. An optical flow of the object in the image data is determined, and a height of the object is determined based on the determined optical flow.

System and method for camera-based detection of object heights proximate to a vehicle

A system for calculating a visibility range from a vehicle is disclosed. The system comprises a high dynamic range image sensor system comprising a pixel array including a plurality of pixels. The image sensor further includes readout circuitry in electrical communication with each pixel of the pixel array. The readout circuitry is operable to readout a distinct pixel value corresponding to one of a plurality of exposure times for each pixel in a single image frame. The system further comprises at least one processor in communication with the readout circuitry. The processor is operable to calculate a visibility range from the vehicle based on a plurality of image processing algorithms.

System and method for visibility range detection

Camera-based autonomous parking is disclosed. An autonomous parking procedure can include detecting parking lines in images captured by a camera on a vehicle. The vehicle can be localized with respect to the parking lines based on location data for the vehicle from a GPS receiver and a location determination for the vehicle based on detected ends of the parking lines. The vehicle can further determine an occupancy state of one or more parking spaces formed by the two or more parking lines using a range sensor on the vehicle and select an empty space. A region of interest including the selected space can be identified and one or more parking lines of the selected space can be detected in an image of the region of interest. The vehicle can autonomously move to reduce errors between the location of the vehicle and the final parking position within the selected space.

Methods and systems for camera-based autonomous parking

An imaging system and method for fog detection are disclosed herein. An imager is configured to image a scene external and forward of a controlled vehicle and to generate image data corresponding to the acquired images. A controller is configured to receive and analyze the image data. When exterior lights of the controlled vehicle are operated in a low beam state, the controller is able to detect light sources of interest in the image data, determine if each light source of interest is a foggy light or a clear light, and generate a first signal if a fog entry condition is satisfied.

Imaging system and method for fog detection

An image acquisition and processing system includes an image sensor and one or more processors that are configured to receive at least a portion of at least one image from the image sensor. The dynamic aim of the image sensor is configured as a function of at least one feature extracted from at least a portion of an image. To accomplish the task, the system utilizes a series of adaptive thresholds used in parallel comparators to determine whether or not a pixel in a given image scene falls on the edge of a given lane line on a road. The location of the lane lines are then used to determine the scene vanishing point, which ideally will be co-located at the optical scene center. If they are not in agreement, the pixel data set being processed can be adjusted to accommodate for any disagreement.

Growing community of inventors

Torrance, CA, United States of America

Oliver Max Jeromin