Abstract: A system and method for locating a trailer coupler on a trailer to assist with the coupling of the trailer coupler to a vehicle hitch on a vehicle. The system includes a human-machine interface, a camera, a global positioning system, a remote computing system, a vehicle-to-infrastructure communication network, controllers, a memory, sensors, and a trailer coupler labeling application. The trailer coupler labeling application includes: sensing at least one of a hitched state and an unhitched state of the trailer coupler, capturing an optical data with the camera when the vehicle hitch is in the hitched and unhitched state, determining a distance of the trailer coupler relative to the camera when the vehicle hitch is in the hitched state, identifying the location of the trailer coupler on an image defined by the captured data and creating a label on the image of the trailer coupler.

Abstract: A method for cross-technology radiofrequency interference mitigation includes detecting an RF device that is within a predetermined distance from a vehicle. The vehicle includes a plurality of wireless communication chipsets, each of the plurality of wireless communication chipsets is configured to wirelessly transmit and receive data. The method further includes determining that signals transmitted by the RF device is causing radiofrequency interference to signals transmitted by the plurality of wireless communication chipsets of the vehicle. Further, method includes commanding at least one of the plurality of wireless communication chipsets or the RF device to perform a control action to minimize the radiofrequency interference in response to determining that the that the signals transmitted by the RF device is causing radiofrequency interference to signals transmitted by the plurality of wireless communication chipsets of the vehicle.

Abstract: A system and method for locating a trailer coupler on a trailer to assist with the coupling of the trailer coupler to a vehicle hitch on a vehicle. The system includes a human-machine interface, a camera, a global positioning system, a remote computing system, a vehicle-to-infrastructure communication network, controllers, a memory, sensors, and a trailer coupler labeling application. The trailer coupler labeling application includes: sensing at least one of a hitched state and an unhitched state of the trailer coupler, capturing an optical data with the camera when the vehicle hitch is in the hitched and unhitched state, determining a distance of the trailer coupler relative to the camera when the vehicle hitch is in the hitched state, identifying the location of the trailer coupler on an image defined by the captured data and creating a label on the image of the trailer coupler.

Abstract: A system for identifying road defects within a roadway ahead of a moving vehicle, includes at least one camera in communication with a system controller and adapted to capture a plurality of time sequential images of the roadway ahead of the moving vehicle, and at least one motion sensor in communication with the system controller and adapted to detect when the vehicle encounters a road defect, the system controller adapted to correlate the road defect with at least one of the plurality of time sequential images of the roadway, analyze, using a computer vision algorithm, the at least one of the plurality of time sequential images, identify, with the computer vision algorithm, the road defect within the at least one of the plurality of time sequential images, and label the identified road defect within the at least one of the plurality of time sequential images.

Abstract: A method of determining the position of a vehicle includes generating a vehicle-based point cloud of objects in proximity to the vehicle, referenced to a vehicle-based coordinate system. The method also includes receiving an infrastructure-based point cloud, referenced to a global coordinate system, of objects detected by a camera mounted at a fixed location external to the vehicle, and registering the vehicle-based point cloud with the infrastructure-based point cloud to determine the vehicle position in the global coordinate system.

Abstract: A system to locate seat controls and belt buckles includes a vehicle having at least one seat. A seat belt system is provided with the at least one seat having a seat belt, a belt latch and a seat belt buckle. A haptic device is provided with the seat belt system, the haptic device generating a haptic signal.

Abstract: A system for activating a voice assistant of a vehicle includes a microphone, a first wireless module, a second wireless module, and a controller in electrical communication with the microphone, the first wireless module, and the second wireless module. The controller is programmed to transmit a plurality of original training signals on a plurality of subcarriers using the first wireless module. The controller is further programmed to receive a plurality of propagated training signals using the second wireless module. The controller is further programmed to determine a deviation between the plurality of original training signals and the plurality of propagated training signals. The controller is further programmed to identify a motion marker based at least in part on the deviation. The controller is further programmed to activate the voice assistant of the vehicle to receive a voice command using the microphone based at least in part on the motion marker.

Abstract: A system for providing information about a vehicle involved in a collision includes a sensing device affixed to the vehicle. The sensing device includes a sensor module configured to perform measurements of one or more conditions of the vehicle, an antenna module configured to transmit and receive radio-frequency (RF) signals, a power module configured to provide power to the sensing device, and a sensing device controller. The sensing device controller is in electrical communication with the sensor module, the antenna module, and the power module. The sensing device controller is programmed to receive an excitation signal from an external transceiving device. The sensing device controller is further programmed to perform a measurement using the sensor module in response to receiving the excitation signal. The sensing device controller is further programmed to transmit the measurement to the external transceiving device using the antenna module.

Abstract: A system for range sensor-based calibration of roadside cameras includes one or more cameras and range sensors with overlapping fields of view of a roadway. Control logic stored within and executed by a controller includes control logic for capturing image and range sensor data, for filtering the data to focus on first and second regions of interest (ROIs); for filtering the data to focus on first and second movements of interest (MOIs); for filtering the data to focus on first and second objects of interest (OOIs); for filtering the data to focus on first and second positions of interest (POIs); and for defining that objects detected by the camera and sensor and that satisfy both the first and second ROI, MOI, OOI, and POI filters are matching objects. The control logic calibrates the camera by applying a correction factor based on the matching objects.

Abstract: A system for video recording for a vehicle includes a camera system, a first wireless module, a second wireless module, and a controller in electrical communication with the camera system, the first wireless module, and the second wireless module. The controller is programmed to transmit a plurality of original training signals on a plurality of subcarriers using the first wireless module. The controller is further programmed to receive a plurality of propagated training signals using the second wireless module. The controller is further programmed to determine a deviation between the plurality of original training signals and the plurality of propagated training signals. The controller is further programmed to determine an occupancy status of an environment surrounding the vehicle based at least in part on the deviation and record a video using the camera system in response to determining that the occupancy status is an occupied status.

Abstract: An infrastructure-supported perception system for connected vehicle applications includes one or more infrastructure perception sensors that capture perception data having a reduced resolution and a reduced frame rate. The reduced resolution includes a reduced number of pixels for a given frame when compared to a standard resolution and the reduced frame rate captures data at a lower rate when compared to a standard frame rate. The infrastructure-supported perception system includes one or more controllers that are part of a connected vehicle. The controllers of the connected vehicle are in wireless communication with the one or more infrastructure perception sensors and one or more servers, and the one or more servers are in wireless communication with the one or more infrastructure perception sensors. The controllers receive dynamic information regarding one or more detected objects in an environment surrounding the connected vehicle from the one or more servers.

Abstract: A preemptive maneuvering system for viewing a status of a traffic control device by one or more cameras of an autonomous vehicle includes one or more controllers, where a moving obstruction is in front of the autonomous vehicle. The one or more controllers execute instructions to instruct the autonomous vehicle to execute one or more preemptive maneuvers to position the autonomous vehicle at the target following distance from the moving obstruction along the roadway.

Abstract: An occupant detection system for determining a unique position of a detected presence within an interior cabin area of a vehicle includes a plurality of signal conversion devices each including conversion circuitry. Each of the plurality of signal conversion devices are assigned to a specific position within the interior cabin area of the vehicle. The conversion circuitry for the plurality of signal conversion devices include unique sub-carrier frequency that corresponds to the unique position within the interior cabin area of the vehicle. The occupant detection system includes a wireless control module including a multi-band transceiver having a first transceiver configured to transmit and receive signals on a first frequency band and a second transceiver configured to transmit and receive signals on a second frequency band.

Abstract: An objection detection system for a vehicle includes one or more range sensors and one or more controllers in communication with the one or more range sensors. The one or more controllers execute instructions to instruct the one or more range sensors to emit a signal. The one or more range sensors receive a reflected signal from the environment surrounding the vehicle. The one or more controllers determine a position of the detected object based on the reflected signal and compare the position of the detected object with a dynamic region of interest (ROI). The one or more controllers determine the position of the detected object is outside of the dynamic ROI. In response to determining the position of the detected object is outside the dynamic ROI, the one or more controllers disregard the detected object for purposes of scene building.

Abstract: A scan matching and radar pose estimator for determining a final radar pose for an autonomous vehicle includes an automated driving controller that is instructed to determine a hyper-local submap based on a predefined number of consecutive aggregated filtered data point cloud scans and associated pose estimates. The automated driving controller determines an initial estimated pose by aligning a latest aggregated filtered data point cloud scan with the most recent hyper-local submap based on an iterative closest point (ICP) alignment algorithm. The automated driving controller determines a pose graph based on the most recent hyper-local submap and neighboring radar point cloud scans, and executes a multi-view non-linear ICP algorithm to adjust initial estimated poses corresponding to the neighboring radar point cloud scans in a moving window fashion to determine a locally adjusted pose.

Abstract: A multi-static radar detection system for a vehicle includes one or more receivers for collecting multi-carrier modulation signals emitted by one or more transmitters that are positioned at base stations located in an environment surrounding the vehicle. The multi-carrier modulation signals include one or more types of reference signals. The multi-static radar detection system also includes one or more controllers in electronic communication with the one or more receivers. The one or more controllers execute instructions to collect, by the one or more receivers, a multi-carrier modulation signal emitted by the one or more transmitters. The one or more controllers determine a Doppler shift and a time delay of a respective object located within the environment surrounding the vehicle based on an interpolated time-frequency grid; and transform a value for the Doppler shift into a velocity value and a value for the time delay into a range value.

Abstract: Systems and methods of harvesting wireless energy for climate control in a cabin of a vehicle are provided. The method comprises receiving an electromagnetic (EM) signal of EM radiation having EM energy to define an EM current. The method further comprises filtering the EM energy to regulate the EM current converting the EM current to direct current. The method further comprises storing the direct current for powering a battery-free wireless sensing unit and powering the battery-free wireless sensing unit with the direct current. After powering the battery-free wireless sensing unit, the method comprises sensing an actual condition in the cabin, the actual condition being one of actual temperature and actual humidity in the cabin. Furthermore, the method comprises adjusting one of temperature and humidity in the cabin in response to a difference between the actual condition and a set condition.

Abstract: A scan aggregator and filter for an autonomous vehicle includes a plurality of radar sensors, where each radar sensor performs a plurality of individual scans of a surrounding environment to obtain data in the form of a radar point cloud including a plurality of detection points. The scan aggregator and filter also includes an automated driving controller in electronic communication with the plurality of radar sensors. The automated driving controller is instructed to filter each of the individual scans to define a spatial region of interest and to remove the detection points of the radar point cloud that represent moving objects based on a first outlier-robust model estimation algorithm. The automated driving controller aggregates a predefined number of individual scans together based on a motion compensated aggregation technique to create an aggregated data scan and applies a plurality of density-based clustering algorithms to filter the aggregated data scan.

Abstract: A multi-static radar detection system for a vehicle includes one or more receivers for collecting multi-carrier modulation signals emitted by one or more transmitters that are positioned at base stations located in an environment surrounding the vehicle. The multi-carrier modulation signals include one or more types of reference signals. The multi-static radar detection system also includes one or more controllers in electronic communication with the one or more receivers. The one or more controllers execute instructions to collect, by the one or more receivers, a multi-carrier modulation signal emitted by the one or more transmitters. The one or more controllers determine a Doppler shift and a time delay of a respective object located within the environment surrounding the vehicle based on an interpolated time-frequency grid; and transform a value for the Doppler shift into a velocity value and a value for the time delay into a range value.

Abstract: A calibration pipeline for 6DoF alignment parameters for an autonomous vehicle includes an automated driving controller instructed to receive inertial measurement unit (IMU) poses and final radar poses and determine smoothened IMU poses from the IMU poses and smoothened final radar poses from the final radar poses. The automated driving controller aligns the smoothened IMU poses and the smoothened final radar poses with one another to create a plurality of radar-IMU A, B relative pose pairs. The automated riving controller determines a solution yielding a threshold number of inliers of further filtered radar-IMU A, B relative pose pairs, randomly samples the further filtered radar-IMU A, B relative pose pairs with replacements several times to determine a stream of filtered radar-IMU A, B relative pose pairs, and solves for a solution X for the stream of filtered radar-IMU A, B relative pose pairs.