Abstract: A method for obtaining a first set of images of an exterior of one or more vehicles, determining a condition of the exterior of the one or more vehicles by an automated vehicle marshaling algorithm of an infrastructure system, and causing the one or more vehicles to navigate toward a waypoint and capture one or more characteristics associated with the one or more vehicles.

Abstract: A method of controlling an autonomously operated vehicle along a test track including the extraction of frequency characteristics of a vehicle, the determination of one or more driving profiles based on the frequency characteristics and a deep learning model, the causation of the vehicle to select at least one of the one or more driving profiles based on at least one of a plurality of track segments along the test track, and the control of the vehicle's movement along the test track based on the vehicle selecting the at least one of the one or more driving profiles and the at least one of the plurality of track segments.

Abstract: A method for vehicle distribution of a fleet of vehicles includes: receiving signals from a set of infrastructure sensors; receiving signals from one or more sensors on-board the vehicles; processing the signals from the set of infrastructure sensors and the signals from the one or more sensors on-board the vehicles; controlling autonomous queuing of the vehicles using the processed signals; and controlling autonomous loading and unloading of the vehicles onto a transportation vehicle according to the queuing of the vehicles.

Abstract: A method includes calculating, by a vehicle system, a pose information for a vehicle having the vehicle system, determining, by the vehicle system, whether the calculated pose information matches that of a vehicle pose information received from an infrastructure system, updating, by the vehicle system, a current pose of the vehicle based on the calculated pose information, transmitting, by the vehicle system, a notification regarding the inaccurate pose information to the infrastructure system, and controlling, by the vehicle system, movement of the vehicle based on a stored marshaling route until a stop condition is satisfied.

Abstract: A vehicle can be detected approaching a limited operation zone of a travel area. It can be determined that the vehicle is able to execute wireless commands from a computer. The object can be identified within the limited operation zone. Based on identifying the object within the limited operation zone, the vehicle can be controlled by providing a control command via wireless communications, the control command including whether the vehicle is permitted to enter the limited operation zone.

Abstract: A method of marshaling an autonomously operated vehicle including the maneuvering of a vehicle toward a position and orientation associated with a charging station, the receipt of location data associated with a first position of the vehicle, and the initiation of an approach to engage the charging station based on updated location data associated with a second position of the vehicle.

Abstract: A method for validating one or more messages broadcasted by one or more vehicles or one or more road-side units may include determining, by an infrastructure controller and based on a channel busy ratio, whether the one or more messages broadcasted match one or more sanitized operating scenarios. The method may include causing, by the infrastructure controller, the one or more vehicles to initiate one or more remedial actions in response to determining that the one or more messages do not match the one or more sanitized operating scenarios.

Abstract: A method of wirelessly communicating status information of one or more vehicles with one or more infrastructures including the receipt of an onboarding process trigger based on a current status associated with a pre-onboarding process of the one or more vehicles, the determination of a current status associated with an onboarding process of the one or more vehicles based on the onboarding process trigger and an autonomous vehicle marshaling algorithm, and the output of an indication corresponding to the current status associated with the onboarding process of the one or more vehicles via exterior lights of the one or more vehicles to the one or more infrastructures or one or more human operators.

Abstract: A method includes obtaining infrastructure data from one or more infrastructure sensors, determining an infrastructure-based positional characteristic of the vehicle based on the infrastructure data, obtaining onboard image data from the onboard image sensor, determining an image-based positional characteristic of the vehicle based on the onboard image data and a digital twin of the manufacturing environment, generating an offset matrix based on the infrastructure-based positional characteristic and the image-based positional characteristic, and selectively adjusting a rotation matrix of the onboard image sensor based on the offset matrix and one or more additional offset matrices.

Abstract: A method for remotely waking-up a vehicle includes the request of a vehicle power state of at least one non-responsive vehicle of a plurality of autonomously operated vehicles, the verification—via a remote-start-wakeup automated vehicle marshaling algorithm installed within an infrastructure—of a current power state of the at least one non-responsive vehicle, the identification that the at least one non-responsive vehicle is in an off-state, and the generation of a wake-up command that is wirelessly transmitted to the at least one non-responsive vehicle via a CV2X-PC5 protocol.

Abstract: A system for calibrating a vehicle includes a funnel-type wheel alignment system and an infrastructure system. The infrastructure system is configured to autonomously control a movement of the vehicle within the funnel-type wheel alignment system based on an autonomous marshaling routine and selectively adjust one or more parameters of the autonomous marshaling routine based on one or more calibration metrics generated by the funnel-type wheel alignment system. The funnel-type wheel alignment system is configured to: obtain steering wheel angle data from one or more vehicle sensors, determine a vehicle steering pinion angle offset based on the steering wheel angle data, perform a physical alignment of one or more wheels of the vehicle as the vehicle moves through the funnel-type wheel alignment system, generate the one or more calibration metrics based on the vehicle steering pinion angle offset and the physical alignment, and broadcast the one or more calibration metrics.

Abstract: A method includes generating, by an infrastructure system, a radio frequency (RF) map based on a plurality of vehicle messages received from a plurality of vehicles and identifying, by the infrastructure system and based on the RF map, an area of a manufacturing environment that corresponds to an RF communication issue. The method includes generating, by the infrastructure system, an infrastructure message based on the RF map and the area of the manufacturing environment, and broadcasting, by the infrastructure system, the infrastructure message to a first vehicle of the plurality of vehicles.

Abstract: A method for the determination of pose information associated with a vehicle, the determination of a steering angle offset of the vehicle using an offset determination model configured to learn the steering angle offset of the vehicle, and the transmission of one or more steering angle offset commands to the vehicle.

Abstract: A method of wirelessly communicating status information of one or more vehicles with one or more infrastructures including the receipt of an onboarding process trigger based on a current status associated with a pre-onboarding process of the one or more vehicles, the determination of a current status associated with an onboarding process of the one or more vehicles based on the onboarding process trigger and an autonomous vehicle marshaling algorithm, and the output of an indication corresponding to the current status associated with the onboarding process of the one or more vehicles via exterior lights of the one or more vehicles to the one or more infrastructures or one or more human operators.

Abstract: A method includes estimating, by a vehicle communication system, a vehicle-localized time based on a previous vehicle system time and at least one internal factor in response to a primary synchronization data not being received and in response to an auxiliary synchronization data not being received. The previous vehicle system time is based on at least one of a previous primary synchronization data or a previous auxiliary synchronization data. The method further includes synchronizing, by the vehicle communication system, a vehicle system time employed by one or more vehicle modules disposed in the vehicle based on one of the primary synchronization data received, the auxiliary synchronization data received, or the vehicle-localized time estimated.

Abstract: A method for controlling vehicle movement includes: obtaining, by a vehicle, at least one radio frequency (RF) signal metric for a plurality of RF signals broadcasted in a manufacturing environment; broadcasting, by the vehicle, a vehicle message when the at least one RF signal metric satisfies at least one RF communication issue condition; generating, by an infrastructure system, an RF map based on the vehicle message and at least one additional vehicle message from at least one additional vehicle; and dynamically adjusting an infrastructure message, by the infrastructure system, based on the RF map when the vehicle autonomously navigates within the manufacturing environment.

Abstract: A method including the causation of a first road-side unit to broadcast one or more messages to one or more vehicles, the determination by an infrastructure-side algorithm of whether one or more messages received by a second road-side unit matches the one or more messages broadcasted by the first road-side unit, and the causation of the one or more vehicles to initiate one or more remedial actions in response to determining that the one or more messages received by the second road-side unit do not match the one or more messages broadcasted by the first road-side unit within a predefined timeframe.

Abstract: A method for obtaining a first set of images of an exterior of one or more vehicles, determining a condition of the exterior of the one or more vehicles by an automated vehicle marshaling algorithm of an infrastructure system, and causing the one or more vehicles to navigate toward a waypoint and capture one or more characteristics associated with the one or more vehicles.

Abstract: A method of marshaling an autonomously operated vehicle including the maneuvering of a vehicle toward a position and orientation associated with a charging station, the receipt of location data associated with a first position of the vehicle, and the initiation of an approach to engage the charging station based on updated location data associated with a second position of the vehicle.

Abstract: A method of controlling an autonomously operated vehicle along a test track including the extraction of frequency characteristics of a vehicle, the determination of one or more driving profiles based on the frequency characteristics and a deep learning model, the causation of the vehicle to select at least one of the one or more driving profiles based on at least one of a plurality of track segments along the test track, and the control of the vehicle's movement along the test track based on the vehicle selecting the at least one of the one or more driving profiles and the at least one of the plurality of track segments.