System and method for bringing a vehicle online

Abstract

The present disclosure provides "Systems and methods for bringing a vehicle online." One method includes receiving an identification pattern from an infrastructure system, determining whether a vehicle is within a distance-related threshold from the infrastructure system, and responsive to determining that the vehicle is within the distance-related threshold from the infrastructure system, performing one or more actions corresponding to the identification pattern.

Description

Technical Field

[0001] This disclosure relates to putting vehicles online, and more specifically, to putting vehicles online based on a uniquely assigned identification pattern. Background Technology

[0002] The statements in this section are provided only as background information in connection with this disclosure and may not constitute prior art.

[0003] Methods commonly used to bring vehicles online typically employ challenges for vehicle identification, such as flashing challenges. However, factory grouping systems that rely on flashing challenges to bring vehicles online cannot disable certain light functions enabled by human operators according to certain criteria. Other issues associated with commonly used flashing challenges may include a lack of customization and incorrect online deployments due to server misinterpretation of the flashing patterns executed by the vehicles.

[0004] This disclosure addresses these and other issues related to the deployment of vehicles. Summary of the Invention

[0005] This section provides a general overview of this disclosure and is not a full disclosure of its entire scope or all its features.

[0006] This disclosure provides a method for bringing a vehicle online, the method comprising: receiving an identification pattern from an infrastructure system at the vehicle; determining whether the vehicle is within a distance-related threshold from the infrastructure system; and performing one or more actions corresponding to the identification pattern in response to determining that the vehicle is within the distance-related threshold from the infrastructure system; wherein the identification pattern includes light patterns, vehicle movement, window movement, door movement, cabin door movement, audio patterns, or combinations thereof; wherein the identification pattern is unique to the vehicle; wherein determining whether the vehicle is within the distance-related threshold from the infrastructure system further comprises: performing one or more positioning techniques based on predetermined geofence-based mapping of a grouped environment; the method further comprises: based on performing the one or more positioning techniques, in response to determining that the vehicle is outside the distance-related threshold from the infrastructure system, causing one or more drones to be deployed to the location of the vehicle; and performing the one or more actions in response to the one or more drones being deployed to the location of the vehicle; and the method further comprises: performing one or more additional actions to confirm a successful online event associated with the vehicle, wherein the one or more additional actions are different from the one or more actions.

[0007] This disclosure provides another method for bringing a vehicle online, the method comprising: assigning an identification pattern to a vehicle in response to receiving an online request from the vehicle; transmitting the identification pattern to the vehicle; verifying the identity of the vehicle based on determining that the vehicle is within a distance-related threshold from an infrastructure system and the execution of one or more actions matching the identification pattern, wherein the one or more actions are performed by the vehicle in response to receiving the identification pattern; and bringing the vehicle online in response to verifying the vehicle's identity; wherein the identification pattern includes light patterns, vehicle movement, window movement, door movement, hatch movement, audio patterns, or combinations thereof; wherein the identification pattern is unique to the vehicle; the method further comprising: receiving from the vehicle... The method includes: receiving one or more messages indicating that a vehicle is located outside a distance-related threshold from an infrastructure system; and deploying one or more drones to the vehicle's location in response to receiving one or more messages; the method further includes: receiving a video stream from one or more drones; performing one or more image recognition techniques in response to receiving the video stream; and determining whether the one or more actions match a recognition pattern in response to performing the one or more image recognition techniques; and the method further includes: performing one or more image recognition techniques based on the field of view of one or more sensors of the infrastructure system; and determining whether the one or more actions match the recognition pattern in response to performing the one or more image recognition techniques.

[0008] This disclosure provides a system for bringing a vehicle online, the system comprising: a vehicle system configured to: transmit an online request, receive a vehicle-specific identification pattern, determine whether a vehicle associated with the vehicle system is within a distance-related threshold of an infrastructure system, and, in response to determining that the vehicle is within the distance-related threshold of the infrastructure system, perform one or more actions corresponding to the identification pattern; and the infrastructure system configured to: assign an identification pattern to a vehicle in response to receiving the online request, transmit the identification pattern, verify the vehicle's identity based on the execution of one or more actions matching the identification pattern, and bring the vehicle online in response to verifying the vehicle's identity; wherein the identification pattern includes light patterns, vehicle movement, window movement, door movement, cabin door movement, audio patterns, or combinations thereof; wherein the vehicle system configured to determine whether the vehicle is within the distance-related threshold of the infrastructure system is further configured to: perform one or more positioning techniques based on predetermined geofencing-based mapping of the grouping environment; wherein the vehicle system is further configured to: based on the execution of the one or more positioning techniques, cause, in response to determining that the vehicle is outside the distance-related threshold of the infrastructure system, to Deploying one or more drones to the location of the vehicle; and performing one or more actions in response to the deployment of the one or more drones to the location of the vehicle; wherein the infrastructure system is further configured to: receive one or more messages from the vehicle system indicating that the vehicle is located outside a distance-related threshold from the infrastructure system; and deploy one or more drones to the location of the vehicle in response to receiving the one or more messages; wherein the infrastructure system is further configured to: receive video streams from the one or more drones; perform one or more image recognition techniques in response to the reception of the video streams; and determine whether the one or more actions match a recognition pattern in response to the performance of the one or more image recognition techniques; wherein the infrastructure system is further configured to: perform one or more image recognition techniques based on the field of view of one or more sensors of the infrastructure system; and determine whether the one or more actions match a recognition pattern in response to the performance of the one or more image recognition techniques; and wherein the vehicle system is further configured to: perform one or more additional actions to confirm a successful online event associated with the vehicle, wherein the one or more additional actions are different from the one or more actions.

[0009] Further applicability will become apparent from the description provided herein. It should be understood that the descriptions and specific examples are intended for illustrative purposes only and are not intended to limit the scope of this disclosure. Attached Figure Description

[0010] To better understand this disclosure, various forms of the disclosure will now be described by way of example with reference to the accompanying drawings, in which: Figure 1 A system for automated vehicle grouping according to one or more embodiments of the present disclosure is shown; Figure 2 One or more embodiments of the present disclosure are shown. Figure 1 The system shown in the image is used to group example vehicles; Figure 3 Implementations of a system for bringing vehicles online according to one or more embodiments of the present disclosure are shown; Figure 4 This is a flowchart illustrating an example method for putting a vehicle online according to one or more embodiments of the present disclosure; Figure 5 This is a flowchart illustrating another example method for putting a vehicle online according to one or more embodiments of the present disclosure; Figure 6 This is a flowchart illustrating yet another example method for putting a vehicle online according to one or more embodiments of the present disclosure; Figure 7 This is a flowchart illustrating yet another example method for putting a vehicle online according to one or more embodiments of the present disclosure; and Figure 8 This is a block diagram illustrating an example computer system according to one or more embodiments of the present disclosure.

[0011] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of this disclosure in any way. Detailed Implementation

[0012] The following description is merely exemplary in nature and is not intended to limit this disclosure, its application, or its uses. It should be understood that throughout the drawings, corresponding reference numerals indicate the same or corresponding parts and features.

[0013] The one or more examples described herein provide systems and methods for enhancing vehicle online capabilities. In one or more examples, the online process disclosed herein enhances the accuracy of vehicle online capability by reducing production cycle time delays; preventing the loading / unloading of incorrect vehicles; preventing incorrect vehicle control and / or parking the vehicles in incorrect parking spaces; and / or preventing the vehicles from being positioned in incorrect charging locations. An additional advantage provided by the online process disclosed herein is the ability to accurately online an unlimited number of vehicles at any distance from a central server and under any conditions.

[0014] Figure 1A schematic block diagram of an Automated Vehicle Grouping (AVM) system 100 is shown. In one or more examples, the AVM system 100 groups one or more vehicles (e.g., vehicle 102) that are traveling at a low speed. However, it should be understood that the AVM system 100 can group one or more vehicles that are traveling at any speed. It should also be understood that the AVM system 100 can group semi-autonomous vehicles and / or fully autonomous vehicles.

[0015] AVM system 100 typically includes vehicle 102, vehicle manufacturing cloud system 104, vehicle delivery manager cloud system 106, vehicle customer web portal account cloud system 108, and infrastructure system 110. Vehicle manufacturing cloud system 104 serves as a central cloud system for managing and / or facilitating any manufacturing processes associated with vehicle 102. Vehicle manufacturing cloud system 104 is configured to communicate wirelessly with vehicle delivery manager cloud system 106 and / or infrastructure system 110. Vehicle manufacturing cloud system 104 is also configured to communicate wirelessly with vehicle 102.

[0016] The vehicle manufacturing cloud system 104 may include an infrastructure-side AVM algorithm 112. However, it should be understood that the infrastructure system 110 may also include an infrastructure-side AVM algorithm 112, such as... Figure 3 As shown in the diagram. Infrastructure-side AVM algorithm 112 processes state information associated with at least one vehicle 102 among one or more vehicles. It should be understood that, in one or more embodiments, infrastructure-side AVM algorithm 112 processes state information associated with each of the one or more vehicles (e.g., vehicle 102). The vehicle manufacturing cloud system 104 is configured to cause the infrastructure system 110 to monitor the progress of the vehicles (e.g., vehicle 102) as they move through a marshalling environment. For example, a marshalling environment can represent a factory marshalling scenario, an automated charging scenario, a depot marshalling scenario, a parking scenario, etc. As an example, a factory marshalling scenario may include vehicles that have just been manufactured, sensed via top-down visual sensing (e.g., via a set of infrastructure sensors 302, such as…). Figure 3 The example shown illustrates an instance of vehicles moving through a production line at a vehicle assembly plant for off-line testing. As another example, an automated charging scenario could include instances where vehicles are correctly assigned to automated charging modes located outdoors or indoors. As yet another example, a depot marshalling scenario could include instances where a fleet of commercial vehicles moves through warehouses and depots for automated loading and / or handling of goods. As an additional example, a parking scenario could include instances where vehicles move through underground or covered parking environments with potentially inconsistent communication networks, such as a Global Navigation Satellite System.

[0017] The vehicle manufacturing cloud system 104 is also configured to cause the infrastructure system 110 to communicate with one or more vehicles. For example, the vehicle manufacturing cloud system 104 utilizes the infrastructure-side AVM algorithm 112 to send instructions to the infrastructure system 110 and / or process information received from the infrastructure system 110. The vehicle manufacturing cloud system 104 is also configured to cause the vehicle delivery manager cloud system 106 to facilitate the delivery of one or more vehicles (e.g., vehicle 102) to various locations. For example, the vehicle manufacturing cloud system 104 utilizes the infrastructure-side AVM algorithm 112 to send instructions to the vehicle delivery manager cloud system 106 and / or process information received from the vehicle delivery manager cloud system 106.

[0018] The vehicle manufacturing cloud system 104 is also configured to communicate directly with one or more vehicles to cause the one or more vehicles to start, stop, or pause their progress through the formation environment. The vehicle manufacturing cloud system 104 is also configured to control the formation speed of one or more vehicles as they travel through (e.g., traverse) the formation environment. For example, the vehicle manufacturing cloud system 104 utilizes the infrastructure-side AVM algorithm 112 to send instructions to vehicle 102 and / or process information received from vehicle 102.

[0019] Infrastructure system 110 includes sensor components 114, wireless communication components 116, a multi-access edge computing (MEC) system 118, and one or more traffic lights 120. It should be understood that the MEC system 118 is configured to support communication between the wireless communication components 116 and the vehicle 102. However, it should also be understood that the MEC system 118 is also configured to support communication between the wireless communication components 116 and any of the vehicle manufacturing cloud system 104, the vehicle delivery manager cloud system 106, and / or the vehicle customer web portal account cloud system 108. For example, the wireless communication components 116 may utilize GPS, Wi-Fi, satellite, 3G / 4G / 5G, and / or Bluetooth. ® To communicate with one or more vehicles.

[0020] The wireless communication component 116 also communicates with the sensor component 114, which is configured to communicate with and / or manage the set of infrastructure sensors 302, as described herein. In one or more examples, the sensor component 114 is also configured to perform one or more positioning functions associated with grouping one or more vehicles, such as, but not limited to, sensing, path planning, detection, control, and / or receiving and analyzing responses from each of the one or more vehicles.

[0021] The wireless communication component 116 also communicates with the traffic light 120. For example, when one or more vehicles are grouped through a grouping environment, the wireless communication component 116 can cause the traffic light 120 to guide the traffic of one or more vehicles. It should be understood that the infrastructure system 110 can forward instructions received from the vehicle manufacturing cloud system 104 to the vehicle 102. However, it should also be understood that the infrastructure system 110 can send instructions directly to the vehicle 102, for example, by utilizing the MEC system 118.

[0022] Vehicle 102 includes a vehicle-side AVM algorithm 122, a wireless transmission module 124, a vehicle central gateway module 126, a vehicle infotainment system 128, one or more vehicle sensors 130, a vehicle battery 132, a vehicle GNSS 134, a vehicle navigation mapping system 136, and a controller area network (CAN) vehicle bus 138. The wireless transmission module 124 may be a transmission control unit (TCU) and / or may be supported by a telematics-enabled subsystem. The wireless transmission module 124 includes one or more sensors configured to collect data and transmit signals to other components of vehicle 102. One or more sensors of the wireless transmission module 124 may include, but are not limited to, a vehicle speed sensor (not shown) configured to determine the current speed of the vehicle 102; a wheel speed sensor (not shown) configured to determine whether the vehicle 102 is traveling uphill or downhill; a throttle position sensor (not shown) configured to determine whether a downshift or upshift of one or more gears associated with the vehicle 102 is required in the current state of the vehicle 102; and / or a turbo speed sensor (not shown) configured to transmit data associated with the rotational speed of the torque converter of the vehicle 102.

[0023] The wireless transmission module 124 transmits information collected by one or more sensors to the vehicle-side AVM algorithm 122. In one embodiment, the vehicle-side AVM algorithm 122 may be a component within the wireless transmission module 124. For example, vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information collected by one or more sensors and transmit the information to infrastructure system 110. As another example, vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information collected by one or more sensors and transmit the information directly to vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to transmit information and / or instructions received from infrastructure system 110 and / or vehicle manufacturing cloud system 104 to the wireless transmission module 124.

[0024] The vehicle central gateway module 126 operates as an interface between various vehicle domain bus systems, such as engine compartment bus (not shown), interior bus (not shown), optical bus for multimedia (not shown), diagnostic bus for maintenance (not shown), or vehicle CAN bus 138. The vehicle central gateway module 126 is configured to distribute data transmitted to it from each of the various domain bus systems to other components of the vehicle 102. The vehicle central gateway module 126 is also configured to distribute information received from the vehicle-side AVM algorithm 122 to the various domain bus systems. The vehicle central gateway module 126 is also configured to send information received from the various domain bus systems to the vehicle-side AVM algorithm 122. For example, the vehicle 102 uses the vehicle-side AVM algorithm 122 to process information received from the vehicle central gateway module 126 and sends the information to the infrastructure system 110. As another example, the vehicle 102 uses the vehicle-side AVM algorithm 122 to process information received from the vehicle central gateway module 126 and sends the information directly to the vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to transmit information and / or instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to the vehicle central gateway module 126.

[0025] The vehicle infotainment system 128 delivers a combination of information and entertainment content and / or services to a user 140 of vehicle 102. It should be understood that in some examples, the vehicle infotainment system 128 may only deliver entertainment content to the user 140 of vehicle 102. It should also be understood that in other examples, the vehicle infotainment system 128 may deliver information services to anyone associated with vehicle 102. As an example, the vehicle infotainment system 128 includes a built-in vehicle computer that combines one or more functions, such as a digital radio, a built-in camera, and / or a television. The vehicle infotainment system 128 transmits information associated with the built-in vehicle computer or processor to a vehicle-side AVM algorithm 122. For example, vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received from the vehicle infotainment system 128 and transmits said information to infrastructure system 110. As another example, vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received from the vehicle infotainment system 128 and transmits said information directly to vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to transmit information and / or instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to the vehicle infotainment system 128.

[0026] One or more vehicle sensors 130 may be one or more of, for example, cameras, lidar, radar, and / or ultrasonic devices. For example, an ultrasonic device serving as one or more vehicle sensors 130 emits high-frequency sound waves that strike a wall or another vehicle and are then reflected back to vehicle 102. Based on the amount of time it takes for the sound waves to return to vehicle 102, vehicle 102 can determine the distance between the one or more vehicle sensors 130 and the wall or another vehicle. As another example, a camera device serving as one or more vehicle sensors 130 provides a visual indication of the space around vehicle 102. As an additional example, a radar device serving as one or more vehicle sensors 130 emits electromagnetic wave signals that strike a wall or another vehicle and are then reflected back to vehicle 102. Based on the amount of time it takes for the electromagnetic waves to return to vehicle 102, vehicle 102 can determine the distance, speed, and angle of vehicle 102 relative to the wall or another vehicle.

[0027] One or more vehicle sensors 130 transmit information associated with the location and / or distance of vehicle 102 relative to a wall or another vehicle to vehicle-side AVM algorithm 122. For example, vehicle 102 utilizes vehicle-side AVM algorithm 122 to process information received from one or more vehicle sensors 130 and transmit said information to infrastructure system 110. As another example, vehicle 102 utilizes vehicle-side AVM algorithm 122 to process information received from one or more vehicle sensors 130 and transmit said information directly to vehicle manufacturing cloud system 104. Vehicle-side AVM algorithm 122 is configured to transmit information and / or instructions received from infrastructure system 110 and / or vehicle manufacturing cloud system 104 to one or more vehicle sensors 130.

[0028] Vehicle battery 132 is controlled by a battery management system (not shown) that provides instructions to vehicle battery 132. For example, the battery management system provides instructions to vehicle battery 132 based on the temperature of vehicle battery 132. However, it should be understood that the battery management system may provide instructions to vehicle battery 132 based on any metric associated with vehicle battery 132, such as the state of power of vehicle 102, the period during which vehicle 102 is in an off state, or a combination thereof. The battery management system ensures that the current pattern of vehicle battery 132 is acceptable. For example, an acceptable current pattern prevents overvoltage, overcharge, and / or overheating of vehicle battery 132. As another example, the temperature of vehicle battery 132 indicates to the battery management system whether any of the acceptable current patterns is within an acceptable temperature range. The battery management system associated with vehicle battery 132 transmits information related to the temperature of vehicle battery 132 to vehicle-side AVM algorithm 122. For example, vehicle 102 uses vehicle-side AVM algorithm 122 to process the received information about vehicle battery 132 and transmit the information to infrastructure system 110. As another example, vehicle 102 utilizes vehicle-side AVM algorithm 122 to process information about vehicle battery 132 and transmits the information directly to vehicle manufacturing cloud system 104. Vehicle-side AVM algorithm 122 is configured to transmit information and / or instructions received from infrastructure system 110 and / or vehicle manufacturing cloud system 104 to vehicle battery 132.

[0029] Vehicle GNSS 134 is configured to communicate with satellites, enabling vehicle 102 to determine its exact location. Vehicle navigation mapping system 136 can display the exact location of vehicle 102 to user 140 via a display screen (not shown). Vehicle GNSS 134 transmits geographic information associated with vehicle 102 to vehicle-side AVM algorithm 122. For example, vehicle 102 uses vehicle-side AVM algorithm 122 to process information received from vehicle GNSS 134 and transmit the information to infrastructure system 110. As another example, vehicle 102 uses vehicle-side AVM algorithm 122 to process information from vehicle GNSS 134 and transmit the information directly to vehicle manufacturing cloud system 104. Vehicle-side AVM algorithm 122 is configured to transmit information and / or instructions received from infrastructure system 110 and / or vehicle manufacturing cloud system 104 to vehicle GNSS 134. As another example, vehicle 102 utilizes vehicle-side AVM algorithm 122 to process information associated with vehicle navigation mapping system 136 and transmits said information to infrastructure system 110. As yet another example, vehicle 102 utilizes vehicle-side AVM algorithm 122 to process information from vehicle navigation mapping system 136 and transmits said information directly to vehicle manufacturing cloud system 104. Vehicle-side AVM algorithm 122 is configured to transmit information and / or instructions received from infrastructure system 110 and / or vehicle manufacturing cloud system 104 to vehicle navigation mapping system 136.

[0030] Vehicle 102 is configured to transmit any information associated with any component included within vehicle 102 to one or more additional vehicles 142. Vehicle 102 is also configured to transmit (e.g., forward) any instructions received from infrastructure system 110 and / or vehicle manufacturing cloud system 104 to any of the one or more additional vehicles 142. For example, communication between vehicle 102 and one or more additional vehicles 142 may assist infrastructure system 110 and / or vehicle manufacturing cloud system 104 in grouping one or more additional vehicles 142. It should be understood that each of the one or more additional vehicles 142 may include any of the components described as included within vehicle 102, such as, but not limited to, vehicle-side AVM algorithm 122, wireless transmission module 124, vehicle central gateway module 126, vehicle infotainment system 128, one or more vehicle sensors 130, vehicle battery 132, vehicle GNSS 134, vehicle navigation mapping system 136, and / or CAN vehicle bus 138. It should also be understood that any of the one or more additional vehicles 142 is configured to transmit information associated with any component included within vehicle 102. It should also be understood that the one or more additional vehicles 142 may also be configured to establish direct wireless communication lines (e.g., via communication links) with infrastructure system 110 and / or vehicle manufacturing cloud system 104, thereby enabling direct exchange of information between the one or more additional vehicles 142 and infrastructure system 110 and / or vehicle manufacturing cloud system 104.

[0031] The vehicle delivery manager cloud system 106 wirelessly communicates (e.g., receives and / or sends instructions and / or information) with one or more of the following: rental agency cloud system 144, valet parking agency cloud system 146, insurance agency cloud system 148, and / or dealer system 150. The vehicle delivery manager cloud system 106 is configured to facilitate the delivery of one or more vehicles to any of the following: a rental agency (not shown) associated with rental agency cloud system 144, a valet parking agency (not shown) associated with valet parking agency cloud system 146, an insurance agency (not shown) associated with insurance agency cloud system 148, and / or dealer system 150. The vehicle delivery manager cloud system 106 also wirelessly communicates with vehicle customer web portal account cloud system 108. It should be understood that other cloud systems may be included in one or more examples.

[0032] The vehicle delivery manager cloud system 106 communicates wirelessly with a user device 152, such as, but not limited to, a mobile device, a display panel, and / or a computer. The vehicle 102 is also configured to communicate directly with the user device 152 wirelessly. For example, a user 140 engages with the user device 152 via an application that organizes any information and / or instructions received from the vehicle customer web portal account cloud system 108 and / or the vehicle 102. As another example, the user 140 may send one or more instructions to the vehicle customer web portal account cloud system 108, such as selecting which vehicle the user 140 wants to receive from any of the following: a rental agency associated with the rental agency cloud system 144, a valet parking agency associated with the valet parking agency cloud system 146, an insurance agency associated with the insurance agency cloud system 148, and / or a dealership system 150.

[0033] refer to Figure 2 Vehicle 102 can be powered in various forms and in various ways, such as by using an electric motor and / or an internal combustion engine. It should be understood that vehicle 102 can be any type of vehicle powered by an electric motor and / or an internal combustion engine, such as a car, truck, robot, aircraft, and / or boat. Vehicle 102 typically includes a vehicle controller 200, one or more actuators 202, multiple onboard sensors 204, a human-machine interface (HMI) 206, and a vehicle system 208. Vehicle 102 also has a reference point 210, i.e., a designated point within the space defined by the vehicle body, which identifies the position of vehicle 102. For example, reference point 210 is the geometric center point where the respective longitudinal and lateral center axes of vehicle 102 intersect. As another example, reference point 210 is the point where vehicle 102 is located when navigating toward a waypoint.

[0034] The multiple onboard sensors 204 include various means for providing data to the vehicle controller 200. For example, the multiple onboard sensors 204 may include object detection sensors (e.g., lidar sensors) disposed on or in the vehicle 102, which provide the relative position, size, and / or shape of one or more objects (such as attached vehicles, bicycles, robots, drones, etc.) traveling beside, in front of, and / or behind the vehicle 102. As another example, one or more of the multiple onboard sensors 204 may be radar sensors attached to one or more bumpers of the vehicle 102, which can provide the position of an object relative to the position of each of the vehicle 102. As yet another example, one or more of the multiple onboard sensors 204 may be configured to monitor one or more functionalities associated with one or more internal components of the vehicle 102.

[0035] Multiple onboard sensors 204 may include camera sensors that provide images from the area surrounding vehicle 102, such as providing front, side, and rear views. As another example, vehicle controller 200 may be programmed to receive sensor data from the camera sensors and perform image processing techniques to detect roads, infrastructure elements, etc. Vehicle controller 200 may be programmed to determine the current vehicle position based on location coordinates (e.g., GPS coordinates) received from vehicle 102 indicating the position of vehicle 102 from a GPS sensor (not shown).

[0036] In some examples, vehicle controller 200 is configured or programmed to control one or more of the following: vehicle braking, propulsion (e.g., controlling the acceleration of vehicle 102 by controlling one or more of an internal combustion engine, electric motor, hybrid engine, etc.), steering, climate control, interior and / or exterior lights, etc. In other examples, vehicle controller 200 is also configured or programmed to determine whether and when vehicle controller 200 (rather than a human operator) controls such operations associated with vehicle 102. It should be understood that any operation associated with vehicle 102 can be facilitated via automated, semi-automated, or manual modes. For example, an automated mode can facilitate complete control of any operation by vehicle controller 200 without the assistance of a human operator. As another example, a semi-automated mode can facilitate at least partial control of any operation by a human operator in combination with vehicle controller 200. As yet another example, a manual mode can facilitate complete control of operation by a human operator without the assistance of vehicle controller 200.

[0037] Vehicle controller 200 includes one or more processors (not shown), or can be communicatively coupled to one or more processors (e.g., via a vehicle communication bus). For example, the one or more processors may be controllers included in vehicle 102, used to monitor and / or control various vehicle controllers, such as powertrain controllers, brake controllers, steering controllers, etc. Vehicle controller 200 is typically arranged for various communications over a vehicle communication network (not shown) (which may include buses in vehicle 102, such as a CAN bus) and / or other wired and / or wireless mechanisms.

[0038] Vehicle controller 200 transmits messages to and / or receives messages from various devices (e.g., one or more actuators 202, HMI 206, etc.) in vehicle 102 via a vehicle network. Alternatively or additionally, where vehicle controller 200 includes multiple devices, a vehicle communication network is used for communication between the devices represented herein as vehicle controller 200. Furthermore, as discussed below, various other controllers and / or sensors provide data to vehicle controller 200 via the vehicle communication network.

[0039] Additionally, the vehicle controller 200 is also configured via the vehicle-side AVM algorithm 122 to communicate with the infrastructure communication network through the vehicle, such as with the infrastructure controller (e.g., ...). Figure 3 The vehicle controller 200 communicates with the infrastructure controller 304 shown. The vehicle controller 200 is also configured via the vehicle-side AVM algorithm 122 to communicate with other traffic objects (e.g., vehicles, infrastructure, etc.) through a wireless vehicle communication interface, such as via a vehicle-to-vehicle communication network. The vehicle communication network represents one or more mechanisms by which the vehicle controller 200 of vehicle 102 communicates with other traffic objects. As an example, the vehicle communication network can be one or more wireless communication mechanisms, including any desired combination of wireless (e.g., cellular, wireless, satellite, microwave, and / or radio frequency) communication mechanisms, and any desired network topology (or multiple topologies utilizing multiple communication mechanisms). Examples of vehicle communication networks include cellular, Bluetooth®, IEEE 802.11, Dedicated Short Range Communication (DSRC), and / or Wide Area Network (WAN) (including the Internet) providing data communication services.

[0040] One or more actuators 202 are implemented via circuits, chips, or other electronic and / or mechanical components that can actuate various vehicle subsystems according to appropriate control signals. One or more actuators 202 can be used to control the braking, acceleration, and / or steering of the vehicle 102. The vehicle controller 200 can be programmed to activate one or more actuators 202 (including propulsion, steering, and / or braking actuators) based on planned acceleration or deceleration of the vehicle 102.

[0041] HMI 206 is configured to receive information from a human operator during operation of vehicle 102. Additionally, HMI 206 is configured to present information to a human operator, such as an occupant of vehicle 102. In some variations, vehicle controller 200 is programmed to receive destination data (e.g., location coordinates) from HMI 206.

[0042] Vehicle system 208 is configured to control each of the subsystems within vehicle 102 and facilitate requests across each of the aforementioned components (e.g., vehicle controller 200, one or more actuators 202, multiple on-board sensors 204, and / or HMI 206). Therefore, at least multiple on-board sensors 204 can be used to autonomously guide vehicle 102 to waypoints. Route selection can be performed using vehicle position, distance traveled, queuing for vehicle grouping, etc.

[0043] In one or more embodiments, Figure 3System 300 is shown, configured to provide means for bringing vehicle 102 (e.g., and / or one or more additional vehicles 142) online. More specifically, enhanced means for accurately bringing vehicle 102 (e.g., and / or one or more additional vehicles 142) online within the boundaries provided by system 300 are provided.

[0044] In one or more embodiments, the infrastructure system 110 includes a sensor component 114 that communicates with a set of infrastructure sensors 302. The set of infrastructure sensors 302 is configured to monitor the movement of vehicle 102 (e.g., and / or one or more auxiliary vehicles 142) as it moves through a grouped environment. The infrastructure system 110 also includes a wireless communication component 116 that provides means for communication between the infrastructure system 110 and at least one communication node 310 and the vehicle manufacturing cloud system 104. However, it should be understood that the wireless communication component 116 also provides means for direct communication between the infrastructure system 110 and vehicle 102 (e.g., and / or one or more auxiliary vehicles 142).

[0045] In one or more examples, the movement of vehicle 102 (e.g., and / or one or more additional vehicles 142) through the manufacturing environment is monitored based on the field of view of the set of infrastructure sensors 302. As another example, the movement of vehicle 102 (e.g., and / or one or more additional vehicles 142) through geofenced areas of the manufacturing environment (e.g., such as...) is also monitored based on one or more infrastructure grouping messages (e.g., IMM) and one or more vehicle grouping messages (e.g., VMM) exchanged between vehicle 102 (e.g., and / or one or more additional vehicles 142) and infrastructure system 110. Figure 3 The movement of the geofenced area 308 shown in the figure.

[0046] Additionally, infrastructure system 110 includes infrastructure controller 304. Infrastructure controller 304 is configured to centrally control the operation of vehicle 102 (e.g., and / or one or more auxiliary vehicles 142). For example, the operation of vehicle 102 (e.g., and / or one or more auxiliary vehicles 142) includes propulsion, braking, and / or steering. It should be understood that infrastructure controller 304 may be located within infrastructure system 110 or externally relative to infrastructure system 110. Infrastructure controller 304 includes infrastructure-side AVM algorithm 112, which is configured to facilitate communication between infrastructure controller 304 and vehicle controller 200 associated with vehicle 102 (e.g., and / or one or more auxiliary vehicles 142).

[0047] The infrastructure-side AVM algorithm 112 is also configured to facilitate communication between the infrastructure controller 304 and one or more anchors 306. For example, each of the one or more anchors 306 may be a transceiver configured to transmit and / or receive any communication-related messages (e.g., instructions, signals, etc.). As an example, the infrastructure controller 304 and one or more anchors 306 are communicatively connected via a wired connection. As another example, each of the one or more anchors 306 is also communicatively connected to each other via a wired connection. However, it should be understood that the one or more anchors 306 may be wirelessly connected to each other and / or wirelessly connected to the infrastructure controller 304. For example, the one or more anchors 306 may be positioned at any distance from each other throughout the marshalling environment. As another example, the one or more anchors 306 may be embedded within the floor of the marshalling environment. However, it should be understood that the one or more anchors 306 may also be positioned on top of the floor of the marshalling environment (e.g., on the surface of the floor, but not embedded within it). It should also be understood that one or more anchor points 306 may be set in a variety of ways, such as, but not limited to, some of the anchor points 306 being embedded in the floor of the marshalling environment and some of the anchor points 306 being set on top of the floor of the marshalling environment.

[0048] In one or more embodiments, the infrastructure-side AVM algorithm 112 is configured to receive online requests from vehicle 102 (e.g., and / or each of one or more additional vehicles 142). In one or more examples, the infrastructure-side AVM algorithm 112 is also configured to generate a custom vehicle-specific identification pattern and assign it to each vehicle from which it receives an online request. In other words, and as an example, the vehicle-specific identification pattern uniquely assigned to vehicle 102 is different from each of the one or more additional vehicles 142 or any other vehicle. As another example, the vehicle-specific identification pattern may include light patterns, vehicle movement, window movement, door movement, hatch movement, audio patterns, or combinations thereof. As yet another example, assigning different identification patterns to different vehicles enhances online accuracy by reducing unintended vehicle online arrivals.

[0049] In one or more examples, a light pattern corresponding to a vehicle-specific identification pattern can be customized such that vehicle 102 (e.g., or one or more auxiliary vehicles 142) can emit a specific light color from various and / or specific lighting mechanisms (such as, but not limited to, brake lights, headlights, and / or side lights) of vehicle 102 (e.g., or one or more auxiliary vehicles 142). As another example, the light pattern can also be customized such that vehicle 102 (e.g., or one or more auxiliary vehicles 142) can emit light at any duration and / or frequency (e.g., such as a series of flashing lights). As yet another example, each of the lighting mechanisms of vehicle 102 (e.g., or one or more auxiliary vehicles 142) is configured to emit the same light color or different light colors simultaneously at different times, at different durations, and / or at any frequency.

[0050] In one or more examples, a vehicle-specific identification pattern may also be customized such that vehicle 102 (e.g., or one or more additional vehicles 142) can perform at least one of vehicle movement, window movement, door movement, hatch movement, and / or an audio pattern corresponding to the vehicle-specific identification pattern. As another example, vehicle movement may include any precise movement of vehicle 102 (e.g., or one or more additional vehicles 142), such as, but not limited to, moving a specific distance (e.g., 2 feet vs. 5 feet) and / or moving in any direction (e.g., 2 feet northeast vs. 3 feet north). As yet another example, each of window movement, door movement, and hatch movement may include any movement (e.g., or movement pattern), such as opening and closing any of the windows, doors, and / or hatches at any various degrees. As yet another example, the audio pattern may include the emission of any sound pattern originating from any transducer of the vehicle (e.g., or one or more additional vehicles 142).

[0051] It should be understood that the vehicle-specific identification pattern can also be further customized with respect to any functionality associated with vehicle 102 (e.g., or one or more attached vehicles 142), such as, but not limited to, activation of the wiper blades of vehicle 102 (e.g., or one or more attached vehicles 142) and / or activation of the washer pump of vehicle 102 (e.g., or one or more attached vehicles 142). In one or more examples, the infrastructure-side AVM algorithm 112 is configured to determine whether vehicle 102 (e.g., or one or more attached vehicles 142) is covered by rain, snow, dirt, or any other obstruction, which can be the basis for causing vehicle 102 (e.g., or one or more attached vehicles 142) to perform a vehicle-specific identification pattern or any other action related to the activation of the wiper blades.

[0052] In one or more examples, infrastructure system 110 is configured to transmit a vehicle-specific identification pattern in response to assigning a vehicle-specific identification pattern to each vehicle from which it receives an online request.

[0053] Upon receiving a vehicle-specific identification pattern, the vehicle-side AVM algorithm 122 is configured to perform one or more localization techniques to determine whether vehicle 102 (e.g., and / or one or more auxiliary vehicles 142) is located within a distance-related threshold from infrastructure system 110. In one or more examples, the distance-related threshold can be any predefined distance from infrastructure system 110, corresponding to the field of view of one or more sensors 302 and / or the communication range with infrastructure system 110 (e.g., or at least one communication node 310). As another example, the distance-related threshold can be one or more predefined identification locations corresponding to areas within the field of view of one or more sensors 302 and / or the communication range with infrastructure system 110 (e.g., or at least one communication node 310). As yet another example, identification locations can be predefined by implementing geofence-based mapping associated with geofenced area 308. It should be understood that geofence-based mapping can be dynamically adjusted and depends on one or more environmental conditions or any other conditions that may affect the field of view of at least one or more sensors 302.

[0054] In one or more examples, one or more positioning techniques may be based on the use of one or more anchor points 306 and / or geofence-based mapping associated with geofence area 308. As another example, one or more positioning techniques may include, but are not limited to, signal triangulation, GPS signaling, and map matching algorithms.

[0055] In one or more examples, vehicle 102 (e.g., and / or one or more auxiliary vehicles 142) is configured to perform one or more actions corresponding to a vehicle-specific identification pattern in response to vehicle-side AVM algorithm 122 determining that vehicle 102 (e.g., and / or one or more auxiliary vehicles 142) is within a distance-related threshold from infrastructure system 110. As another example, the one or more actions may include, but are not limited to, light patterns, vehicle movement, window movement, door movement, hatch movement, audio patterns, and / or any other function-related patterns associated with vehicle 102 (e.g., and / or one or more auxiliary vehicles). It should be understood that different actions among the one or more actions may be performed based on the location of vehicle 102 (e.g., and / or one or more auxiliary vehicles 142), ensuring that the execution of one or more actions can be detected by at least one or more sensors 302.

[0056] In one or more examples, and where the vehicle-side AVM algorithm 122 and / or the infrastructure-side AVM algorithm 112 determine that vehicle 102 (e.g., and / or one or more additional vehicles 142) is located outside a distance-related threshold from infrastructure system 110, infrastructure-side AVM algorithm 112 is configured to deploy one or more drones 312 to the location of vehicle 102 (e.g., and / or one or more additional vehicles 142). It should be understood that the number of drones deployed by the infrastructure system can be proportional to the number of vehicles to be autonomously controlled by infrastructure system 110 (e.g., based on any ratio), which prevents authorization bottlenecks during deployment. It should also be understood that one or more drones 312 are configured to acknowledge multiple vehicles simultaneously, wherein the acknowledgment order can depend on a priority list indicating the desired acknowledgment order and / or a prediction of the movement of vehicle 102 (e.g., and / or one or more additional vehicles 142) (e.g., performed by infrastructure-side AVM algorithm 111).

[0057] For example, one or more drones 312 are configured to calibrate the position associated with vehicle 102 (e.g., and / or one or more auxiliary vehicles 142) based on one or more reference points and / or one or more anchor points 306. As another example, one or more drones 312 are also configured to recalibrate the position associated with vehicle 102 (e.g., and / or one or more auxiliary vehicles 142) based on one or more reference points and / or one or more anchor points 306 associated with infrastructure system 110 and a position that may be within a distance-related threshold.

[0058] In one or more examples, when vehicle 102 (e.g., or one or more attached vehicles 142) is within a distance-related threshold, infrastructure system 110 is configured to identify vehicle 102 (e.g., or one or more attached vehicles 142) based on the execution of one or more actions that match a vehicle-specific identification pattern (e.g., by vehicle 102 (e.g., or one or more attached vehicles 142)). In other words, infrastructure-side AVM algorithm 112 is configured to perform one or more image recognition techniques on captured image data received from one or more sensors 302 to determine whether one or more actions match a vehicle-specific identification pattern.

[0059] In one or more examples, and in instances where vehicle 102 (e.g., or one or more attached vehicles 142) is located outside a distance-related threshold, one or more drones 312 are configured to transmit a video stream capturing the execution of one or more actions (by vehicle 102 (e.g., or one or more attached vehicles 142)). As another example, vehicle 102 (e.g., or one or more attached vehicles 142) is configured to perform one or more actions in instances where vehicle 102 (e.g., or one or more attached vehicles 142) is determined (e.g., via vehicle-side AVM algorithm 122) to be within a distance-related threshold from one or more drones 312. In one or more examples, the distance-related threshold can be any predefined distance from one or more drones 312, corresponding to the field of view and / or communication range of one or more drones 312. As another example, infrastructure-side AVM algorithm 112 is also configured to perform one or more image recognition techniques on the video stream received from one or more drones 312 to determine whether one or more actions match a vehicle-specific recognition pattern. As yet another example, the infrastructure-side AVM algorithm 112 is configured to identify the vehicle 102 based on one or more actions that match a vehicle-specific identification pattern. However, it should be understood that one or more drones 312 can determine whether one or more actions match the vehicle-specific identification pattern itself.

[0060] In one or more examples, the infrastructure-side AVM algorithm 112 is configured to authorize vehicle 102 (e.g., and / or one or more attached vehicles 142) in response to confirming the identity of vehicle 102 (e.g., and / or one or more attached vehicles 142). As another example, and provided that vehicle 102 (e.g., and / or one or more attached vehicles 142) has been confirmed by the infrastructure-side AVM algorithm 112, the vehicle-side AVM algorithm 112 is also configured to perform one or more means for confirming the identity of vehicle 102 (e.g., and / or one or more attached vehicles 142), as described herein. It should also be understood that one or more drones 312 may authorize vehicle 102 (e.g., and / or one or more attached vehicles 142).

[0061] In one or more embodiments, and in instances where the identity of vehicle 102 (e.g., and / or one or more additional vehicles 142) is confirmed, vehicle 102 (e.g., and / or one or more additional vehicles 142) is configured to perform one or more additional actions to demonstrate that the online status of vehicle 102 (e.g., and / or one or more additional vehicles 142) is successful. As another example, the one or more additional actions performed by vehicle 102 (e.g., and / or one or more additional vehicles 142) may be the same actions included within one or more actions or actions different from one or more actions.

[0062] In one or more embodiments, and in instances where bringing vehicle 102 (e.g., and / or one or more additional vehicles 142) online is unsuccessful, other methods for bringing vehicle 102 (e.g., and / or one or more additional vehicles 142) online may be implemented, such as drone-based authorization (e.g., if infrastructure-based authorization was initially implemented) and / or manual authorization.

[0063] Figure 4 This is a flowchart illustrating an example method 400 for bringing a vehicle (e.g., vehicle 102 and / or one or more additional vehicles 142) online, as described herein.

[0064] At operation 402, the vehicle is configured to receive an identification pattern from an infrastructure system (e.g., infrastructure system 110). In one or more examples, the identification pattern includes light patterns, vehicle movement, window movement, door movement, cabin door movement, audio patterns, or combinations thereof. As another example, the identification pattern is vehicle-specific.

[0065] At operation 404, the vehicle is also configured (e.g., via vehicle-side AVM algorithm 122) to determine whether the vehicle is within a distance-related threshold from the infrastructure system. In one or more examples, determining whether the vehicle is within the distance-related threshold from the infrastructure includes (e.g., by vehicle-side AVM algorithm 122) performing one or more positioning techniques. As another example, the performance of one or more positioning techniques is based on predetermined geofence-based mapping of the marshalling environment.

[0066] At operation 406, the vehicle is also configured to perform one or more actions. In one or more examples, the execution of one or more actions corresponds to the recognition of a pattern. As another example, one or more actions are performed in response to (e.g., by vehicle-side AVM algorithm 122) determining that the vehicle is within a distance-related threshold from the infrastructure system.

[0067] In one or more embodiments, the vehicle is also configured to cause one or more drones (e.g., one or more drones 312) to be deployed to the vehicle's location and to perform one or more actions. In one or more examples, the deployment of one or more drones is caused based on the execution of one or more positioning technologies. As another example, the deployment of one or more drones is caused in response to determining that the vehicle is outside a distance-related threshold from the infrastructure system. As yet another example, one or more actions are performed in response to the drones being deployed to the vehicle's location.

[0068] In one or more embodiments, the vehicle is configured to perform one or more additional actions. In one or more examples, one or more additional actions are performed to confirm a successful online event associated with the vehicle. As another example, the one or more additional actions differ from the stated one or more actions.

[0069] Figure 5 This is a flowchart illustrating another example method 500 for bringing a vehicle (e.g., vehicle 102 and / or one or more additional vehicles 142) online, as described herein.

[0070] At operation 502, the vehicle is configured to receive an identification pattern from an infrastructure system (e.g., infrastructure system 110). In one or more examples, the identification pattern includes light patterns, vehicle movement, window movement, door movement, cabin door movement, audio patterns, or combinations thereof. As another example, the identification pattern is vehicle-specific.

[0071] At operation 504, the vehicle is also configured (e.g., via vehicle-side AVM algorithm 122) to determine whether the vehicle is within a distance-related threshold from the infrastructure system. In instances where the vehicle is determined not to be within the distance-related threshold from the infrastructure system, at operation 506, the vehicle is further configured to cause one or more drones (e.g., one or more drones 312) to be deployed to the vehicle's location. In one or more examples, the deployment of one or more drones is caused based on the execution of one or more positioning technologies. Additionally, and in instances where the vehicle is determined not to be within the distance-related threshold from the infrastructure system, at operation 508, the vehicle is further configured to perform one or more actions in response to the deployment of the drones to the vehicle's location.

[0072] However, in instances where the vehicle is determined to be within a distance-related threshold from the infrastructure system, at operation 510, the vehicle is configured to perform one or more actions. In one or more examples, the execution of one or more actions corresponds to the recognition pattern.

[0073] Figure 6 This is a flowchart illustrating yet another example method 600 for bringing a vehicle (e.g., vehicle 102 and / or one or more additional vehicles 142) online, as described herein.

[0074] At operation 602, an infrastructure system (e.g., infrastructure system 110) is configured to assign an identification pattern to a vehicle. In one or more examples, the identification pattern is assigned in response to receiving an online request from the vehicle. As another example, the identification pattern includes light patterns, vehicle movement, window movement, door movement, cabin door movement, audio patterns, or combinations thereof. As yet another example, the identification pattern is vehicle-specific.

[0075] At operation 604, the infrastructure system is also configured to transmit an identification pattern to the vehicle. At operation 606, the infrastructure system is also configured to verify the vehicle's identity. In one or more examples, the vehicle's identity is verified based on the infrastructure system determining that the vehicle is within a distance-related threshold from the infrastructure system and / or performing one or more actions matching the identification pattern. As another example, one or more actions are performed by the vehicle. As yet another example, one or more actions are performed in response to (e.g., by the vehicle) receiving the identification pattern.

[0076] At operation 608, the infrastructure system is also configured to bring the vehicle online. In one or more examples, the vehicle is brought online in response to the infrastructure system confirming the vehicle's identity.

[0077] In one or more embodiments, the infrastructure system is configured to receive one or more messages from the vehicle and deploy one or more drones to the location of the vehicle. In one or more examples, the one or more messages indicate that the vehicle is outside a distance-related threshold from the infrastructure system. As another example, one or more drones are deployed in response to receiving one or more messages.

[0078] In one or more embodiments, the infrastructure system is also configured to receive a video stream, perform one or more image recognition techniques, and determine whether one or more actions match a recognition pattern. In one or more examples, a video stream is received from one or more drones. As another example, one or more image recognition techniques are performed in response to receiving the video stream. As yet another example, a determination of whether one or more actions match a recognition pattern is performed in response to performing one or more image recognition techniques. As yet another example, one or more image recognition techniques are performed based on the field of view of one or more sensors of the infrastructure system (e.g., one or more sensors 302).

[0079] Figure 7 This is a flowchart illustrating another example method 700 for bringing a vehicle (e.g., vehicle 102 and / or one or more additional vehicles 142) online, as described herein.

[0080] At operation 702, an infrastructure system (e.g., infrastructure system 110) is configured to assign an identification pattern to a vehicle. In one or more examples, the identification pattern is assigned in response to receiving an online request from the vehicle. As another example, the identification pattern includes light patterns, vehicle movement, window movement, door movement, cabin door movement, audio patterns, or combinations thereof. As yet another example, the identification pattern is vehicle-specific.

[0081] At operation 704, the infrastructure system is also configured to transmit an identification pattern to the vehicle. At operation 706, the infrastructure system is also configured to (e.g., via infrastructure-side AVM algorithm 112) determine whether the vehicle is within a distance-related threshold from the infrastructure system. In an instance where the vehicle is determined to be within the distance-related threshold from the infrastructure system, at operation 708, the infrastructure system is configured to verify the vehicle's identity. In one or more examples, the vehicle's identity is verified based on the infrastructure system determining that the vehicle is within the distance-related threshold from the infrastructure system and / or performing one or more actions matching the identification pattern. As another example, one or more actions are performed by the vehicle. As yet another example, one or more actions are performed in response to (e.g., by the vehicle) receiving the identification pattern. Additionally, and in an instance where the vehicle is determined to be within the distance-related threshold from the infrastructure system, at operation 710, the infrastructure system is also configured to bring the vehicle online. In one or more examples, the vehicle is brought online in response to the infrastructure system verifying the vehicle's identity.

[0082] However, in cases where it is determined that the vehicle is not within a distance-related threshold from the infrastructure system, at operation 712, the infrastructure system is configured to deploy one or more drones to the vehicle's location. In one or more examples, one or more drones are deployed in response to receiving one or more messages from the vehicle indicating that the vehicle is outside a distance-related threshold from the infrastructure system.

[0083] Figure 8 An operating environment, such as a computer system, is shown that facilitates the execution of one or more systems and methods described herein. More specifically, the systems and methods described herein can be implemented using computing device 802. For example, computing device 802 can be a personal computer, desktop computer, laptop computer, tablet computer, handheld computer, server, workstation, mainframe, wearable computer, supercomputer, or a combination thereof. However, it should be understood that the foregoing examples of computing device 802 are not exhaustive, and computing device 802 can be any type of processing or computing device. Computing device 802 typically includes a processor 804, a display adapter 806, one or more input / output ports 808, one or more input / output components 810, a network adapter 812, a power supply 814, and memory 816. However, it should be understood that computing device 802 can include any of the listed components, and is not required to include any of them.

[0084] Processor 804 is configured to provide instructions to computing device 802, enabling computing device 802 to perform one or more tasks, including implementing software programs to perform one or more operations as described in more detail herein. It should also be understood that computing device 802 may include any number of processors 804. Display adapter 806 may be a graphics card or video board that provides computing device 802 with the ability to display content on display device 818. For example, display device 818 may be any screen, monitor, and / or light-emitting component associated with any of a personal computer, desktop computer, laptop computer, tablet computer, handheld computer, server, workstation, host, wearable computer, supercomputer, or a combination thereof. However, it should be understood that the foregoing examples of display device 818 are not exhaustive, and display device 818 may be any type of device capable of providing visual display.

[0085] Input / output port 808 provides multiple interfaces (e.g., jacks) for one or more cables to connect to computing device 802. It should be understood that any number of input / output ports 808 may be present on computing device 802. For example, input / output port 808 provides computing device 802 with means to receive signals and / or data from external devices connected to computing device 802 via one or more cables. As another example, input / output port 808 provides computing device 802 with means to transmit signals and / or data to external devices connected to computing device 802 via one or more cables. Input / output component 810 may include one or more components supporting input / output port 808, such as, but not limited to, switches, buttons, pressure pads, float switches, keyboards, radio receivers, or combinations thereof.

[0086] Network adapter 812 can be any type of network interface controller configured to provide a device for communicating with another computing device (such as remote computing device 822) via network 820. For example, remote computing device 822 can be a user device such as a cellular phone, smartphone, tablet computer, laptop computer, or a combination thereof. Power supply 814 is configured to convert alternating high-voltage current (e.g., AC) into direct current (e.g., DC) to provide power to other components of computing device 802 (e.g., processor 804, display adapter 806, one or more input / output ports 808, one or more input / output components 810, network adapter 812, and memory 816).

[0087] Additionally, memory 816 may be a mass storage device and / or system memory, such as a hard disk drive, memory card, solid-state drive, random access memory (RAM), or a combination thereof. Memory 816 is configured to provide storage for instructions and data associated with the operation of computing device 802. Memory 816 may typically include operating system 824, online software 826, and online data 828. For example, operating system 824 is configured to manage and / or process any of the data and / or instructions associated with online software 826 and / or online data 828, such as bringing one or more vehicles online, as described in more detail herein.

[0088] Furthermore, a system bus 830 is also included within the computing device 802, configured to connect each of the various components of the computing device 802 (e.g., processor 804, display adapter 806, one or more input / output ports 808, one or more input / output components 810, network adapter 812, power supply 814, and memory 816). It should also be understood that the functions associated with each component of the computing device 802 and with each component of the computing device 802 can be implemented within a remote computing device 822. Although Figure 8 The operating environment shown herein depicts a specific configuration associated with at least computing device 802, network 820, and remote computing device 822; however, it should be understood that the operating environment can be configured in any manner.

[0089] Therefore, one or more examples of this disclosure provide an apparatus for bringing vehicles online based on a fully customizable and vehicle-specific pattern, which, if recognizable by a central server (e.g., infrastructure system 110) and / or drones (e.g., one or more drones 312), can enable vehicles to be accurately brought online within a grouping system.

[0090] Unless otherwise expressly indicated herein, all numerical values ​​indicating mechanical / thermal properties, percentage of composition, dimensions and / or tolerances or other characteristics should be understood as being modified by the words “about” or “approximately” when describing the scope of this disclosure. Such modification is desired for various reasons, including: industrial practice; material, manufacturing and assembly tolerances; and testing capabilities.

[0091] As used herein, the phrases A, B, and C at least one should be interpreted as representing logic (A or B or C) using the non-exclusive logic "or", and should not be interpreted as representing "at least one of A, at least one of B, and at least one of C".

[0092] In this application, the terms “controller” and / or “module” may refer to, be part of, or include the following: application-specific integrated circuit (ASIC); digital, analog, or mixed analog / digital discrete circuit; digital, analog, or mixed analog / digital integrated circuit; composable logic circuit; field-programmable gate array (FPGA); processor circuitry (shared, dedicated, or grouped) that executes code; memory circuitry (shared, dedicated, or grouped) that stores code executed by the processor circuitry; other suitable hardware components that provide the described functionality; or combinations of some or all of the foregoing, such as in a system-on-a-chip.

[0093] The term memory is a subset of the term computer-readable medium. As used herein, the term computer-readable medium does not cover transient electrical or electromagnetic signals propagated through a medium (such as on a carrier wave); therefore, the term computer-readable medium can be considered tangible and non-transient. Non-limiting examples of non-transient tangible computer-readable media include non-volatile memory circuits (such as flash memory circuits, erasable programmable read-only memory circuits, or mask read-only circuits), volatile memory circuits (such as static random access memory circuits or dynamic random access memory circuits), magnetic storage media (such as analog magnetic tape or digital magnetic tape or hard disk drives), and optical storage media (such as CDs, DVDs, or Blu-ray discs).

[0094] The apparatus and methods described in this application can be implemented, in part or in whole, by a dedicated computer created by configuring a general-purpose computer to perform one or more specific functions embodied in a computer program. Function blocks, flowchart components, and other elements described above serve as software specifications that can be translated into computer programs through the routine work of a technician or programmer.

[0095] The description in this disclosure is merely exemplary in nature, and therefore, variations without departing from the spirit and scope of this disclosure are intended to be made within its scope. Such variations should not be considered as departing from the spirit and scope of this disclosure.

[0096] According to the present invention, a method for bringing a vehicle online includes: assigning an identification pattern to the vehicle in response to receiving an online request from the vehicle; transmitting the identification pattern to the vehicle; verifying the identity of the vehicle based on determining that the vehicle is within a distance-related threshold from an infrastructure system and the execution of one or more actions matching the identification pattern, wherein the one or more actions are performed by the vehicle in response to receiving the identification pattern; and bringing the vehicle online in response to verifying the identity of the vehicle.

[0097] In one aspect of the invention, the identification pattern includes a light pattern, vehicle movement, window movement, door movement, cabin door movement, audio pattern, or a combination thereof.

[0098] In one aspect of the invention, the identification pattern is unique to the vehicle.

[0099] In one aspect of the invention, the method includes: receiving from a vehicle one or more messages indicating that the vehicle is located outside a distance-related threshold from an infrastructure system; and deploying one or more drones to the location of the vehicle in response to receiving the one or more messages.

[0100] In one aspect of the invention, the method includes: receiving a video stream from the one or more drones; performing one or more image recognition techniques in response to receiving the video stream; and determining whether the one or more actions match the recognition pattern in response to performing the one or more image recognition techniques.

[0101] In one aspect of the invention, the method includes: performing one or more image recognition techniques based on the field of view of one or more sensors of an infrastructure system; and determining, in response to performing the one or more image recognition techniques, whether the one or more actions match the recognition pattern.

Claims

1. A method for putting a vehicle into service, the method comprising: The vehicle receives an identification pattern from the infrastructure system. Determine whether the vehicle is within a distance-related threshold from the infrastructure system; as well as In response to determining that the vehicle is within the distance-related threshold of the infrastructure system, one or more actions corresponding to the identification pattern are performed.

2. The method of claim 1, wherein the identification pattern includes a light pattern, vehicle movement, window movement, door movement, cabin movement, audio pattern, or a combination thereof.

3. The method of claim 1, wherein the identification pattern is unique to the vehicle.

4. The method of claim 1, wherein determining whether the vehicle is within the distance-related threshold from the infrastructure system further comprises: One or more positioning techniques are performed based on pre-defined geofencing mapping of the grouped environment.

5. The method of claim 4, further comprising: Based on the execution of the one or more positioning technologies, in response to determining that the vehicle is outside the distance-related threshold from the infrastructure system, one or more drones are deployed to the location of the vehicle; as well as The one or more actions are performed in response to the deployment of the one or more drones to the location of the vehicle.

6. The method of claim 1, further comprising: Perform one or more additional actions to confirm a successful online event associated with the vehicle, wherein the one or more additional actions are different from the one or more actions.

7. A system for putting vehicles into service, the system comprising: The vehicle system is configured to: Transmitting the online request, Receive the vehicle's unique identification pattern. Determine whether the vehicle associated with the vehicle system is located within a distance-related threshold from the infrastructure system, and In response to determining that the vehicle is within the distance-related threshold of the infrastructure system, one or more actions corresponding to the identification pattern are performed; and The infrastructure system is configured as follows: In response to receiving the online request, the identification pattern is assigned to the vehicle. Transmit the identification pattern, The vehicle's identity is confirmed based on the execution of one or more actions that match the recognition pattern. The vehicle is brought online in response to confirmation of its identity.

8. The system of claim 7, wherein the recognition pattern includes a light pattern, vehicle movement, window movement, door movement, cabin movement, audio pattern, or a combination thereof.

9. The system of claim 7, wherein the vehicle system configured to determine whether the vehicle is within the distance-related threshold of the infrastructure system is further configured to: One or more positioning techniques are performed based on pre-defined geofencing mapping of the grouped environment.

10. The system of claim 9, wherein the vehicle system is further configured to: Based on the execution of the one or more positioning technologies, in response to determining that the vehicle is outside the distance-related threshold from the infrastructure system, one or more drones are deployed to the location of the vehicle; and The one or more actions are performed in response to the deployment of the one or more drones to the location of the vehicle.

11. The system of claim 7, wherein the infrastructure system is further configured to: Receive from the vehicle system one or more messages indicating that the vehicle is outside the distance-related threshold of the infrastructure system; and In response to receiving the one or more messages, one or more drones are deployed to the location of the vehicle.

12. The system of claim 11, wherein the infrastructure system is further configured to: Receive video streams from the one or more drones; In response to the receipt of the video stream, one or more image recognition techniques are performed; and In response to the execution of the one or more image recognition techniques, it is determined whether the one or more actions match the recognition pattern.

13. The system of claim 7, wherein the infrastructure system is further configured to: One or more image recognition techniques are performed based on the field of view of one or more sensors of the infrastructure system; and In response to the execution of the one or more image recognition techniques, it is determined whether the one or more actions match the recognition pattern.

14. The system of claim 7, wherein the vehicle system is further configured to: Perform one or more additional actions to confirm a successful online event associated with the vehicle, wherein the one or more additional actions are different from the one or more actions.

Images