System and method for detecting, analyzing, and notifying wireless key performance indicator evaluation

Abstract

The invention provides a system and a method for detecting, analyzing and notifying wireless key performance index evaluation. A method includes calculating at least one metric corresponding to one or more key performance metrics associated with one or more messages exchanged between a vehicle and an infrastructure system; detecting one or more communication-based interruptions associated with the one or more messages based on the analysis of the at least one metric; and initiating a remedial action based on the one or more communication-based interruptions and the adjustments to the one or more marshalling commands.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to marshalling vehicles. More specifically, the present disclosure relates to marshalling vehicles based on one or more key performance indicator influences. BACKGROUND

[0002] The statements in this section merely provide background information related to the present disclosure and can not constitute prior art.

[0003] Wireless communication systems facilitate efficient operation of autonomous vehicles. For example, vehicle routing and control has been performed using over-the-air vision systems that include a central server. However, such routing of vehicles is dependent on timely and reliable wireless communication and can be impacted by, for example, network congestion, packet delay, interference, and / or signal degradation. The very nature of radio frequency based interference further makes it difficult to diagnose and resolve communication related problems in a proactive manner. The present disclosure addresses these and other issues related to vehicle marshalling with at least these factors in mind. SUMMARY

[0004] This section provides a general summary of the present disclosure and is not a comprehensive disclosure of its full scope or all of its features.

[0005] The present disclosure provides a method comprising: calculating at least one metric corresponding to one or more key performance indicators associated with one or more messages exchanged between a vehicle and an infrastructure system; detecting, by a vehicle-side algorithm, one or more communication-based disruptions associated with the one or more messages based on an analysis of the at least one metric; and initiating a remedial action based on the one or more communication-based disruptions and an adjustment to one or more marshalling commands; wherein the one or more key performance indicators comprise a packet error rate, an inter-packet gap, a latency, a transmission time interval, a data rate, or a combination thereof; wherein the one or more messages comprise an infrastructure marshalling message (IMM) query, a vehicle marshalling message (VMM) alert, an IMM query response, and a VMM alert response, and wherein: a first networking layer and a first application layer correspond to the IMM query and the VMM alert, and wherein the first networking layer comprises a rolling header counter for randomized IMM requests, a rolling header counter for randomized VMM requests, a timestamp, or a combination thereof, and further wherein the first application layer comprises one or more VMM-related data elements associated with the vehicle, a sequentially randomized rolling counter for VMM transmissions associated with the vehicle, a rolling counter for IMM receptions associated with the infrastructure system, a VMM generation time, a time confidence, or a combination thereof; and a second networking layer and a second application layer correspond to the IMM query response and the VMM alert response, and wherein the second networking layer comprises an IMM response rolling header matching the IMM query, a VMM response alert rolling header counter matching the VMM alert, a timestamp, or a combination thereof, and further wherein the second application layer comprises one or more IMM-related data elements associated with the vehicle, a sequentially randomized rolling counter for IMM transmissions associated with the infrastructure system, a rolling counter for VMM receptions associated with the vehicle, an IMM generation time, a time confidence, or a combination thereof; wherein the detection of the at least one metric further comprises: measuring a percentage of lost packets over a second time interval associated with the exchange of the one or more messages; monitoring a time interval between consecutive packets received at the vehicle; calculating a time taken to successfully exchange the one or more messages; measuring a time interval between consecutive packet transmissions associated with the one or more messages; or verifying a simultaneous exchange of the one or more messages; wherein the analysis of the at least one metric further comprises: dynamically estimating a communication-related delay associated with the exchanged one or more messages; or dynamically estimating a missed message in the exchanged one or more messages; further comprising: initiating a trigger associated with a low-speed automation of the vehicle based on the analysis of the at least one metric; and wherein the initiation of the remedial action further comprises: initiating a stop procedure associated with the vehicle; receiving the adjustment to the one or more marshalling commands from the infrastructure system;or causing generation of a timestamp and a virtual dynamic radio frequency coverage heat map associated with the grouping environment, wherein the virtual dynamic radio frequency coverage heat map is generated in response to a verification of the vehicle's location based on a match of coordinates of the vehicle's location to snapshot data associated with the vehicle's location.

[0006] The present disclosure provides a system comprising: a vehicle system configured to: compute at least one metric corresponding to one or more key performance indicators associated with one or more messages exchanged between a vehicle and an infrastructure system; detect, by a vehicle-side algorithm, one or more communication-based disruptions associated with the one or more messages based on an analysis of the at least one metric; and initiate a remedial action based on the one or more communication-based disruptions and an adjustment to one or more marshalling commands; an infrastructure system configured to: transmit, to the vehicle, the adjustment to the one or more marshalling commands in response to receiving the analysis of the at least one metric; and a cloud system configured to: cause generation of a timestamp and a virtual dynamic radio frequency coverage heat map associated with a marshalling environment, wherein the virtual dynamic radio frequency coverage heat map is generated in response to a verification of a location of the vehicle based on coordinates of the location of the vehicle matching snapshot data associated with the location of the vehicle; wherein the one or more key performance indicators comprise a packet error rate, an inter-packet gap, a latency, a transmission time interval, a data rate, or a combination thereof; wherein the one or more messages comprise an infrastructure marshalling message (IMM) query, a vehicle marshalling message (VMM) alert, an IMM query response, and a VMM alert response, and wherein: a first networking layer and a first application layer correspond to the IMM query and the VMM alert, and wherein the first networking layer comprises a rolling header counter for randomized IMM requests, a rolling header counter for randomized VMM requests, a timestamp, or a combination thereof, and further wherein the first application layer comprises one or more VMM-related data elements associated with the vehicle, a sequentially randomized rolling counter for VMM transmissions associated with the vehicle, a rolling counter for IMM receptions associated with the infrastructure system, a VMM generation time, a time confidence, or a combination thereof; and a second networking layer and a second application layer correspond to the IMM query response and the VMM alert response, and wherein the second networking layer comprises an IMM response rolling header matching the IMM query, a VMM response alert rolling header counter matching the VMM alert, a timestamp, or a combination thereof, and further wherein the second application layer comprises one or more IMM-related data elements associated with the vehicle, a sequentially randomized rolling counter for IMM transmissions associated with the infrastructure system, a rolling counter for VMM receptions associated with the vehicle, an IMM generation time, a time confidence, or a combination thereof; wherein the vehicle system configured to detect the at least one metric is further configured to: measure a percentage of lost packets over a second time interval associated with the exchange of the one or more messages; monitor a time interval between consecutive packets received at the vehicle; compute a time taken to successfully exchange the one or more messages; measure a time interval between consecutive packet transmissions associated with the one or more messages; or verify a simultaneous exchange of the one or more messages;wherein the vehicle system configured to analyze the at least one metric is further configured to: dynamically estimate a communication-related delay associated with the one or more messages exchanged; or dynamically estimate a missed message of the one or more messages exchanged; and wherein the vehicle system is further configured to: initiate a trigger associated with a low-speed automation of the vehicle based on the analysis of the at least one metric.

[0007] The present disclosure provides one or more non-transitory computer-readable media storing processor-executable instructions that, when executed by at least one processor, cause the at least one processor to: calculate at least one metric corresponding to one or more key performance indicators associated with one or more messages exchanged between a vehicle and an infrastructure system; detect, by a vehicle-side algorithm, one or more communication-based disruptions associated with the one or more messages based on an analysis of the at least one metric; and initiate a remedial action based on the one or more communication-based disruptions and an adjustment to one or more marshalling commands; wherein the one or more key performance indicators include a packet error rate, an inter-packet gap, a latency, a transmission time interval, a data rate, or a combination thereof; wherein the one or more messages include an infrastructure marshalling message (IMM) query, a vehicle marshalling message (VMM) alert, an IMM query response, and a VMM alert response, and wherein: a first networking layer and a first application layer correspond to the IMM query and the VMM alert, and wherein the first networking layer includes a rolling header counter for randomized IMM requests, a rolling header counter for randomized VMM requests, a timestamp, or a combination thereof, and further wherein the first application layer includes one or more VMM-related data elements associated with the vehicle, a sequentially randomized rolling counter for VMM transmissions associated with the vehicle, a rolling counter for IMM receptions associated with the infrastructure system, a VMM generation time, a time confidence, or a combination thereof; and a second networking layer and a second application layer correspond to the IMM query response and the VMM alert response, and wherein the second networking layer includes an IMM response rolling header matching the IMM query, a VMM response alert rolling header counter matching the VMM alert, a timestamp, or a combination thereof, and further wherein the second application layer includes one or more IMM-related data elements associated with the vehicle, a sequentially randomized rolling counter for IMM transmissions associated with the infrastructure system, a rolling counter for VMM receptions associated with the vehicle, an IMM generation time, a time confidence, or a combination thereof; wherein the at least one processor caused to detect the at least one metric is further caused to: measure a percentage of lost packets over a second time interval associated with the exchange of the one or more messages; monitor a time interval between consecutive packets received at the vehicle; calculate a time taken to successfully exchange the one or more messages; measure a time interval between consecutive packet transmissions associated with the one or more messages; or verify a simultaneous exchange of the one or more messages; wherein the at least one processor caused to analyze the at least one metric is further caused to: dynamically estimate a communication-related delay associated with the exchanged one or more messages; or dynamically estimate a missed message in the exchanged one or more messages; wherein the at least one processor is further caused to: initiate a trigger associated with a low-speed automation of the vehicle based on the analysis of the at least one metric;And wherein the at least one processor caused to initiate the remedial action is further caused to: initiate a stop procedure associated with the vehicle; receive an adjustment to one or more marshaling commands from the infrastructure system; or cause generation of a timestamp and a virtual dynamic radio frequency coverage heat map associated with the marshaling environment, wherein the virtual dynamic radio frequency coverage heat map is generated in response to a verification that coordinates based on the location of the vehicle match snapshot data associated with the location of the vehicle.

[0008] Further areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0009] So that the disclosure can be well understood, various forms thereof will now be described, by way of example, with reference to the drawings in which:

[0010] Figure 1 A system for automated vehicle marshaling is shown in accordance with one or more embodiments of the present disclosure;

[0011] Figure 2 An example vehicle assigned by the system shown in accordance with one or more embodiments of the present disclosure; Figure 1

[0012] Figure 3 A system for detecting, analyzing, and / or notifying of wireless key performance indicator evaluations is shown in accordance with one or more embodiments of the present disclosure;

[0013] Figure 4 A flow diagram showing an example method for detecting, analyzing, and / or notifying of real-time wireless key performance indicator impacts associated with wireless communications between a vehicle and an infrastructure system is shown in accordance with one or more embodiments of the present disclosure;

[0014] Figures 5 to 7 A message exchange between a vehicle and an infrastructure system is shown in accordance with one or more embodiments of the present disclosure; and

[0015] Figure 8 is a block diagram showing an example computer system in accordance with one or more embodiments of the present disclosure.

[0016] The drawings described herein are for purposes of illustration only and are not intended to limit the scope of the present disclosure in any way. DETAILED DESCRIPTION

[0017] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features. ​

[0018] One or more examples described herein provide an enhanced means for detecting, analyzing, and / or notifying of real-time wireless key performance indicator (KPI) impacts. One or more embodiments allow for detailed analysis of the performance of a communication system on infrastructure marshaling messages (IMMs) and vehicle marshaling messages (VMMs) by implementing a thorough understanding of potential bottlenecks and / or areas of a marshaling environment (e.g., a factory floor or a parking lot) to enhance relative to each message type’s communication. In further one or more embodiments, valuable insights into the reliability of one or more communication channels are provided. For example, information associated with these insights can be used to identify potential issues related to packet loss and / or transmission errors, enabling proactive measures to enhance the overall performance of the communication system.

[0019] In further one or more embodiments, correlation analysis between one or more metrics (e.g., latency-related metrics and / or packet error rate-related metrics) facilitates the identification of potential relationships between latency and packet loss, enabling a deeper understanding of one or more factors that can be causing communication performance issues. In further one or more embodiments, by separating data associated with IMMs and VMMs, targeted optimization efforts can be provided. For example, if one message type exhibits higher latency or packet error rate issues, specific measures can be taken to address these issues without impacting the performance of the other message type.

[0020] In one or more embodiments, by providing a modular approach that separately tracks different metrics and message types, scalability is enhanced. For example, additional message types and / or performance metrics can be easily incorporated into the communication system without requiring significant modifications to existing data structures and / or analysis processes. In further one or more embodiments, various timestamps can be tracked throughout the communication process. For example, the various timestamps can be used to analyze the timing of different events and accurately calculate latency. In further one or more embodiments, one or more counters are used to track infrastructure maneuver message requests and / or response headers. For example, the counters can help identify any potential message loss and / or sequencing issues.

[0021] In one or more embodiments, the data rate at which IMM queries and VMM alert messages are exchanged between the automated vehicle and the infrastructure system is monitored. For example, information associated with the data rate can be useful for optimizing the communication system and ensuring efficient data transfer. In further one or more embodiments, the secure hypertext transfer protocol (HTTPS) status of the IMM and VMM is tracked. For example, information associated with the tracked HTTPS status can facilitate troubleshooting and / or identify potential issues related to the HTTPS communication layer. In still further one or more embodiments, the time taken for a data request can be tracked. For example, information associated with the tracked time can help identify potential delays and / or bottlenecks in the data request process. In further one or more embodiments, a real-time virtual heat map of network connectivity reported by vehicles can be provided, which is continuously updated during automated marshalling of vehicles within a marshalling environment. For example, creating a real-time connectivity feedback mechanism for customers results in increased reliability and / or uptime.

[0022] Figure 1 A schematic block diagram of an automated vehicle marshalling (AVM) system 100 is shown. In one or more examples, the AVM system 100 marshals one or more vehicles (e.g., vehicle 102) that are traveling at low speeds. However, it should be appreciated that the AVM system 100 can marshal one or more vehicles that are traveling at any speed. It should also be appreciated that the AVM system 100 can marshal semi-autonomous vehicles and / or fully autonomous vehicles.

[0023] The AVM system 100 generally includes a vehicle 102, a vehicle manufacturing cloud system 104, a vehicle delivery manager cloud system 106, a vehicle customer web portal account cloud system 108, and an infrastructure system 110. The vehicle manufacturing cloud system 104 operates as a central cloud system that manages and / or facilitates any manufacturing processes associated with the vehicle 102. The vehicle manufacturing cloud system 104 is configured to wirelessly communicate with the vehicle delivery manager cloud system 106 and / or the infrastructure system 110. The vehicle manufacturing cloud system 104 is also configured to wirelessly communicate with the vehicle 102.

[0024] The vehicle manufacturing cloud system 104 can include an infrastructure-side AVM algorithm 112. The infrastructure-side AVM algorithm 112 processes status information associated with at least the vehicle 102 of the one or more vehicles. It should be understood that the infrastructure-side AVM algorithm 112 processes status information associated with each of the one or more vehicles (e.g., the vehicle 102). The vehicle manufacturing cloud system 104 is configured to cause the infrastructure system 110 to monitor the progress of the one or more vehicles (e.g., the vehicle 102) as the vehicles progress through the marshaling environment. The vehicle manufacturing cloud system 104 is further configured to cause the infrastructure system 110 to communicate with the 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 to process information received from the infrastructure system 110. The vehicle manufacturing cloud system 104 is further configured to cause the vehicle delivery manager cloud system 106 to facilitate the delivery of the one or more vehicles (e.g., the 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 to process information received from the vehicle delivery manager cloud system 106.

[0025] The vehicle manufacturing cloud system 104 is further configured to communicate directly with the one or more vehicles to cause the one or more vehicles to begin, stop, or pause progress through the marshaling environment. The vehicle manufacturing cloud system 104 is further configured to control the marshaling speed of the one or more vehicles as the vehicles travel through (e.g., traverse) the marshaling environment. For example, the vehicle manufacturing cloud system 104 utilizes the infrastructure-side AVM algorithm 112 to send instructions to the vehicle 102 and / or to process information received from the vehicle 102.

[0026] The infrastructure system 110 includes a sensor component 114, a wireless communication component 116, a multi-access edge computing (MEC) system 118, and one or more traffic signals 120. It should be understood that the MEC system 118 is configured to support communication between the wireless communication component 116 and the vehicle 102. However, it should be understood that the MEC system 118 is further configured to support communication between the wireless communication component 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 component 116 can utilize GPS, Wi-Fi, satellite, 3G / 4G / 5G, and / or Bluetooth TM to communicate with the one or more vehicles.

[0027] The wireless communication component 116 also communicates with a sensor component 114 configured to manage one or more of, for example, a camera, a lidar, a radar, and / or an ultrasonic device. The sensor component 114 monitors movement of the vehicle(s) as the vehicle(s) are platooned through the platooning environment. Additionally, the wireless communication component 116 also communicates with a traffic light 120. For example, the wireless communication component 116 can cause the traffic light 120 to direct traffic of the vehicle(s) as the vehicle(s) are platooned through the platooning environment. 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.

[0028] The 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 global navigation satellite (e.g., GNSS) 134, a vehicle navigation mapping system 136, and a controller area network (CAN) vehicle bus 138. The wireless transmission module 124 can be a transmission control unit (TCU) and / or can be supported by a telematics supported subsystem. The wireless transmission module 124 includes one or more sensors configured to collect data and send signals to other components of the vehicle 102. The one or more sensors of the wireless transmission module 124 can include a vehicle speed sensor (not shown) configured to determine a 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 needed in a current state of the vehicle 102, and / or a turbo speed sensor (not shown) configured to send data associated with a speed of a torque converter of the vehicle 102.

[0029] The wireless transmission module 124 communicates information collected by the one or more sensors to the vehicle-side AVM algorithm 122. In one embodiment, the vehicle-side AVM algorithm 122 can be disposed as a component within the wireless transmission module 124. For example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information collected by the one or more sensors and send the information to the infrastructure system 110. As another example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information collected by the one or more sensors and send the information directly to the vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to communicate information and / or instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to the wireless transmission module 124.

[0030] The vehicle central gateway module 126 operates as an interface between various vehicle domain bus systems, such as an engine bay bus (not shown), an interior bus (not shown), an optical bus for multimedia (not shown), a diagnostic bus for maintenance (not shown), or a vehicle CAN bus 138. The vehicle central gateway module 126 is configured to distribute data communicated to the vehicle central gateway module 126 by 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 utilizes the vehicle-side AVM algorithm 122 to process information received from the vehicle central gateway module 126 and send the information to the infrastructure system 110. As another example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received from the vehicle central gateway module 126 and send the information directly to the vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to communicate 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.

[0031] The vehicle infotainment system 128 delivers a combination of information and entertainment content and / or services to the user 140 of the vehicle 102. It should be appreciated that in some examples, the vehicle infotainment system 128 can deliver only entertainment content to the user 140 of the vehicle 102. It should also be appreciated that in other examples, the vehicle infotainment system 128 can deliver information services to anyone associated with the vehicle 102. As an example, the vehicle infotainment system 128 includes a built-in car 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 communicates information associated with the built-in car computer or processor to the vehicle-side AVM algorithm 122. For example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received from the vehicle infotainment system 128 and send the information to the infrastructure system 110. As another example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received from the vehicle infotainment system 128 and send the information directly to the vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to communicate information and / or instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to the vehicle infotainment system 128.

[0032] The one or more vehicle sensors 130 can be, for example, one or more of a camera, a lidar, a radar, and / or an ultrasonic device. For example, an ultrasonic device used as the one or more vehicle sensors 130 emits high-frequency sound waves that hit an object (e.g., a wall or another vehicle) and are then reflected back to the vehicle 102. Based on the amount of time it takes for the sound waves to return to the vehicle 102, the vehicle 102 can determine the distance between the one or more vehicle sensors 130 and the object. As another example, a camera device used as the one or more vehicle sensors 130 provides a visual indication of the space around the vehicle 102. As an additional example, a radar device used as the one or more vehicle sensors 130 emits electromagnetic wave signals that hit an object and are then reflected back to the vehicle 102. Based on the amount of time it takes for the electromagnetic waves to return to the vehicle 102, the vehicle 102 can determine the range, speed, and angle of the vehicle 102 relative to the object.

[0033] The one or more vehicle sensors 130 communicate information associated with the position and / or distance of the vehicle 102 relative to the object to the vehicle-side AVM algorithm 122. For example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received from the one or more vehicle sensors 130 and transmit the information to the infrastructure system 110. As another example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received from the one or more vehicle sensors 130 and transmit the information directly to the vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to communicate information and / or instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to the one or more vehicle sensors 130.

[0034] The vehicle battery 132 is controlled by a battery management system (not shown) that provides instructions to the vehicle battery 132. For example, the battery management system provides instructions to the vehicle battery 132 based on the temperature of the vehicle battery 132. However, it should be understood that the battery management system can provide instructions to the vehicle battery 132 based on any metric associated with the vehicle battery 132, such as the power state of the vehicle 102, the period of time during at least one day that the vehicle 102 is in an off state, or a combination thereof. The battery management system ensures that the current pattern of the vehicle battery 132 is acceptable. For example, the acceptable current pattern prevents overvoltage, overcharging, and / or overheating of the vehicle battery 132. As another example, the temperature of the vehicle battery 132 indicates to the battery management system whether any of the acceptable current patterns are within an acceptable temperature range. The battery management system associated with the vehicle battery 132 communicates information associated with the temperature of the vehicle battery 132 to the vehicle-side AVM algorithm 122. For example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received about the vehicle battery 132 and transmit the information to the infrastructure system 110. As another example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information about the vehicle battery 132 and transmit the information directly to the vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to communicate information and / or instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to the vehicle battery 132.

[0035] The vehicle GNSS 134 is configured to communicate with satellites such that the vehicle 102 can determine a specific location of the vehicle 102. The vehicle navigation mapping system 136 can display the specific location of the vehicle 102 to a user 140 via a display screen (not shown). The vehicle GNSS 134 communicates geographic information associated with the vehicle 102 to the vehicle-side AVM algorithm 122. For example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information received from the vehicle GNSS 134 and send the information to the infrastructure system 110. As another example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information from the vehicle GNSS 134 and send the information directly to the vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to communicate information and / or instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to the vehicle GNSS 134. As another example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information associated with the vehicle navigation mapping system 136 and send the information to the infrastructure system 110. As another example, the vehicle 102 utilizes the vehicle-side AVM algorithm 122 to process information from the vehicle navigation mapping system 136 and send the information directly to the vehicle manufacturing cloud system 104. The vehicle-side AVM algorithm 122 is configured to communicate information and / or instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to the vehicle navigation mapping system 136.

[0036] The vehicle 102 is configured to communicate any information associated with any components included within the vehicle 102 to one or more additional vehicles 142. The vehicle 102 is also configured to communicate (e.g., forward) any instructions received from the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 to any of the one or more additional vehicles 142. For example, the communication of the vehicle 102 with the one or more additional vehicles 142 can assist the infrastructure system 110 and / or the vehicle manufacturing cloud system 104 in grouping the one or more additional vehicles 142. It should be appreciated that each of the one or more additional vehicles 142 can include any of the components described as included within the vehicle 102, such as, for example, a vehicle-side AVM algorithm, a wireless transmission module, a vehicle central gateway module, a vehicle infotainment system, one or more vehicle sensors, a vehicle battery, a vehicle GNSS system, a vehicle navigation mapping system, and / or a CAN vehicle bus. It should also be appreciated that any of the one or more additional vehicles 142 are configured to communicate information associated with any components included within the vehicle 102. It should also be appreciated that the one or more additional vehicles 142 can also be configured to establish a direct wireless communication link (e.g., via a communication link) with the infrastructure system 110 and / or the vehicle manufacturing cloud system 104, whereby information can be exchanged directly between the one or more additional vehicles 142 and the infrastructure system 110 and / or the vehicle manufacturing cloud system 104.

[0037] The vehicle delivery manager cloud system 106 is in wireless communication (e.g., receiving and / or sending instructions and / or information) with one or more of a rental agency cloud system 144, a valet parking agency cloud system 146, an insurance agency cloud system 148, and / or a dealer system 150. The vehicle delivery manager cloud system 106 is configured to facilitate the delivery of one or more vehicles to a rental agency (not shown) associated with the rental agency cloud system 144, a valet parking agency (not shown) associated with the valet parking agency cloud system 146, an insurance agency (not shown) associated with the insurance agency cloud system 148, and / or any of the dealer system 150. The vehicle delivery manager cloud system 106 is also in wireless communication with the vehicle customer web portal account cloud system 108. It should be appreciated that other cloud systems can be included in one or more examples.

[0038] The delivery manager cloud system 106 is in wireless communication with a user device 152, such as a mobile device, a display panel, and / or a computer. The vehicle 102 is also configured to wirelessly communicate directly with the user device 152. For example, the user 140 interfaces 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 can 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 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 dealer system 150.

[0039] Reference is made to Figure 2 In various forms, the vehicle 102 can be powered in various ways, such as with an electric motor and / or an internal combustion engine. It should be understood that the vehicle 102 can be any type of vehicle powered by an electric motor and / or an internal combustion engine, such as an automobile, a truck, a robot, an airplane, and / or a boat. The vehicle 102 generally includes a vehicle controller 200, one or more actuators 202, a plurality of on-board sensors 204, a human-machine interface (HMI) 206, and vehicle systems 208. The vehicle 102 also has a reference point 210, which is a designated point within a space defined by the vehicle body that identifies a location of the vehicle 102. For example, the reference point 210 is a geometric center point at which respective longitudinal and lateral center axes of the vehicle 102 intersect. As another example, the reference point 210 is a point at which the vehicle 102 is located when the vehicle 102 is navigating toward a waypoint.

[0040] In some examples, the vehicle controller 200 is configured or programmed to control operation of one or more of vehicle braking, propulsion (e.g., to control acceleration of the vehicle 102 by controlling one or more of an internal combustion engine, an electric motor, a hybrid engine, etc.), steering, climate control, interior and / or exterior lights, etc. In other examples, the vehicle controller 200 is also configured or programmed to determine whether and when the vehicle controller 200 (rather than a human operator) controls such operations related to the vehicle 102. It should be understood that any operations associated with the vehicle 102 can be facilitated via an automated, semi-automated, or manual mode. For example, an automated mode can facilitate full control of any operations by the vehicle controller 200 without assistance from a human operator. As another example, a semi-automated mode can facilitate at least partial control of any operations by a human operator in combination with the vehicle controller 200. As a further example, a manual mode can facilitate full control of operations by a human operator without assistance from the vehicle controller 200.

[0041] The 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 can be controllers included in the vehicle 102 for monitoring and / or controlling various vehicle controllers, such as powertrain controllers, brake controllers, steering controllers, etc. The vehicle controller 200 is generally arranged for communication over a vehicle communication network (not shown), which can include a bus in the vehicle 102, such as a controller area network (CAN), etc., and / or other wired and / or wireless mechanisms.

[0042] The vehicle controller 200 transmits messages to and / or receives messages from various devices in the vehicle 102 (e.g., the one or more actuators 202, the HMI 206, etc.) via the vehicle network. Alternatively or additionally, where the vehicle controller 200 includes multiple device sends, the vehicle communication network is used to represent communication between the device sends of the vehicle controller 200 in this disclosure. Further, as discussed below, various other controllers and / or sensors provide data to the vehicle controller 200 via the vehicle communication network.

[0043] Additionally, the vehicle controller 200 is configured for communication over a vehicle-to-infrastructure communication network, such as communication with an infrastructure controller (not shown), via the vehicle-side AVM algorithm 212. The vehicle controller 200 is also configured for communication with other traffic objects (e.g., vehicles, infrastructure, etc.) via a wireless vehicle communication interface, such as via a vehicle-to-vehicle communication network, via the vehicle-side AVM algorithm 212. The vehicle communication network represents one or more mechanisms by which the vehicle controller 200 of the vehicle 102 communicates with other traffic objects. As an example, the vehicle communication network can be one or more of a wireless communication mechanism, 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 when 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), etc.

[0044] The 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. The one or more actuators 202 can be used to control braking, acceleration, and / or steering of the vehicle 102. The vehicle controller 200 can be programmed to activate the one or more actuators 202 (including propulsion, steering, and / or braking actuators) based on a planned acceleration or deceleration of the vehicle 102.

[0045] ​The plurality of on-board sensors 204 includes a variety of devices for providing data to the vehicle controller 200. For example, the plurality of on-board sensors 204 can include object detection sensors (e.g., lidar sensors) disposed on or in the vehicle 102 that provide a relative position, size, and / or shape of one or more objects (such as additional vehicles, bicycles, robots, drones, etc.) traveling alongside, in front of, and / or behind the vehicle 102 around the vehicle 102. As another example, one or more of the plurality of on-board sensors 204 can be radar sensors fixed to one or more bumpers of the vehicle 102 that can provide a position of an object relative to a position of each vehicle 102.

[0046] The plurality of on-board sensors 204 can include camera sensors that provide images from areas around the vehicle 102, for example, to provide a forward view, a side view, a rear view, etc. As another example, the vehicle controller 200 can be programmed to receive sensor data from the camera sensors and implement image processing techniques to detect roads, infrastructure elements, etc. The vehicle controller 200 can also be programmed to determine a current vehicle position based on position coordinates (e.g., GPS coordinates) received from the vehicle 102 indicative of a position of the vehicle 102 determined from a GPS sensor (not shown).

[0047] The HMI 206 is configured to receive information from a human operator during operation of the vehicle 102. Further, the HMI 206 is configured to present information to a human operator, such as an occupant of the vehicle 102. In some variations, the vehicle controller 200 is programmed to receive destination data (e.g., position coordinates) from the HMI 206.

[0048] The vehicle systems 208 are configured to control each of the subsystems within the vehicle 102 and facilitate requests across each of the aforementioned components (e.g., the vehicle controller 200, the one or more actuators 202, the plurality of on-board sensors 204, and / or the HMI 206). Thus, the vehicle 102 can be autonomously directed to a waypoint using at least the plurality of on-board sensors 204. Route selection can be performed using vehicle position, distance traveled, queuing for vehicle platooning, etc.

[0049] In another embodiment, Figure 3A system 300 configured to facilitate communication between a vehicle 102 and an infrastructure system 110 is shown. For example, the system 300 provides a means for detecting, analyzing, and / or notifying of real-time wireless KPI impacts associated with wireless communication between the vehicle 102 and the infrastructure system 110. However, it should be understood that the system 300 can provide a means for detecting, analyzing, and / or notifying of real-time wireless KPI impacts associated with unicast wireless communication or message exchange between any entity within a marshaling environment. Generally, in one or more embodiments, the infrastructure system 110 communicates with the vehicle 102 via cellular protocol or a secure wireless protocol using one of two means. It should be understood that the infrastructure system 110 can communicate with the vehicle 102 by any other means, such as via a radio frequency (RF) related communication protocol. It should also be understood that the secure wireless protocol can include and / or be transmitted via a CV2X-PC5 protocol. However, it should also be understood that any secure communication protocol can be used.

[0050] As Figure 3 The infrastructure system 110 as shown generally includes at least one GNSS repeater 302, an AVM central server 304, and the sensor component 114. The AVM central server 304 operates as a central server for the infrastructure system 110 that processes communications ultimately received from each of the vehicle-side AVM algorithm 122 and / or the server cloud system 310 utilizing a central server module 306 and / or a perception module 308. The central server module 306 is configured to directly communicate with one or more wireless communication modules 314 (e.g., a public cellular module 314a; a private cellular module 314b; and / or a cellular module 314c supported by a distributed antenna system (e.g., a DAS) and / or a MEC) of a vehicle wireless communication unicast module 312. For example, the central server module 306 is configured to initiate and / or maintain a marshaling procedure (e.g., via a communication link) associated with the vehicle 102 going online, going offline, and / or going back online on the infrastructure system 110 by communicating with the one or more wireless communication modules 314 utilizing a wireless CV2X-PC5 protocol. It should also be understood that the central server module can be communicatively coupled (e.g., via wireless or wired means) to the perception module 308.

[0051] The perception module 308 is configured to process and / or interpret sensor data acquired by sensor component 114 to detect, identify, classify, and / or track vehicles 102 and / or one or more auxiliary vehicles 142 as they move through the formation environment. The perception module 308 is also configured to develop a three-dimensional model of the formation environment based on sensor data acquired by sensor component 114 and / or sensor data received from vehicle 102 (e.g., from one or more vehicle sensors 130). At least one GNSS repeater 302 is configured to wirelessly receive one or more GNSS signals received directly from vehicle GNSS 134. For example, the one or more GNSS signals help the perception module 308 develop the three-dimensional model, thereby supporting the acquired sensor data.

[0052] like Figure 3 As shown, vehicle 102 typically includes a vehicle-side AVM algorithm 122, one or more vehicle sensors 130, a vehicle GNSS 134, and a vehicle wireless communication unicast module 312. The one or more vehicle sensors 130 can wirelessly sense and thereby detect the behavior associated with the wireless KPIs affecting one or more messages exchanged between vehicle 102 and infrastructure system 110. Vehicle-side AVM algorithm 122 is configured to analyze at least one metric corresponding to the detected KPIs associated with one or more messages exchanged between vehicle 102 and infrastructure system 110. For example, KPIs may include packet error rate, inter-packet gap, delay, transmission time interval, data rate, etc. As another example, the analysis of at least one metric may include a dynamic estimate of the communication-related delays associated with a single exchange of one or more messages and / or a dynamic estimate of missed messages in the exchanged one or more messages. However, it should be understood that the analysis of at least one metric may include any techniques associated with the metrics associated with the KPI analysis. As an example, vehicle 102 may initiate a stop procedure based on the analysis of one or more metrics and in response to the detection of one or more communication-based interruptions associated with the exchange of one or more messages between vehicle 102 and infrastructure system 110.

[0053] The infrastructure system 110 is configured to transmit one or more instructions (e.g., one or more platooning commands) to the vehicle 102 based on the analysis of the one or more metrics and in response to detecting one or more communication-based disruptions associated with the exchange of one or more messages between the vehicle 102 and the infrastructure system 110. As another example, the one or more platooning commands can cause the vehicle 102 to be platooned in a manner that will cause the vehicle 102 to maneuver around any traffic objects (e.g., vehicles, infrastructure, etc.). In other words, the one or more platooning commands can provide the vehicle 102 with a new set of one or more waypoints to follow that causes the vehicle 102 to move around the traffic objects. For example, the vehicle 102 can receive the one or more platooning commands at the vehicle wireless communication unicast module 312 via the public cellular module 314a, the private cellular module 314, and / or the cellular module 314c supported by the DAS and / or the MEC.

[0054] The vehicle 102 can also communicate information associated with the analysis of the one or more metrics and the detection of one or more communication-based disruptions associated with the exchange of one or more messages between the vehicle 102 and the infrastructure system 110 to the server cloud system 310. The server cloud system 310 includes an original equipment manufacturer cloud system (e.g., the vehicle manufacturing cloud system 104) and a station manager cloud system (e.g., the vehicle delivery manager cloud system 106). Additionally, the infrastructure system 110 can also communicate any information associated with the analysis of the one or more metrics and the detection of one or more communication-based disruptions associated with the exchange of one or more messages between the vehicle 102 and the infrastructure system 110. In one or more embodiments, the server cloud system 310 is configured to generate a timestamp and a virtual dynamic RF coverage heat map associated with a platooning environment. For example, the RF coverage heat map is generated in response to a verification of a location of the vehicle 102 based on matching coordinates (e.g., X coordinate, Y coordinate, and / or Z coordinate) of the vehicle 102 to snapshot data associated with the location of the vehicle 102.

[0055] Figure 4 is a flow diagram illustrating an example method 400 for detecting, analyzing, and / or notifying of real-time wireless KPI impacts associated with wireless communications between a vehicle (e.g., the vehicle 102) and an infrastructure system (e.g., the infrastructure system 110). At operation 402, at least one metric corresponding to one or more KPIs is computed. For example, the one or more KPIs are associated with one or more messages exchanged between the vehicle and the infrastructure system. As another example, the one or more KPIs include a packet error rate, an inter-packet gap, a latency, a transmission time interval, a data rate, or a combination thereof. As a further example, the one or more messages include an IMM query (e.g., Figure 6VMM message alerts (e.g., VMM message alert 620 shown in FIG. 6), IMM query responses (e.g., IMM message query response 606 shown in FIG. 6), and VMM alert responses (e.g., VMM message alert response 622 shown in FIG. 6). As another example, Figure 6 VMM message alerts (e.g., VMM message alert 620 shown in FIG. 6), IMM query responses (e.g., IMM message query response 606 shown in FIG. 6), and VMM alert responses (e.g., VMM message alert response 622 shown in FIG. 6). As another example, Figure 6 VMM message alerts (e.g., VMM message alert 620 shown in FIG. 6), IMM query responses (e.g., IMM message query response 606 shown in FIG. 6), and VMM alert responses (e.g., VMM message alert response 622 shown in FIG. 6). As another example, Figure 6 VMM message alerts (e.g., VMM message alert 620 shown in FIG. 6), IMM query responses (e.g., IMM message query response 606 shown in FIG. 6), and VMM alert responses (e.g., VMM message alert response 622 shown in FIG. 6). As another example, Figure 5 At least one metric associated with one or more KPIs is shown when the KPIs can involve one or more messages exchanged between the vehicle and the infrastructure system.

[0056] Referring back to Figure 4 and in one or more embodiments, the first networking layer and the first application layer correspond to IMM queries and VMM messages. For example, the first networking layer includes a rolling header counter for randomized IMM requests, a rolling header counter for randomized VMM requests, a timestamp, or a combination thereof. As another example, the first application layer includes one or more VMM-related data elements associated with the vehicle, a sequential-randomized rolling counter for VMM transmissions associated with the vehicle, a rolling counter for IMM receptions associated with the infrastructure system, a VMM generation time, a time confidence, or a combination thereof.

[0057] In still one or more embodiments, the second networking layer and the second application layer correspond to IMM query responses and VMM alert responses. For example, the second networking layer includes an IMM response rolling header matching an IMM query, a VMM response rolling header counter matching a VMM alert, a timestamp, or a combination thereof. As another example, the second application layer includes one or more IMM-related data elements associated with the vehicle, a sequential-randomized rolling counter for IMM transmissions associated with the infrastructure system, a rolling counter for VMM receptions associated with the vehicle, an IMM generation time, a time confidence, or a combination thereof.

[0058] At operation 404, one or more communication-based interruptions associated with one or more messages are detected by a vehicle-side algorithm (e.g., vehicle-side AVM algorithm 122). For example, the detection of the one or more communication-based interruptions is based on an analysis of at least one metric. In one or more embodiments, the detection of the at least one metric includes measuring a percentage of lost packets within a second time interval associated with the exchange of the one or more messages; monitoring a time interval between consecutive packets received at the vehicle; calculating a time taken to successfully exchange the one or more messages; measuring a time interval between consecutive packet transmissions associated with the one or more messages; and / or verifying a simultaneous exchange of the one or more messages.

[0059] More specifically, the packet error rate is determined by measuring the percentage of packets lost within a second time interval associated with the exchange of one or more messages. An example and non-limiting objective is to maintain a packet error rate of less than 10% within the second interval. The inter-packet gap is determined by monitoring the time interval between successive packets received at the vehicle. An example and non-limiting acceptable range is between 90 milliseconds and 190 milliseconds. The latency is determined by calculating the time taken to successfully exchange one or more messages. An example and non-limiting objective latency is less than 100 milliseconds. The transmission time interval is determined by measuring the time interval between successive packet transmissions associated with one or more messages. An example and non-limiting acceptable range is between 90 milliseconds and 110 milliseconds. The data rate is determined by verifying the simultaneous exchange of one or more messages. An example and non-limiting acceptable data exchange rate interval is the simultaneous exchange of an IMM query and a VMM alert message in 100 milliseconds.

[0060] As an example, Figure 5 An example exchange 500 of one or more messages received / transmitted between the vehicle 102 and the infrastructure system 110 at different data rates, latency, packet status, and message timing (e.g., message delay or missed messages) is shown. For example, based on the query response, the vehicle-side algorithm is configured to decide whether to use the received IMM or to ignore the received IMM. As another example, based on the query response, the vehicle-side algorithm is further configured to determine whether a packet has been lost.

[0061] Referring back to Figure 4 And in still another embodiment or embodiments, the analysis of the at least one metric further includes a dynamic estimation of a communication-related delay associated with the exchanged one or more messages or a dynamic estimation of a missed message in the exchanged one or more messages. More specifically, the dynamic estimation of the communication-related delay can be for one or more delay responses. For example, the vehicle-side AVM algorithm 122 is configured to dynamically estimate one or more delays associated with any of an IMM query, a VMM alert, an IMM query response, and / or a VMM alert response. As another example, the vehicle-side AVM algorithm 122 is further configured to dynamically estimate a missed IMM query response and / or a VMM alert response in real-time prior to determining any of that one or more messages is missed, a packet is lost, a packet is delayed, or a combination thereof.

[0062] At operation 406, the remedial action is initiated. For example, the initiation of the remedial action is based on one or more communication-based disruptions and / or adjustments to one or more marshalling commands. In one or more embodiments, the initiation of the remedial action includes: initiating a stop procedure associated with the vehicle; receiving, from the infrastructure system, an adjustment to one or more marshalling commands; and / or causing the cloud system (e.g., the server cloud system 310) to generate a timestamp and a virtual dynamic radio frequency coverage heat map associated with the marshalling environment. For example, the virtual dynamic radio frequency coverage heat map is generated in response to a verification that coordinates based on a location of the vehicle match snapshot data associated with the location of the vehicle. In further one or more embodiments, a trigger associated with low speed automation of the vehicle is initiated. For example, the initiation of the trigger is based on an analysis of at least one metric. As another example, the trigger can be initiated based on an analysis performed by the vehicle-side AVM algorithm 122, where the vehicle-side AVM algorithm 122 is configured to implement a trigger within the vehicle 102 based on any of an IMM query, a VMM alert, an IMM query response, and / or a VMM alert response (e.g., as shown in FIG. 6). Figure 5

[0063] Figure 6 An IMM message exchange 600 and a VMM message exchange 602 associated with the above-described description related to one or more messages are shown. Specifically, Figure 6 An IMM message query 604 transmitted from the vehicle 102 to the infrastructure system 110 is depicted. For example, the IMM message query 604 can include a MIM-request- header-counter, a MIM-request-timestamp, or a combination thereof. Figure 6 An IMM message query response 606 transmitted from the infrastructure system 110 to the vehicle 102 is also depicted. For example, the IMM message query response 606 can include a MIM-response-header-counter, a MIM-ota,rx,cstimestamp, a MIM-ota-tx-cstimestamp, a MIM-ota-tx-cstimestamp-full, a MIM-prepared-cstimestamp, a content-length, or a combination thereof.

[0064] ​Point 608 can represent a before HTTP-timestamp. Point 610 can represent any of an after receiving successful IMM-timestamp, a after HTTP-timestamp, an RTT time difference, a MIM request latency, or a combination thereof. The vehicle-side AVM algorithm 122 is configured to determine a round trip time 612 associated with the exchange of the IMM message query 604 and the IMM message query response 606 based on a time difference between point 608 and point 610.

[0065] Point 614 can represent a MIM over the air interface receive coordinated time stamp (MIM-ota-rx-cs-timestamp). Point 616 can represent any of a MIM over the air interface transmit coordinated time stamp (MIM-ota-tx-cs-timestamp), a full MIM over the air interface transmit coordinated time stamp (MIM-ota-tx-cs-timestamp-full), a MIM prepared coordinated time stamp (MIM-prepared-cs-timestamp), or a combination thereof. The vehicle-side AVM algorithm 122 is further configured to determine a processing time 618 associated with the exchange of the IMM message query 604 and the IMM message query response 606 based on a time difference between point 614 and point 616.

[0066] Figure 6 A VMM message alert 620 transmitted from the vehicle 102 to the infrastructure system 110 is also depicted. For example, the VMM message alert 620 can include a MVM requested header counter (MVM-requested-header-counter), a MVM posted timestamp (MVM-posted-timestamp), or a combination thereof. Figure 6 A VMM message alert response 622 transmitted from the infrastructure system 110 to the vehicle 102 is additionally depicted. For example, the VMM message alert response 622 can include a MVM-response-header-counter, a MVM over the air interface receive coordinated time stamp (MVM-ota-rx-cs-timestamp), a MVM over the air interface transmit coordinated time stamp (MVM-ota-tx-cs-timestamp), a full MIM over the air interface transmit coordinated time stamp (MVM-ota-tx-cs-timestamp-full), or a combination thereof.

[0067] Point 624 can represent any of a before-HTTP-timestamp, after-HTTP-timestamp, or a combination thereof, after successfully receiving and encoding the MVM raw data from the MABx. Point 626 can represent any of a post-HTTP-timestamp (success status code), RTT time difference, or a combination thereof. The vehicle-side AVM algorithm 122 is configured to determine a round-trip time 628 associated with the exchange of the VMM message alert 620 and the VMM message alert response 622 based on a time difference between point 624 and point 626.

[0068] Point 630 can represent a MVM over-the-air interface reception coordinated time stamp (MVM-ota-rx-cs-timestamp). Point 632 can represent a MVM over-the-air interface transmission coordinated time stamp (MVM-ota-tx-cs-timestamp), a full MVM over-the-air interface transmission time stamp (MVM-ota-tx-cs-timestamp-full), or a combination thereof. The vehicle-side AVM algorithm 122 is further configured to determine a processing time 634 associated with the exchange of the VMM message alert 620 and the VMM message alert response 622 based on a time difference between point 630 and point 632.

[0069] It should be appreciated that each of the IMM message query 604, the IMM message query response 606, the VMM message alert 620, and the VMM message alert response 622 can be exchanged simultaneously between the vehicle 102 and the infrastructure system 110. However, it should also be appreciated that each of the IMM message query 604, the IMM message query response 606, the VMM message alert 620, and the VMM message alert response 622 can be exchanged in any order, at any frequency, non-simultaneously, and / or with any delay taken into account.

[0070] Additionally, IMM message query 604 and VMM message alert 620 can be incorporated into a first networking layer and a first application layer. In one or more embodiments, the first networking layer may include a rolling header counter for IMM requests, a timestamp, a rolling header counter for VMM requests, or a combination thereof. For example, the IMM rolling header counter may be randomized for message queries every 100 milliseconds. As another example, the VMM rolling header counter may be randomized for message alerts every 100 milliseconds. As a further example, the timestamp may be the basis for determining delays and / or initiating one or more delayed operations. In one or more other embodiments, the first application layer may include a rolling counter for the randomized order of VMM transmissions received from vehicle 102, a rolling counter for IMM reception associated with infrastructure system 110, VMM message generation time, time confidence, and various other data elements or combinations thereof associated with VMM messages related to the autocorrelation behavior of vehicle 102.

[0071] Furthermore, the IMM message query response 606 and the VMM message alarm response 622 can be incorporated into a second networking layer and a second application layer. In one or more embodiments, the second networking layer may include an IMM response rolling header counter, a timestamp, a VMM response rolling header counter, or a combination thereof. For example, whether the IMM response rolling header counter matches the requested query is determined by the vehicle-side AVM algorithm 122. As another example, whether the VMM response rolling header counter matches the requested alarm is determined by the vehicle-side AVM algorithm 122. As a further example, the timestamp may be a basis for determining delay, the initiation of one or more delayed operations associated with the received IMM message related to the query, the initiation of one or more delayed operations associated with the received VMM message related to the alarm, the transmission of the timestamp associated with the IMM message related to the query response, the transmission of the timestamp associated with the VMM message related to the alarm response, or a combination thereof. In one or more other embodiments, the second application layer may include a rolling counter for the sequential randomization of IMM transmissions received from infrastructure system 110, a rolling counter for VMMs associated with vehicle 102, IMM message generation time, time confidence, and various other data elements or combinations thereof associated with IMM messages related to the automatic related behavior of vehicle 102.

[0072] refer to Figure 7 The diagram illustrates the exchange 700 of the VMM receive / transmit rolling counter and the IMM receive / transmit rolling counter. In one or more embodiments, each of the VMM receive / transmit rolling counter and the IMM receive / transmit rolling counter is randomized within a predetermined range (e.g., between 1 and 65535).

[0073] For example, each of the VMM receive / transmit rolling counter and the IMM receive / transmit rolling counter can be randomized at a vehicle 102 key-on and represent a first VMM message transmitted to the infrastructure system 110 or broadly unicast for receipt by any system, such as the server cloud system 310. As another example, each of the VMM receive / transmit rolling counter and the IMM receive / transmit rolling counter can be randomized at a time the infrastructure system 110 responds to a first VMM message representing a first IMM message transmitted to the vehicle 102. However, it should be appreciated that the first IMM message can also be transmitted from the infrastructure system 110 to the cloud server system 310. As a further example, each of the VMM receive / transmit rolling counter and the IMM receive / transmit rolling counter can be randomized at any (e.g., each) on-boarding process, such as a blink challenge. As an additional example, each of the VMM receive / transmit rolling counter and the IMM receive / transmit rolling counter can be randomized at a security authentication rotation associated with any of the exchanged IMM and / or VMM messages.

[0074] As yet another example, each of the VMM and / or IMM rolling counters of subsequent transmissions following the first VMM message and / or the first IMM message are incremented by one (e.g., “1”). However, it should be appreciated that each of the VMM and / or IMM rolling counters of subsequent transmissions following the first VMM message and / or the first IMM message can be incremented by any number. It should also be appreciated that each of the VMM and / or IMM rolling counters of subsequent transmissions following the first VMM message and / or the first IMM message roll back any increment (e.g., 1) in the event that a predefined range is exceeded (e.g., after 65535). In still one or more embodiments, each of the VMM receive / transmit rolling counter and the IMM receive / transmit rolling counter are used as zero (e.g., “0”) in the event that there is no rolling counter synchronization on any of the IMM messages or VMM messages.

[0075] Figure 8An operating environment that facilitates the performance of one or more systems and methods described herein is shown. More specifically, the systems and methods described herein can be implemented using a computing device 802. For example, the computing device 802 can be a personal computer, a desktop computer, a laptop computer, a tablet computer, a handheld computer, a server, a workstation, a mainframe, a wearable computer, a supercomputer, or a combination thereof. However, it should be understood that the foregoing examples of the computing device 802 are non-exhaustive and that the computing device 802 can be any type of processing or computing device. The computing device 802 generally 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 a memory 816. However, it should be understood that the computing device 802 can include any additional components therein and need not include any of the listed components (e.g., the processor 804, the display adapter 806, the one or more input / output ports 808, the one or more input / output components 810, the network adapter 812, the power supply 814, and the memory 816).

[0076] The processor 804 is configured to provide the computing device 802 with instructions such that the computing device 802 can process one or more tasks, including implementing a software program to perform one or more operations as described in greater detail herein. It should also be understood that the computing device 802 can include any number of processors 804 therein. The display adapter 806 can be a graphics card or video board that provides the computing device 802 with the ability to display content on a display device 818. For example, the display device 818 can be any screen, monitor, and / or light-emitting component associated with any of a personal computer, a desktop computer, a laptop computer, a tablet computer, a handheld computer, a server, a workstation, a mainframe, a wearable computer, a supercomputer, or a combination thereof. However, it should be understood that the foregoing examples of the display device 818 are non-exhaustive and that the display device 818 can be any type of device capable of providing a visual display.

[0077] The input / output ports 808 provide a plurality of interfaces (e.g., jacks) for one or more cables to connect to the computing device 802. It should be appreciated that there can be any number of input / output ports 808 on the computing device 802. For example, the input / output ports 808 provide the computing device 802 with a means to receive signals and / or data from external devices connected to the computing device 802 via one or more cables. As another example, the input / output ports 808 provide the computing device 802 with a means to send signals and / or data to external devices connected to the computing device 802 via one or more cables. The input / output components 810 can include one or more components that support the input / output ports 808, such as, but not limited to, switches, buttons, pressure pads, float switches, keyboards, radio receivers, or combinations thereof.

[0078] The network adapter 812 can be any type of network interface controller configured to provide a means for communicating with another computing device, such as the remote computing device 822, over the network 820. For example, the remote computing device 822 can be a user device, such as a cellular phone, a smart phone, a tablet computer, a laptop computer, or combinations thereof. The power supply 814 is configured to convert alternating current high voltage current (e.g., AC) to direct current (e.g., DC) to provide power to the other components of the computing device 802 (e.g., the processor 804, the display adapter 806, the one or more input / output ports 808, the one or more input / output components 810, the network adapter 812, and the memory 816).

[0079] Additionally, the memory 816 can be a mass storage device and / or a system memory, such as a hard drive, a memory card, a solid-state drive, a random access memory (RAM), or combinations thereof. The memory 816 is configured to provide storage for instructions and data associated with the operation of the computing device 802. The memory 816 can generally include an operating system 824, detection software 826, and detection data 828. For example, the operating system 824 is configured to manage and / or process any of the data and / or instructions associated with the detection software 826 and / or the detection data 828, as described in greater detail herein.

[0080] Furthermore, a system bus 830 is also included within the computing device 802, which is configured to couple each of the various components (e.g., the processor 804, the display adapter 806, the one or more input / output ports 808, the one or more input / output components 810, the network adapter 812, the power supply 814, and the memory 816) of the computing device 802. It should also be appreciated that each of the components of the computing device 802, and the functionality associated with each of the components of the computing device 802, can be implemented within the remote computing device 822. While Figure 8The 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.

[0081] Therefore, one or more examples of this disclosure provide a means for providing enhanced vehicle marshalling based on the detection and analysis of any impact associated with one or more key performance indicators related to the exchange of one or more messages between a vehicle and an infrastructure system. This disclosure also specifies that such detection and analysis is performed by the vehicle, and the vehicle is further configured to notify the infrastructure system and / or cloud system of the vehicle's analysis of any impact associated with the exchange of one or more messages.

[0082] 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.

[0083] 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".

[0084] 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.

[0085] The term memory is a subset of the term computer readable medium. The term computer readable medium as used herein does not encompass transitory propagating signals per se (such as electric or electromagnetic waves propagating through a medium other than a computer readable medium). Thus, the term computer readable medium can be considered as tangibly embodied and non-transitory. Non-limiting examples of non-transitory computer readable media are 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 tapes or digital magnetic tapes or hard disk drives), and optical storage media (such as CDs, DVDs or BluRay discs).

[0086] The apparatus and methods described in this application can be partially or entirely implemented by special purpose computers configured to create a general purpose computer that is configured to perform one or more specific functions embodied in the computer program. The functional blocks, flowchart components and other elements described above serve as software specifications which can be translated into a computer program by routine work of a skilled programmer or engineer.

[0087] The description of the present disclosure is merely exemplary in nature and, thus, variations that do not depart from the essence of the present disclosure are intended to be within the scope of the present disclosure. Such variations are not to be regarded as a departure from the spirit and scope of the present disclosure.

[0088] According to the present application, there is provided one or more non-transitory computer readable media having stored processor-executable instructions that, when executed by at least one processor, cause the at least one processor to: compute at least one metric corresponding to one or more key performance indicators associated with one or more messages exchanged between a vehicle and an infrastructure system; detect, by a vehicle-side algorithm, one or more communication-based disruptions associated with the one or more messages based on an analysis of the at least one metric; and initiate a remedial action based on the one or more communication-based disruptions and an adjustment to one or more grouping commands.

[0089] According to embodiments, the one or more key performance indicators include a packet error rate, an inter-packet gap, a latency, a transmission time interval, a data rate, or a combination thereof.

[0090] According to an embodiment, the one or more messages include an infrastructure marshaling message (IMM) query, a vehicle marshaling message (VMM) alert, an IMM query response, and a VMM alert response, and wherein: the first networking layer and the first application layer correspond to the IMM query and the VMM alert, and wherein the first networking layer includes a randomized IMM request rolling header counter, a randomized VMM request rolling header counter, a timestamp, or a combination thereof, and further wherein the first application layer includes one or more VMM related data elements associated with the vehicle, a sequentially randomized rolling counter of VMM transmissions associated with the vehicle, a rolling counter of IMM receptions associated with the infrastructure system, a VMM generation time, a time confidence, or a combination thereof; and the second networking layer and the second application layer correspond to the IMM query response and the VMM alert response, and wherein the second networking layer includes an IMM response rolling header matching the IMM query, a VMM response rolling header counter matching the VMM alert, a timestamp, or a combination thereof, and further wherein the second application layer includes one or more IMM related data elements associated with the vehicle, a sequentially randomized rolling counter of IMM transmissions associated with the infrastructure system, a rolling counter of VMM receptions associated with the vehicle, an IMM generation time, a time confidence, or a combination thereof.

[0091] According to an embodiment, the at least one processor caused to detect the at least one metric is further caused to: measure a percentage of lost packets within a second time interval associated with the exchange of the one or more messages; monitor a time interval between successive packets received at the vehicle; calculate a time taken to successfully exchange the one or more messages; measure a time interval between successive packet transmissions associated with the one or more messages; or verify a simultaneous exchange of the one or more messages.

[0092] According to an embodiment, the at least one processor caused to analyze the at least one metric is further caused to: dynamically estimate a communication related latency associated with the exchanged one or more messages; or dynamically estimate a missed message of the exchanged one or more messages.

[0093] According to an embodiment, the at least one processor is further caused to: initiate a trigger associated with a low speed automation of the vehicle based on the analysis of the at least one metric.

[0094] According to an embodiment, the at least one processor caused to initiate the remedial action is further caused to: initiate a stop procedure associated with the vehicle; receive an adjustment to one or more marshaling commands from the infrastructure system; or cause generation of a virtual dynamic radio frequency coverage heat map associated with the marshaling environment, wherein the virtual dynamic radio frequency coverage heat map is generated in response to a verification of a location of the vehicle based on a coordinate matching snapshot data associated with the location of the vehicle.

Claims

1. A method comprising: Calculate at least one metric corresponding to one or more key performance indicators associated with one or more messages exchanged between vehicles and infrastructure systems; One or more communication-based interruptions associated with the one or more messages are detected by a vehicle-side algorithm based on the analysis of the at least one metric. as well as Remedial action is initiated based on one or more communication-based interruptions and / or adjustments to one or more marshalling commands.

2. The method of claim 1, wherein the one or more key performance indicators include packet error rate, inter-packet gap, delay, transmission time interval, data rate, or a combination thereof.

3. The method of claim 1, wherein the one or more messages include an Infrastructure Grouping Message (IMM) query, a Vehicle Grouping Message (VMM) alert, an IMM query response, and a VMM alert response.

4. The method of claim 3, wherein the first networking layer and the first application layer correspond to the IMM query and the VMM alarm, and wherein the first networking layer includes a randomized rolling header counter for IMM requests, a randomized rolling header counter for VMM requests, a timestamp, or a combination thereof, and further wherein the first application layer includes one or more VMM-related data elements associated with the vehicle, a rolling counter for the sequential randomization of VMM transmissions associated with the vehicle, a rolling counter for IMM receptions associated with the infrastructure system, VMM generation time, time confidence, or a combination thereof.

5. The method of claim 3, wherein the second networking layer and the second application layer correspond to the IMM query response and the VMM alarm response, and wherein the second networking layer includes an IMM response rolling header matching the IMM query, a VMM response rolling header counter matching the VMM alarm, a timestamp, or a combination thereof, and further wherein the second application layer includes one or more IMM-related data elements associated with the vehicle, a rolling counter for the randomized order of IMM transmissions associated with the infrastructure system, a rolling counter for VMM reception associated with the vehicle, an IMM generation time, a time confidence level, or a combination thereof.

6. The method of claim 1, wherein the detection of the at least one metric further comprises: Measure the percentage of packets lost during a second time interval associated with the exchange of the one or more messages; Monitor the time interval between consecutive packets received at the vehicle; Calculate the time taken to successfully exchange the one or more messages; Measure the time interval between consecutive packet transmissions associated with the one or more messages; or The exchange verifies one or more messages simultaneously.

7. The method of claim 1, wherein the detection of the at least one metric further comprises: Dynamically estimate the communication-related latency associated with one or more messages exchanged; or Dynamically estimate the messages missed in one or more messages exchanged.

8. The method of claim 1, further comprising: Triggers associated with low-speed automation of the vehicle are initiated based on the analysis of the at least one metric.

9. The method of claim 1, wherein initiating the remedial action further comprises: Initiate a stop procedure associated with the vehicle; Receive adjustments to one or more marshalling commands from the infrastructure system; or This results in the generation of a timestamp and a virtual dynamic radio frequency coverage heatmap associated with the grouping environment, wherein the virtual dynamic radio frequency coverage heatmap is generated in response to verification of the vehicle's location based on the coordinates of the vehicle's location and snapshot data associated with the vehicle's location.

10. A system comprising: The vehicle system is configured to: Calculate at least one metric corresponding to one or more key performance indicators associated with one or more messages exchanged between vehicle and infrastructure systems. One or more communication-based interruptions associated with the one or more messages are detected by a vehicle-side algorithm based on the analysis of at least one metric. Remedial action is initiated based on one or more communication-based interruptions and / or adjustments to one or more marshalling commands; The infrastructure system is configured as follows: In response to receiving the analysis of the at least one metric, an adjustment to one or more formation commands is transmitted to the vehicle; and The cloud system is configured as follows: This results in the generation of a timestamp and a virtual dynamic radio frequency coverage heatmap associated with the grouping environment, wherein the virtual dynamic radio frequency coverage heatmap is generated in response to verification of the vehicle's location based on the coordinates of the vehicle's location and snapshot data associated with the vehicle's location.

11. The system of claim 10, wherein the one or more key performance indicators include packet error rate, inter-packet gap, delay, transmission time interval, data rate, or a combination thereof.

12. The system of claim 10, wherein the one or more messages include an Infrastructure Grouping Message (IMM) query, a Vehicle Grouping Message (VMM) alarm, an IMM query response, and a VMM alarm response, and wherein: The first networking layer and the first application layer correspond to the IMM query and the VMM alarm, and wherein the first networking layer includes a randomized rolling header counter for IMM requests, a randomized rolling header counter for VMM requests, a timestamp, or a combination thereof, and further wherein the first application layer includes one or more VMM-related data elements associated with the vehicle, a rolling counter for the sequential randomization of VMM transmissions associated with the vehicle, a rolling counter for IMM reception associated with the infrastructure system, VMM generation time, time confidence, or a combination thereof; and The second networking layer and the second application layer correspond to the IMM query response and the VMM alarm response, wherein the second networking layer includes an IMM response rolling header matching the IMM query, a VMM response rolling header counter matching the VMM alarm, a timestamp, or a combination thereof, and further wherein the second application layer includes one or more IMM-related data elements associated with the vehicle, a rolling counter for the randomized order of IMM transmissions associated with the infrastructure system, a rolling counter for VMM reception associated with the vehicle, an IMM generation time, a time confidence level, or a combination thereof.

13. The system of claim 10, wherein the vehicle system configured to detect the at least one metric is further configured to: Measure the percentage of packets lost during a second time interval associated with the exchange of the one or more messages; Monitor the time interval between consecutive packets received at the vehicle; Calculate the time taken to successfully exchange the one or more messages; Measure the time interval between consecutive packet transmissions associated with the one or more messages; or The exchange verifies one or more messages simultaneously.

14. The system of claim 10, wherein the vehicle system configured to analyze the at least one metric is further configured to: Dynamically estimate the communication-related latency associated with one or more messages exchanged; or Dynamically estimate the messages missed in one or more messages exchanged.

15. The system of claim 10, wherein the vehicle system is further configured to: Triggers associated with low-speed automation of the vehicle are initiated based on the analysis of the at least one metric.

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