Height detection method

Abstract

In one aspect, a system is described. The system includes: a height warning module configured to: detect one or more objects attached to the vehicle; determining the total height of the vehicle; acquiring a first driving route for the vehicle to arrive at the destination point; extracting first height limitation information of one or more first limitation obstacles positioned along the first driving route; determining a first headroom height based on an overall height of the vehicle and first height restriction information of the one or more first restriction obstacles; and when the first headroom height is greater than the threshold headroom, calculating as true a first probability that the vehicle and the one or more objects safely pass through the one or more first restricted obstacles.

Description

Technical Field

[0001] The present disclosure generally relates to the field of transportation. More specifically, the present disclosure relates to a system and method for vehicles to safely pass through underground passages, bridges, tunnels, etc. Background Art

[0002] “A driver may encounter various overhead objects in the path of the vehicle while driving. Overhead objects may include persistent objects, such as road overpasses, tunnels, traffic signs, or other overhead objects that are permanent fixtures along the road; and / or non-persistent objects, such as tree branches that may be removed. Some overhead objects (e.g., tunnels) may have warning signs that indicate clearance height, while other overhead objects (e.g., tree branches) may not provide clearance height to avoid the overhead objects. However, drivers may be oblivious or unaware of the height of their vehicle, the height of the load on the vehicle, and / or be unable to see the overhead objects, and therefore, the driver may be unable to avoid the overhead objects.

[0003] Even if the driver identifies an overhead object, the driver may not be able to avoid the overhead object while maintaining travel toward the destination. For example, if the road leading to a tunnel does not have an exit or other path to avoid the tunnel between a vehicle that is taller than the tunnel's clearance height and the tunnel entrance, the vehicle may have to stop and turn around before the tunnel entrance.

[0004] In addition, various elevated objects, such as tree branches, do not have warning signs that clearly indicate their height, and therefore, it may be difficult for the driver to determine whether a collision is likely to occur. " [Source: US Patent Application US10843694B2, Invention Name "Vehicle Height Detection and Environmental Warning System (Vehicle Height Detection and Environmental Warning System)", Published in May 2020]

[0005] Therefore, there is a long felt need for a system and method for determining the overall height of a vehicle including an overhead load and providing assistance in safely passing the vehicle without a collision. Summary of the invention

[0006] An overview is provided below to provide a basic understanding of one or more embodiments described herein. The present invention summary is not intended to mark key or core elements or to describe any scope of different embodiments and / or any scope of claims. The sole purpose of the present invention summary is to present some concepts in a simplified form as a prelude to a more detailed description presented herein.

[0007] In one aspect, a system is described. The system includes: a height warning module configured to: detect one or more objects attached to a vehicle; determine a total height of the vehicle, wherein the total height of the vehicle includes a first height of the vehicle and a second height of the one or more objects; obtain a first driving route for the vehicle to reach a destination; extract first height limit information of one or more first limiting obstacles located along the first driving route; determine a first clearance height based on the total height of the vehicle and the first height limit information of the one or more first limiting obstacles; when the first clearance height is greater than a threshold clearance, calculate a first probability that the vehicle and the one or more objects safely pass through the one or more first limiting obstacles as true, and transmit a maneuver command to an electric drive unit to maneuver the vehicle; and when the first probability is calculated to be false, transmit a signal to a control module to dynamically adjust an adjustable roof rack to reduce the total height of the vehicle, wherein when the first clearance height is less than the threshold clearance height, the first probability is calculated to be false.

[0008] In another aspect, a method is described. The method includes: detecting one or more objects attached to a vehicle; determining a total height of the vehicle, wherein the total height of the vehicle includes a first height of the vehicle and a second height of the one or more objects; obtaining a first driving route for the vehicle to reach a destination; extracting first height limit information of one or more first limiting obstacles located along the first driving route; determining a first clearance height based on the total height of the vehicle and the first height limit information of the one or more first limiting obstacles; when the first clearance height is greater than a threshold clearance height, calculating a first probability that the vehicle and the one or more objects safely pass through the one or more first limiting obstacles as true, and transmitting a maneuvering command to an electric drive unit to maneuver the vehicle; and when the first probability is calculated to be false, transmitting a signal to a control module to dynamically adjust an adjustable roof rack to reduce the total height of the vehicle, wherein when the first clearance height is less than the threshold clearance height, the first probability is calculated to be false.

[0009] In yet another aspect, a non-transitory storage medium storing a sequence of instructions is described. The non-transitory storage medium, when executed by a processor, causes: detecting one or more objects attached to a vehicle; determining a total height of the vehicle, wherein the total height of the vehicle includes a first height of the vehicle and a second height of the one or more objects; obtaining a first driving route for the vehicle to reach a destination; extracting first height limit information of one or more first limiting obstacles located along the first driving route; determining a first clearance height based on the total height of the vehicle and the first height limit information of the one or more first limiting obstacles; when the first clearance height is greater than a threshold clearance height, calculating a first probability that the vehicle and the one or more objects safely pass through the one or more first limiting obstacles as true, and transmitting a maneuvering command to an electric drive unit to maneuver the vehicle; and when the first probability is calculated to be false, transmitting a signal to a control module to dynamically adjust an adjustable roof rack to reduce the total height of the vehicle, wherein when the first clearance height is less than the threshold clearance height, the first probability is calculated to be false.

[0010] In another aspect, a system is described, comprising: a height warning module, the height warning module being configured to: detect one or more objects attached to a vehicle; determine a total height of the vehicle, wherein the total height of the vehicle includes a first height of the vehicle and a second height of the one or more objects; obtain a first driving route for the vehicle to reach a destination; extract first height limit information of one or more first limiting obstacles located along the first driving route; determine a first clearance height based on the total height of the vehicle and the first height limit information of the one or more first limiting obstacles; when the first clearance height is greater than a threshold clearance height, calculate a first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true, and transmit a maneuvering command to an electric drive unit to maneuver the vehicle; and when the first probability is calculated as false, transmit a signal to a control module to dynamically adjust an adjustable roof rack so as to reduce the total height of the vehicle, wherein when the first clearance height is less than the threshold clearance height, the first probability is calculated as false.

[0011] According to one embodiment, the system is part of the one or more first restrictive obstacles along the first driving route.

[0012] According to one embodiment, the system is part of the vehicle.

[0013] According to one embodiment, the system is part of one or more nearby vehicles.

[0014] According to one embodiment, the system is part of an external infrastructure.

[0015] According to one embodiment, the system is in communication with the vehicle.

[0016] According to one embodiment, the system communicates with one or more nearby vehicles.

[0017] According to one embodiment, the system comprises one or more sensors.

[0018] According to one embodiment, the one or more sensors include a laser sensor, a rangefinder, a distance sensor, a camera, a photoelectric sensor, a measurement sensor, and an ultrasonic sensor.

[0019] According to one embodiment, the camera captures at least one of an image and a video of the vehicle, wherein the vehicle includes the one or more objects attached.

[0020] According to one embodiment, when the first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles is calculated to be false, the system transmits a command to the electric drive unit of the vehicle through a communication module.

[0021] According to one embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0022] According to an embodiment, the one or more sensors are configured to determine a distance between the vehicle and the one or more first limiting obstacles.

[0023] According to an embodiment, the one or more sensors are configured to determine an overall height of the vehicle.

[0024] According to one embodiment, the one or more sensors are configured to determine a distance between the vehicle and one or more nearby vehicles.

[0025] According to an embodiment, the one or more sensors are configured to determine a distance between the vehicle and an external infrastructure.

[0026] According to one embodiment, the system further comprises a communication module.

[0027] According to one embodiment, the communication module is configured to establish wireless communication with at least one of the vehicle, the one or more first limiting obstacles, external infrastructure, and one or more nearby vehicles.

[0028] According to one embodiment, said one or more first limiting obstacles comprise a display for displaying messages to said vehicle.

[0029] According to one embodiment, the message comprises a traffic sign.

[0030] According to one embodiment, the vehicle comprises the control module.

[0031] According to one embodiment, the control module includes a natural language processing module configured to recognize, interpret and understand at least one of messages, audio, instructions, traffic signs, text and images.

[0032] According to one embodiment, the natural language processing module is configured to recognize, interpret and understand the context of at least one of the message, the audio, the instruction, the traffic sign, the text and the image through an artificial intelligence module.

[0033] According to one embodiment, the control module transmits commands to the electric drive unit.

[0034] According to one embodiment, the system comprises an artificial intelligence module.

[0035] According to one embodiment, the artificial intelligence module is pre-trained using a first data set including one or more traffic signs, one or more messages, one or more instructions, one or more texts, one or more images, and one or more videos to recognize, interpret, and understand one or more scenarios.

[0036] According to one embodiment, the artificial intelligence module is trained using the second data set in order to learn, improve and understand the one or more scenarios in an optimized manner.

[0037] According to one embodiment, the artificial intelligence module understands the one or more scenarios and transmits commands to the electric drive unit.

[0038] According to one embodiment, the command instructs at least one of the electric drive unit and the control module to perform a predetermined action when the one or more first limiting obstacles are reached.

[0039] According to one embodiment, the predetermined action comprises at least one of: applying automatic braking, passing the one or more first limiting obstacles, stopping before the one or more first limiting obstacles, taking a second driving route, and adjusting the adjustable roof rack.

[0040] According to one embodiment, the control module provides a user interface via an infotainment unit through which the system receives the overall height of the vehicle as input from a user.

[0041] According to one embodiment, the vehicle comprises the adjustable roof rack for holding the one or more objects.

[0042] According to one embodiment, the vehicle includes the control module, the control module instructing the adjustable roof rack to dynamically adjust so as to reduce the overall height of the vehicle.

[0043] According to one embodiment, the adjustable roof rack is configured to be adjusted to one of a first level, a second level, and a third level.

[0044] According to one embodiment, the first level comprises a first predetermined height.

[0045] According to one embodiment, said second level comprises a second predetermined height.

[0046] According to one embodiment, said third level comprises a third predetermined height.

[0047] According to one embodiment, an artificial intelligence module is pre-trained using a first data set, wherein the first data set includes vehicle information, vehicle specifications, predetermined height information of the one or more objects, driving route information, height limit information of the one or more first limiting obstacles, and height information of the adjustable roof rack.

[0048] According to one embodiment, the artificial intelligence module is trained using the second data set to learn and improve.

[0049] According to one embodiment, the artificial intelligence module transmits a command to the control module, wherein the command instructs the adjustable roof rack to automatically adjust to one of a first level, a second level, and a third level.

[0050] According to one embodiment, the system includes a width warning module operating in cooperation with the height warning module.

[0051] According to one embodiment, the width warning module is configured to: detect the one or more objects attached to the vehicle; determine the total width of the vehicle, wherein the total width of the vehicle includes a first width of the vehicle and a second width of the one or more objects; obtain the first driving route for the vehicle to reach the destination point; extract the first width limitation information of the one or more first limiting obstacles located along the first driving route; determine a first clearance width based on the total width of the vehicle and the first width limitation information of the one or more first limiting obstacles; and when the first clearance width is greater than a threshold clearance width, calculate a second probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true.

[0052] According to one embodiment, when the second probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles is calculated to be false, the width warning module transmits a command to the electric drive unit of the vehicle through a communication module.

[0053] According to one embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0054] In yet another aspect, a method is described, comprising: detecting one or more objects attached to a vehicle; determining a total height of the vehicle, wherein the total height of the vehicle includes a first height of the vehicle and a second height of the one or more objects; obtaining a first driving route for the vehicle to reach a destination; extracting first height limit information of one or more first limiting obstacles located along the first driving route; determining a first clearance height based on the total height of the vehicle and the first height limit information of the one or more first limiting obstacles; when the first clearance height is greater than a threshold clearance height, calculating a first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true, and transmitting a maneuvering command to an electric drive unit to maneuver the vehicle; and when the first probability is calculated as false, transmitting a signal to a control module to dynamically adjust an adjustable roof rack so as to change the total height of the vehicle, wherein when the first clearance height is less than the threshold clearance height, the first probability is calculated as false.

[0055] According to an embodiment, the second height of the one or more objects comprises a maximum height among the one or more objects.

[0056] According to one embodiment, the method further comprises: calculating one or more second driving routes for the vehicle to reach the destination.

[0057] According to one embodiment, calculating the one or more second driving routes for the vehicle to arrive at the destination point includes: identifying the current position of the vehicle; obtaining the destination point of the vehicle; determining one or more third driving routes leading to the destination point based on the current position and the destination point; extracting second height limit information of one or more second restricting obstacles located along the one or more third driving routes; determining a second clearance height based on the total height of the vehicle and the second height limit information of the one or more second restricting obstacles; and when the second clearance height is greater than the threshold clearance height, calculating a second probability that the vehicle together with the one or more objects safely passes through the one or more second restricting obstacles as true; and calculating the one or more second driving routes among the one or more third driving routes for the vehicle to arrive at the destination point, wherein, for the one or more second driving routes, the second probability is calculated to be true.

[0058] According to one embodiment, the method further comprises: transmitting a command to the electric drive unit of the vehicle through a communication module when the first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles is calculated to be false.

[0059] According to one embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0060] According to one embodiment, the method further comprises: establishing wireless communication with at least one of the vehicle, the one or more first limiting obstacles, external infrastructure, and one or more nearby vehicles through a communication module.

[0061] According to one embodiment, the method further includes: recognizing, interpreting and analyzing, by a natural language processing (NLP) module, one or more contexts of at least one of a message, an instruction, a traffic sign, a text and an image through artificial intelligence.

[0062] According to one embodiment, the method further includes: pre-training an artificial intelligence module using a first data set to recognize, interpret and understand one or more scenarios, wherein the first data set includes one or more traffic signs, one or more messages, one or more instructions, one or more texts, one or more images and one or more videos.

[0063] According to one embodiment, the method further comprises: training the artificial intelligence module using a second data set to learn, improve and understand the one or more scenarios in an optimized manner.

[0064] According to one embodiment, the method further comprises: interpreting and analyzing the one or more scenarios by an artificial intelligence module, and transmitting commands to the electric drive unit based on the one or more scenarios.

[0065] According to one embodiment, the method further comprises dynamically adjusting the adjustable roof rack to reduce the overall height of the vehicle.

[0066] According to one embodiment, the method further comprises dynamically adjusting the adjustable roof rack to one of a first level, a second level, and a third level.

[0067] According to one embodiment, the method further includes dynamically adjusting the adjustable roof rack to one of a first level, a second level, and a third level based on a command received from an artificial intelligence module.

[0068] According to one embodiment, the method also includes: detecting the one or more objects attached to the vehicle; determining the total width of the vehicle, wherein the total width of the vehicle includes a first width of the vehicle and a second width of the one or more objects; obtaining the first driving route for the vehicle to reach the destination point; extracting first width limitation information of the one or more first limiting obstacles located along the first driving route; determining a first clearance width based on the total width of the vehicle and the first width limitation information of the one or more first limiting obstacles; and when the first clearance width is greater than a threshold clearance width, calculating a second probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true.

[0069] According to one embodiment, the method further comprises: transmitting a command to the electric drive unit of the vehicle through a communication module when the second probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles is calculated to be false.

[0070] According to one embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0071] In yet another aspect, a non-transitory storage medium storing a sequence of instructions is described, which, when executed by a processor, causes: detecting one or more objects attached to a vehicle; determining a total height of the vehicle, wherein the total height of the vehicle includes a first height of the vehicle and a second height of the one or more objects; obtaining a first driving route for the vehicle to reach a destination; extracting first height limit information of one or more first limiting obstacles located along the first driving route; determining a first clearance height based on the total height of the vehicle and the first height limit information of the one or more first limiting obstacles; when the first clearance height is greater than a threshold clearance height, calculating a first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true, and transmitting a maneuvering command to an electric drive unit to maneuver the vehicle; and when the first probability is calculated as false, transmitting a signal to a control module to dynamically adjust an adjustable roof rack so as to change the total height of the vehicle, wherein when the first clearance height is less than the threshold clearance height, the first probability is calculated as false.

[0072] According to one embodiment, the non-transitory storage medium further enables: calculating one or more second driving routes for the vehicle to reach the destination point.

[0073] According to one embodiment, the one or more second driving routes for the vehicle to arrive at the destination are calculated so as to: identify the current position of the vehicle; obtain the destination of the vehicle; determine one or more third driving routes leading to the destination based on the current position and the destination; extract second height limit information of one or more second restricting obstacles located along the one or more third driving routes; determine a second clearance height based on the total height of the vehicle and the second height limit information of the one or more second restricting obstacles; and when the second clearance height is greater than the threshold clearance height, calculate a second probability that the vehicle together with the one or more objects safely passes through the one or more second restricting obstacles as true; and calculate the one or more second driving routes among the one or more third driving routes for the vehicle to arrive at the destination, wherein, for the one or more second driving routes, the second probability is calculated as true.

[0074] According to one embodiment, the non-transitory storage medium further enables: when the first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles is calculated to be false, a command is transmitted to the electric drive unit of the vehicle through a communication module.

[0075] According to one embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0076] According to one embodiment, the non-transitory storage medium further enables: establishing wireless communication with at least one of the vehicle, the one or more first limiting obstacles, external infrastructure, and one or more nearby vehicles through the communication module.

[0077] According to one embodiment, the non-transitory storage medium further enables: recognizing, interpreting and analyzing one or more contexts of at least one of a message, an instruction, a traffic sign, a text and an image by a natural language processing (NLP) module through artificial intelligence.

[0078] According to one embodiment, the non-transitory storage medium also enables: using a first data set to pre-train an artificial intelligence module to recognize, interpret and understand one or more scenarios, wherein the first data set includes one or more traffic signs, one or more messages, one or more instructions, one or more texts, one or more images and one or more videos.

[0079] According to one embodiment, the non-transitory storage medium further causes: training the artificial intelligence module using the second data set to learn, improve and understand the one or more scenarios in an optimized manner.

[0080] According to one embodiment, the non-transitory storage medium further enables: the one or more scenarios to be interpreted and analyzed by an artificial intelligence module, and commands to be transmitted to the electric drive unit based on the one or more scenarios.

[0081] According to one embodiment, the non-transitory storage medium further causes: dynamically adjusting the adjustable roof rack to reduce an overall height of the vehicle.

[0082] According to one embodiment, the non-transitory storage medium further causes: dynamically adjusting the adjustable roof rack to one of a first level, a second level, and a third level.

[0083] According to one embodiment, the non-transitory storage medium further causes: dynamically adjusting the adjustable roof rack to one of a first level, a second level, and a third level based on a command received from an artificial intelligence module.

[0084] According to one embodiment, the non-transitory storage medium also enables: detecting the one or more objects attached to the vehicle; determining the total width of the vehicle, wherein the total width of the vehicle includes a first width of the vehicle and a second width of the one or more objects; obtaining the first driving route for the vehicle to reach the destination point; extracting the first width limitation information of the one or more first limiting obstacles located along the first driving route; determining a first clearance width based on the total width of the vehicle and the first width limitation information of the one or more first limiting obstacles; and when the first clearance width is greater than a threshold clearance width, calculating a second probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true.

[0085] According to one embodiment, the non-transitory storage medium further enables: when the second probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles is calculated to be false, a command is transmitted to the electric drive unit of the vehicle through a communication module.

[0086] According to one embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0087] The methods and systems disclosed herein may be implemented in any device for implementing various aspects, and may be executed in the form of a non-transitory machine-readable medium embodying an instruction set, which, when executed by a machine, causes the machine to perform any operations disclosed herein. Other features will be apparent from the accompanying drawings and the detailed description below. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Various aspects of the present disclosure will now be described in more detail with reference to the accompanying drawings showing exemplary embodiments, in which:

[0089] Figure 1 A system according to one or more embodiments is shown.

[0090] Figure 2 Components of a vehicle are shown according to one or more embodiments.

[0091] Figure 3A and Figure 3B A vehicle is shown approaching a restricted obstacle according to one or more embodiments.

[0092] Figure 4 A system according to one or more embodiments is shown.

[0093] Figure 5 Methods according to one or more embodiments are shown.

[0094] Figure 6 A non-transitory storage medium executed by a processor according to one or more embodiments is shown.

[0095] Figure 7 A flow chart is shown for determining the overall height of a vehicle including an overhead load and providing assistance to the vehicle in accordance with one or more embodiments.

[0096] Figure 8 Vehicle-to-vehicle data transmission is shown according to one or more embodiments.

[0097] Fig. 9A and 9B Determination of the overall height of a vehicle and the distance between the vehicle and a limiting obstacle is shown according to one or more embodiments.

[0098] Fig. 10A , 10B 10C illustrate a sample message received by a target vehicle according to one or more embodiments.

[0099] Fig.11A A block diagram of a network security module for a system and a server is shown.

[0100] Fig. 11B One embodiment of a network security module is shown.

[0101] Fig. 11C Another embodiment of a network security module is shown.

[0102] Fig. 12A Shown is the structure of a neural network / machine learning model with a feedback loop.

[0103] Fig. 12B The structure of a neural network / machine learning model with reinforcement learning is shown.

[0104] Fig.13 An adjustable roof rack is shown according to one or more embodiments.

[0105] Other features of the present embodiments will be apparent from the accompanying drawings and the following detailed description. DETAILED DESCRIPTION

[0106] For simplicity and clarity of illustration, the drawings illustrate the general manner of construction. The description and drawings may omit descriptions and details of well-known features and techniques to avoid unnecessarily obscuring the present disclosure. The drawings exaggerate the size of some elements relative to other elements to help improve the understanding of the embodiments of the present disclosure. The same reference numerals in different drawings represent the same elements.

[0107] Although the detailed description herein contains many specifics for the purpose of illustration, one of ordinary skill in the art will appreciate that many variations and changes to the details are considered to be included herein.

[0108] Therefore, the examples herein do not have any loss of generality to any of the claims set forth, nor do they impose limitations thereon. The terms used herein are for the purpose of describing specific embodiments only and are not limiting. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present disclosure belongs.

[0109] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0110] As used herein, the qualifiers "a" and "an" refer to one or more than one (i.e., at least one) of the grammatical object of the qualifier. For example, "an / an element" means one element or more than one element. In addition, the use of the qualifiers "a" and "an" in this specification and the drawings is to be interpreted as meaning "one or more" unless otherwise specified or the context clearly indicates a singular form.

[0111] As used herein, the terms "example" and / or "exemplary" are meant to serve as an example, instance, or illustration. For the avoidance of doubt, such examples do not limit the subject matter described herein. Furthermore, any aspect or design described herein as "example" and / or "exemplary" is not necessarily preferred or advantageous over other aspects or designs, nor does it exclude equivalent exemplary structures and techniques known to those of ordinary skill in the art.

[0112] As used herein, the terms "first", "second", "third", etc. (if any) in the specification and claims distinguish similar elements and do not necessarily describe a specific sequence or chronological order. These terms are interchangeable where appropriate, so that the embodiments of this document can, for example, operate in a sequence different from that shown or otherwise described herein. In addition, the terms "including", "having" and any variations thereof cover non-exclusive inclusions, so that the process, method, system, article, device or equipment including a list of elements is not necessarily limited to those elements, but may include other elements that are not explicitly listed or inherent to such processes, methods, systems, articles, devices or equipment.

[0113] As used herein, the terms "left", "right", "front", "back", "top", "bottom", "upper", "lower", etc., if any, in the specification and claims are used for descriptive purposes and not necessarily for describing permanent relative positions. The terms so used are interchangeable where appropriate, such that embodiments of the apparatus, methods, and / or articles described herein are, for example, capable of operation in other orientations than those illustrated or otherwise described herein.

[0114] Unless so clearly described, any element action or instruction used in this article is not critical or necessary. In addition, the term "set" includes items (e.g., related items, unrelated items, combinations of related items and unrelated items, etc.) and can be interchanged with "one or more". In the case of only one item expected, the term "one" or similar language is used. In addition, the terms "having", "containing", "including", etc. are open terms. In addition, unless otherwise clearly stated, the phrase "based on" means "based at least in part on".

[0115] As used herein, the terms "system", "device", "unit" and / or "module" refer to different components, component parts or components of each level of structure. However, other expressions that achieve the same purpose can replace these terms.

[0116] As used herein, the terms "coupled", "coupled", etc. refer to connecting two or more elements mechanically, electrically, and / or otherwise. Two or more electrical elements may be electrically coupled together, but not mechanically or otherwise coupled together. The coupling / coupling may last for any length of time, such as permanently or semi-permanently or only for a moment. "Electrically coupled" includes all types of electrical couplings. The absence of the words "removable", "removably", etc. near the words "coupled / coupling", etc. does not mean that the coupling / coupling, etc. in question is or is not removable.

[0117] As used herein, the term "or" refers to an inclusive "or" rather than an exclusive "or." That is, unless specified otherwise or clear from the context, "X employs A or B" is intended to mean any of the natural inclusive permutations. That is, if X employs A; X employs B; or X employs both A and B, then "X employs A or B" is satisfied in any of the foregoing instances.

[0118] As used herein, two or more elements or modules are “unitary” or “integrated” if they functionally operate together. Two or more elements are “non-unitary” if each element can functionally operate independently.

[0119] As used herein, the term "real time" refers to operations performed as quickly as possible when a triggering event occurs. A triggering event can include the receipt of data necessary for performing a task or otherwise processing information. Due to the inherent delays in transmission and / or computing speeds, the term "real time" encompasses operations that occur in a "near" real time or slightly delayed manner from a triggering event. In a number of embodiments, "real time" can represent real time minus the time delay for processing (e.g., determining) and / or transmitting data. A specific time delay can vary according to the type and / or amount of data, the processing speed of the hardware, the transmission capability of the communication hardware, the transmission distance, etc. However, in many embodiments, the time delay can be less than approximately one second, two seconds, five seconds, or ten seconds.

[0120] As used herein, the term "approximately" can mean within a specified or unspecified range of a specified or unspecified stated value. In some embodiments, "approximately" can mean within plus or minus ten percent of the stated value. In other embodiments, "approximately" can mean within plus or minus five percent of the stated value. In other embodiments, "approximately" can mean within plus or minus three percent of the stated value. In other embodiments, "approximately" can mean within plus or minus one percent of the stated value.

[0121] Digital electronic circuits or computer software, firmware or hardware, including the structures disclosed herein and their structural equivalents, or a combination of one or more of them, can implement the implementations and all functional operations described herein. The implementation can be one or more computer program products, that is, one or more modules of computer program instructions encoded on a computer-readable medium, for being executed by a data processing device or controlling the operation of a data processing device. The computer-readable medium can be a combination of a machine-readable storage device, a machine-readable storage substrate, a memory device, a combination of substances that affect a machine-readable propagation signal, or a combination of one or more of them. The term "computing system" covers all devices, devices and machines for processing data, including, for example, a programmable processor, a computer or multiple processors or computers. In addition to hardware, the device can also include code that creates an execution environment for the computer program in question, for example, code that constitutes a processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them. A propagation signal is an artificially generated signal (e.g., a machine-generated electrical signal, an optical signal, or an electromagnetic signal) that encodes information for transmission to a suitable receiver device.

[0122] The actual dedicated control hardware or software code used to implement these systems and / or methods is not limited to these implementations. Therefore, any software and any hardware can implement the systems and / or methods based on the description of this article without referring to specific software codes.

[0123] A computer program (also referred to as a program, software, software application, script, or code) is written in any suitable form of a programming language, including compiled or interpreted languages. It can be deployed in any suitable form, including a stand-alone program or a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program may be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions). A computer program may be executed on a single computer or on multiple computers located at one site or distributed across multiple sites and interconnected by a communications network.

[0124] One or more programmable processors execute one or more computer programs to perform functions by operating on input data and generating output, performing the processes and logic flows described herein. The processes and logic flows may also be performed by a dedicated logic circuit, and the device may also be implemented as a dedicated logic circuit, such as, but not limited to, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), an application specific standard product (ASSP), a system on a chip (SOC) type system, a complex programmable logic device (CPLD), etc.

[0125] Processors suitable for executing computer programs include, for example, general-purpose microprocessors and special-purpose microprocessors, and any one or more processors of digital computers of any suitable type. The processor will receive instructions and data from a read-only memory or a random access memory or both. The elements of a computer can include a processor for executing instructions and one or more memory devices for storing instructions and data. The computer will also include one or more large-capacity storage devices (such as magnetic disks, magneto-optical disks, optical disks, or solid-state disks) for storing data, or be operably coupled to receive data from the one or more large-capacity storage devices, transmit data to the one or more large-capacity storage devices, or both. However, the computer does not need to have such a device. In addition, another device, for example, a mobile phone, a personal digital assistant (PDA), a mobile audio player, a global positioning system (GPS) receiver, etc. can be embedded in the computer. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, including, for example, semiconductor memory devices (e.g., erasable programmable read-only memory (EPROM), electronically erasable programmable read-only memory (EEPROM), and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks (e.g., compact disk read-only memory (CD ROM) disks, digital versatile disk read-only memory (DVD-ROM) disks), and solid-state disks. Special purpose logic circuits may supplement or be incorporated in the processor and memory.

[0126] To provide interaction with a user, a computer may have a display device, such as a cathode ray tube (CRT) or liquid crystal display (LCD) monitor, for displaying information to the user, and a keyboard and pointing device, such as a mouse or trackball, through which the user can provide input to the computer. Other kinds of devices also provide interaction with the user. For example, feedback to the user may be any suitable form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and a computer may receive input from a user in any suitable form, including acoustic, voice, or tactile input.

[0127] A computing system that includes a back-end component (e.g., a data server), or includes a middleware component (e.g., an application server), or includes a front-end component (e.g., a client computer with a graphical user interface or a web browser through which a user can interact with the implementation), or any suitable combination of one or more such back-end, middleware, or front-end components can implement the implementations described herein. Any suitable form or medium of digital data communication (e.g., a communication network) can interconnect the components of the system. Examples of communication networks include local area networks (LANs) and wide area networks (WANs), such as intranets and the Internet.

[0128] A computing system may include clients and servers. The clients and servers are remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0129] Embodiments may include or utilize a special or general purpose computer including computer hardware. Embodiments within the scope of the present invention may also include physical and other computer readable media for carrying or storing computer executable instructions and / or data structures. Such computer readable media can be any medium accessible to a general or special purpose computer system. A computer readable medium storing computer executable instructions is a physical storage medium. A computer readable medium carrying computer executable instructions is a transmission medium. Therefore, by way of example and not limitation, embodiments of the present invention can include at least two different types of computer readable media: a physical computer readable storage medium and a transmission computer readable medium.

[0130] Although the present embodiments described herein are with reference to specific example embodiments, it will be apparent that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the various embodiments. For example, hardware circuits (e.g., complementary metal oxide semiconductor (CMOS) based logic circuits), firmware, software (e.g., embodied in a non-transitory machine-readable medium), or any combination of hardware, firmware, and software may enable and operate the various devices, units, and modules described herein. For example, transistors, logic gates, and circuits (e.g., application specific integrated circuits (ASICs) and / or digital signal processor (DSP) circuits) may embody various electrical structures and methods.

[0131] In addition, non-transitory machine-readable media and / or systems may embody various operations, processes, and methods disclosed herein.Accordingly, the specification and drawings are illustrative rather than restrictive.

[0132] Physical computer-readable storage media include RAM, ROM, EEPROM, CD-ROM or other optical disk storage (such as CD, DVD, etc.), magnetic disk storage or other magnetic storage devices, solid-state disks or any other media. They store the desired program code in the form of computer-executable instructions or data structures that can be accessed by general or special computers.

[0133] As used herein, the term "network" may include the Internet, a local area network, a wide area network, or a combination thereof. A network may include one or more networks or communication systems, such as the Internet, a telephone system, a satellite network, a cable television network, and various other private and public networks. In addition, the connection may include a wired connection (such as a wire, a cable, an optical fiber line, etc.), a wireless connection, or a combination thereof. In addition, although not shown, other computers, systems, devices, and networks may also be connected to the network. A network refers to any set of devices or subsystems connected by a link that joins (directly or indirectly) a set of terminal nodes that share resources located on or provided by a network node. Computers communicate with each other using a public communication protocol through digital interconnection. For example, a subsystem may include a cloud. A cloud refers to a server accessed via the Internet, and the software and databases running on these servers.

[0134] Furthermore, upon reaching various computer system components, program code in the form of computer executable instructions or data structures can be automatically transferred from a transmission computer readable medium to a physical computer readable storage medium (or vice versa). For example, computer executable instructions or data structures received over a network or data link can be buffered in RAM within a network interface module (NIC) and then ultimately transferred to computer system RAM and / or a less volatile computer readable physical storage medium at the computer system. Thus, computer system components that also (or even primarily) utilize transmission media can include computer readable physical storage media.

[0135] For example, computer executable instructions include instructions and data that cause a general-purpose computer, a special-purpose computer, or a special-purpose processing device to perform a specific function or group of functions. Computer executable instructions can be, for example, binary, intermediate format instructions such as assembly language, or even source code. Although the subject matter described herein is in a language specific to structural features and / or method actions, the described features or described actions do not limit the subject matter defined in the claims. On the contrary, the features and actions described herein are example forms of implementing the claims.

[0136] Although this specification contains many details, these are not to be construed as limitations on the scope of the present disclosure or claims, but rather as descriptions of features that are specific to a particular implementation. A single implementation may implement certain features described in this specification in the context of a separate implementation. Conversely, multiple implementations may implement various features described in the context of a single implementation individually or in any suitable subcombination. In addition, although features described herein as functioning in certain combinations and even initially claimed as such, in some cases, one or more features from a claimed combination may be removed from the combination, and a claimed combination may be directed to a subcombination or a variation of a subcombination.

[0137] Similarly, although operations are depicted in the drawings herein in a particular order to achieve desired results, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desired results. In some cases, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system components in the embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems may be integrated together in a single software product or packaged into multiple software products.

[0138] Even though particular combinations of features are recited in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of possible implementations. Other implementations fall within the scope of the claims. For example, the actions recited in the claims can be performed in a different order and still achieve the desired results. In fact, many of these features can be combined in ways not specifically recited in the claims and / or disclosed in the specification. Although each dependent claim may directly refer to only one claim, the disclosure of possible implementations includes the combination of each dependent claim with every other claim in the claim group.

[0139] In addition, a computer system including one or more processors and a computer-readable medium such as a computer memory can practice these methods. Specifically, one or more processors execute computer-executable instructions stored in the computer memory to perform various functions, such as the actions described in the embodiments.

[0140] Those skilled in the art will appreciate that the present invention can be implemented in a network computing environment with many types of computer system configurations, including personal computers, desktop computers, laptop computers, message processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, pagers, routers, switches, etc. The present invention can also be implemented in a distributed system environment in which local and remote computer systems that are linked by a network (by a hardwired data link, a wireless data link, or by a combination of a hardwired and wireless data link) all perform tasks. In a distributed system environment, program modules can be located in both local and remote memory storage devices.

[0141] Unless otherwise indicated, the following terms and phrases shall be understood to have the following meanings.

[0142] As used herein, the term "cryptographic protocol" is also referred to as a security protocol or encryption protocol. It is an abstract or concrete protocol that performs security-related functions and applies cryptographic methods that are usually sequences of cryptographic primitives. The protocol describes the use of an algorithm. A sufficiently detailed protocol includes details about data structures and representations to implement multiple interoperable versions of a program. Cryptographic protocols are widely used for secure application-level data transport. Cryptographic protocols typically include at least some of the following aspects: key negotiation or establishment, entity authentication, symmetric encryption and message authentication, secure application-level data transport, non-repudiation methods, secret sharing methods, and secure multi-party computation. Hash algorithms can be used to verify the integrity of data. Secure Socket Layer (SSL) and Transport Layer Security (TLS) (SSL's successor) are cryptographic protocols that network switches can use to protect data communications on the network.

[0143] Secure application-level data transport widely uses cryptographic protocols. Cryptographic protocols typically include at least some of the following aspects: key negotiation or establishment, entity authentication, symmetric encryption, and message authentication material construction, secure application-level data transport, non-repudiation methods, secret sharing methods, and secure multi-party computation.

[0144] Network switches use cryptographic protocols such as Secure Sockets Layer (SSL) and Transport Layer Security (TLS), the successor to SSL, to secure data communications on wireless networks.

[0145] As used herein, the term "unauthorized access" means that someone uses another person's account or other methods to gain access to a website, program, server, service, or other system. For example, if someone keeps guessing passwords or usernames for accounts that do not belong to them until they gain access, this is considered unauthorized access.

[0146] As used herein, the term “IoT” stands for the Internet of Things, which describes a network of physical “things” or objects embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet.

[0147] As used herein, "machine learning" refers to an algorithm that gives a computer the ability to learn without explicit programming, including algorithms that learn from data and predict data. Machine learning techniques include, but are not limited to, support vector machines, artificial neural networks (ANNs) (also referred to herein as "neural networks"), deep learning neural networks, logistic regression, discriminant analysis, random forests, linear regression, rule-based machine learning, naive Bayes, nearest neighbors, decision trees, decision tree learning, and hidden Markov, etc. For clarity, a part of the machine learning process can use algorithms such as linear regression or logistic regression. However, using linear regression or another algorithm as part of the machine learning process is different from using a spreadsheet program to perform statistical analysis such as regression. The machine learning process can continuously learn and adjust the classifier as new data becomes available, and does not rely on explicit or rule-based programming. ANN can be characterized by a feedback loop to dynamically adjust the system output when new data becomes available because it learns from the new data. In machine learning, back propagation and feedback loops are used to train artificial intelligence / machine learning (AI / ML) models to improve the accuracy and performance of the model over time.

[0148] Statistical modeling relies on discovering relationships between variables (like mathematical equations) to predict outcomes.

[0149] As used herein, the term "data mining" is the process used to transform raw data into useful information.

[0150] As used herein, the term "data acquisition" is the process of sampling signals that measure real-world physical conditions and converting the resulting samples into digital values ​​that are processed by a computer. Data acquisition systems typically convert analog waveforms into digital values ​​for processing. Components of a data acquisition system include sensors that convert physical parameters into electrical signals, signal conditioning circuits that convert sensor signals into a form that can be converted into digital values, and analog-to-digital converters that convert the conditioned sensor signals into digital values. Standalone data acquisition systems are often referred to as dataloggers.

[0151] As used herein, the term "dashboard" is a type of interface that visualizes specific key performance indicators (KPIs) for a specific goal or process. It is based on data visualization and infographics.

[0152] As used herein, a "database" is a collection of information organized so that it can be easily accessed, managed, and updated. A computer database typically contains an aggregation of data records or files.

[0153] As used herein, the term "data set" or "Dataset" is a collection of data. In the case of tabular data, a data set corresponds to one or more database tables, where each column of the table represents a specific variable and each row corresponds to a given record of the data set in question. A data set lists the value of each variable for each member of the data set, such as the height and weight of an object. Each value is called a datum. A data set can also consist of a collection of documents or files.

[0154] As used herein, a "sensor" is a device that measures physical input from its environment and converts it into data that can be interpreted by a person or machine. Most sensors are electronic and present electronic data, but some are simpler, such as a glass thermometer, and present visual data.

[0155] In one embodiment, the sensors may be removably or fixedly mounted within the vehicle and may be arranged in various arrangements to provide information to the autonomous operating features. The sensors may include one or more of a GPS unit, a radar unit, a light detection and ranging (LIDAR, also known as a laser radar) unit, an ultrasonic sensor, an infrared sensor, an inductive sensor, a camera, an accelerometer, a tachometer, or a speedometer. Some sensors (e.g., radar, LIDAR, or camera units) may actively or passively scan the vehicle environment for obstacles (e.g., other vehicles, buildings, pedestrians, etc.), roads, lane markings, signs, or signals. Other sensors (e.g., GPS, accelerometer, or tachometer units) may provide data for determining the location or movement of the vehicle (e.g., via GPS coordinates, dead reckoning, wireless signal triangulation, etc.).

[0156] As used herein, the term "stadiometer" refers to a device for measuring height having a vertical measuring plate and a horizontal headboard. The device can be used to measure the height of objects and the height of vehicles. The device consists of a vertical ruler with a sliding horizontal rod or paddle that is adjusted to rest on top of the head. The device can be a portable device. The device can also be used to measure the height of a portion of an object.

[0157] As used herein, the term "vehicle" refers to an object used to transport people or goods. Cars, cars, trucks, buses, etc. are examples of vehicles.

[0158] The term "electronic control unit" (ECU), also known as "electronic control module" (ECM), is generally a module that controls one or more subsystems. Here, an ECU can be installed in a car or other motor vehicle. It can refer to many ECUs, and can include but is not limited to an engine control module (ECM), a powertrain control module (PCM), a transmission control module (TCM), a brake control module (BCM) or an electronic brake control module (EBCM), a central control module (CCM), a central timing module (CTM), a general electronic module (GEM), a body control module (BCM), and a suspension control module (SCM). ECUs are sometimes collectively referred to as the vehicle's computer or the vehicle's central computer, and may include a separate computer. In one example, an electronic control unit can be an embedded system in the automotive electronics. In another example, the electronic control unit is wirelessly coupled to the automotive electronics.

[0159] The terms "non-transitory computer-readable medium" and "computer-readable medium" include a single medium or multiple media, such as a centralized or distributed database, and / or associated caches and servers that store one or more sets of instructions. Furthermore, the terms "non-transitory computer-readable medium" and "computer-readable medium" include any tangible medium that can store, encode, or carry a set of instructions for execution by a processor, which, when executed, causes a system to perform any one or more of the methods or operations disclosed herein. As used herein, the term "computer-readable medium" is expressly defined to include any type of computer-readable storage device and / or storage disk, and to exclude propagating signals.

[0160] As used herein, the term “vehicle data bus” refers to an interface to a vehicle data bus (e.g., CAN, LIN, Ethernet / IP, FlexRay, and MOST) that enables communication between vehicle onboard equipment (OBE) and other vehicle systems to support connected vehicle applications.

[0161] The term "handshaking" refers to the exchange of predetermined signals between agents connected by a communication channel to ensure that each agent is connected to the other agent (and not to an imposter). This can also include the use of passwords and codes by operators. Handshaking signals are transmitted back and forth across the communication network to establish a valid connection between two stations. Hardware handshaking uses dedicated wires in RS-232 serial transmissions, such as the Request to Send (RTS) and Clear to Send (CTS) lines. Software handshaking sends codes such as "synchronize" (SYN) and "acknowledge" (ACK) in TCP / IP transmissions.

[0162] The term "infotainment system" or "in-vehicle infotainment system" (IVI) as used herein refers to a combination of vehicle systems for delivering entertainment and information. In one example, the information can be delivered to the driver and passengers / occupants of the vehicle through audio / video interfaces, control elements such as touch screen displays, button panels, voice commands, etc. Some of the major components of an in-vehicle infotainment system are an integrated head-unit, heads-up display (also known as head-up display), high-end digital signal processors (DSPs) and graphics processing units (GPUs) to support multiple displays, operating systems, controller area networks (CAN), low voltage differential signaling (LVDS) and other network protocol support (as required), connectivity modules, automotive sensor integration, digital instrument clusters, etc.

[0163] As used herein, the term "control module" refers to those parts of a digital computer that coordinate the execution of instructions in the proper sequence, the interpretation of each instruction, and the application of appropriate signals to the arithmetic unit and other parts based on the interpretation. A control unit or control module may refer to an electronic control unit or subsystem of an ECU, and may refer to a functional unit in an electronic control unit or subsystem that controls one or more units of vehicle equipment.

[0164] As used herein, the term "environment" or "surroundings" refers to the environment and space that the vehicle is navigating in. It refers to the dynamic environment in which the vehicle is traveling, including other vehicles, obstacles, pedestrians, lane boundaries, traffic signs and signals, speed limits, potholes, snow, standing water, etc.

[0165] As used herein, the term "autonomous mode" refers to an independent and unsupervised mode of operation.

[0166] As used herein, the term "autonomous communication" includes communication in different scenarios within a period of time with minimal supervision, and is not solely or completely based on pre-coded scenarios or pre-coded rules or pre-defined protocols. Generally speaking, autonomous communication occurs in an independent and unsupervised manner. In one embodiment, the communication module enables autonomous communication.

[0167] As used herein, the term "autonomous vehicle," also known as a self-driving vehicle, unmanned vehicle, or robotic vehicle, refers to a vehicle that incorporates vehicle automation, i.e., a ground vehicle that is able to sense its environment and move safely with little or no human input. Self-driving vehicles incorporate a variety of sensors to sense their surroundings, such as thermal imaging cameras, radio detection and ranging (RADAR), light detection and ranging (LIDAR), sound navigation and ranging (sonar), global positioning system (GPS), odometers, and inertial measurement units. A control system designed for this purpose interprets the sensor information to identify an appropriate navigation path as well as obstacles and related landmarks.

[0168] As used herein, the term "communication system" or "communication module" refers to a system that enables information exchange between two points. The process of transmitting and receiving information is called communication. The elements of communication include, but are not limited to, the transmitter of the information, the channel or medium of communication, and the receiver of the information.

[0169] As used herein, the term "connection" refers to a communication link. It refers to a communication channel that connects two or more devices for the purpose of data transfer. It can refer to a physical transmission medium, such as a wire, or to a logical connection through a multiplexed medium, such as a radio channel in telecommunications and a computer network. A channel is used to transmit information, such as a digital bit stream, from one or several transmitters to one or several receivers. A channel has a certain information transmission capacity, which is usually measured by its bandwidth in Hertz (Hz) or data rate in bits per second. For example, vehicle-to-vehicle (V2V) communication can wirelessly exchange information about the speed, location, and direction of surrounding vehicles.

[0170] The term "communication" as used herein refers to the transmission of information and / or data from one point to another. Communication can be by means of electromagnetic waves. Communication is also the flow of information from one point (called a source) to another point (called a receiver). Communication includes one of the following: transmission of data, instructions, information, or a combination of data, instructions and information. Communication occurs between any two communication systems or communication units. The term "communication with..." may refer to any coupling, connection or interaction using any system, hardware, software, protocol or mode to exchange information or data using electrical signals, whether the exchange occurs wirelessly or through a wired connection. The term communication includes systems that combine other more specific types of communication, such as: V2I (vehicle to infrastructure), V2N (vehicle to network), V2V (vehicle to vehicle), V2P (vehicle to pedestrian), V2D (vehicle to device), V2G (vehicle to grid) and vehicle to everything (V2X) communication.

[0171] In addition, the communication device is configured on a computer having a communication function, and performs two-way communication with the vehicle-mounted emergency reporting device by means of a communication line through a radio station and a communication network such as a public telephone network or by means of satellite communication through a communication satellite. The communication device is suitable for communicating with the communication terminal through the communication network.

[0172] The term "vehicle-to-vehicle (V2V) communication" refers to technology that allows vehicles to broadcast and receive messages. The messages can be omnidirectional, creating a 360-degree "awareness" of other vehicles in the vicinity. Vehicles can be equipped with appropriate software (or safety applications or safety situation detection) that can use information from surrounding vehicles to determine potential collision threats as they progress.

[0173] As used herein, the term "protocol" refers to the procedures required to initiate and maintain communications; a formal set of conventions governing the format and relative timing of message exchanges between two communicating terminals; a set of conventions governing the interaction of processes, devices, and other components within a system; a set of signaling rules for passing information or commands between boards connected to a bus; a set of signaling rules for passing information between agents; a set of semantic and syntactic rules that determine the behavior of interacting entities; a set of rules and formats (semantics and syntax) that determine the communication behavior of simulated applications; a set of conventions or rules governing the interaction of processes or applications within a computer system or network; a set of formal conventions governing the format and relative timing of message exchanges in a computer system; a set of semantic and syntactic rules that determine the behavior of functional units in achieving meaningful communications; a set of semantic and syntactic rules for exchanging information.

[0174] As used herein, the term "Vehicle-to-Everything (V2X) communication" refers to the transmission of information from a vehicle to any entity that may affect the vehicle, and vice versa. There are two types of V2X communication technologies, depending on the underlying technology employed: cellular networks and other technologies that support direct device-to-device communication (such as Dedicated Short Range Communication (DSRC), Port Community System (PCS), wait).

[0175] As used herein, the term "communication protocol" refers to standardized communications between any two systems. An example communication protocol is the DSRC protocol. The DSRC protocol uses a specific frequency band (e.g., 5.9 GHz (gigahertz)) and a specific message format (e.g., basic safety messages, signal phase and timing, and roadside warnings) to enable communications between vehicles and infrastructure components (e.g., traffic signals and roadside sensors). DSRC is a standardized protocol whose specifications are maintained by various organizations, including the Institute of Electrical and Electronics Engineers (IEEE) and the Society of Automotive Engineers (SAE).

[0176] The term "two-way communication" as used herein refers to the exchange of data between two components. In one example, the first component can be a vehicle, and the second component can be an infrastructure that can be used through a system of hardware, software, and firmware.

[0177] The term "alert" or "alert signal" refers to a communication that draws attention. Alerts may include visual, tactile, audible alerts, and combinations of these alerts to alert the driver or passengers. These alerts allow the recipient, such as the driver or passenger, to react and respond quickly.

[0178] As used herein, the term "communicates with" refers to any coupling, connection, or interaction using signals to exchange information, messages, instructions, commands, and / or data using any system, hardware, software, protocol, or format, whether the exchange occurs wirelessly or through a wired connection.

[0179] As used herein, the term "traffic signal" refers to a light used to control the movement of traffic. Traffic signals can be set up at road intersections and crossroads. Traffic signals usually consist of three signals that convey meaningful information to drivers and passengers through colors and symbols (including arrows and bicycles). Conventional traffic signal colors are red, yellow (also called amber), and green arranged vertically or horizontally. Although this is standardized internationally, there are national and local differences in traffic signal sequences and laws.

[0180] As used herein, the term "electric drive unit" refers to a unit capable of controlling the operation of various devices of an autonomous vehicle. The electric drive unit is responsible for achieving the mobility of the vehicle.

[0181] As used herein, the term "limiting obstacle" refers to an object that blocks or impedes the path or route of a vehicle, or prevents the vehicle from moving or progressing toward a destination point by causing difficulty (eg, a collision).

[0182] As used herein, the term "threshold clearance height" refers to the minimum clearance height required for a vehicle to move without collision. The threshold clearance height may also be the minimum clearance (e.g., gap) for a vehicle to move under a restrictive obstacle (e.g., an underpass, a bridge, a tree, a tunnel, a roof structure, a building, a parking area, etc.). Below the threshold clearance, a vehicle, loaded or unloaded, may collide with a restrictive obstacle.

[0183] As used herein, the term "threshold clearance width" refers to the minimum clearance width required for a vehicle to move without collision. The threshold clearance width may also be the minimum clearance (e.g., gap) for a vehicle to move under a restrictive obstacle (e.g., an underpass, a bridge, a tree, a tunnel, a roof structure, a building, a parking area, etc.). Below the threshold clearance, a vehicle, loaded or unloaded, may collide with a restrictive obstacle.

[0184] As used herein, the term “Third Party Service” means any unaffiliated individual, company, or entity that performs services for the Company. A Third Party Service Provider may receive compensation for its services but has no share, stock, or equity in the Company. The services of a Third Party Service Provider may also be free of charge. A Third Party Service Provider may also be web-based technology that is not exclusively operated or controlled by a Government Entity or involves substantial participation by a non-Government Entity.

[0185] As used herein, the term "overall height" refers to the height of a vehicle from the ground to the top of the vehicle with or without a load on the roof (e.g., a luggage rack). The overall height refers to the sum of the height of the vehicle and the maximum height of one or more loads. For example, consider a vehicle with one or more loads on a luggage rack on the roof. The vehicle height is 2.5 meters. One load has a height of 0.25 meters and another load has a height of 0.50 meters. The overall height of the vehicle is then 2.5 + 0.5 (maximum height among the loads) = 3 meters. As another example, consider a vehicle with no load on the roof luggage rack. The vehicle height is 2.5 meters. The overall height of the vehicle is then 2.5 meters. The height of the vehicle includes the height of the luggage rack (i.e., from the ground to the top of the luggage rack).

[0186] As used herein, the term "safe passage" means that the vehicle passes through the restraining barrier without collision. The vehicle together with the load does not make any contact with the surface of the restraining barrier on all sides (e.g., top, bottom, sides, etc.). Safe passage also means that the vehicle passes through the restraining barrier without causing any damage or even scratches to the vehicle and one or more objects attached to the vehicle (e.g., load).

[0187] As used herein, the term "probability" refers to the likelihood of the outcome of any random event. Probability can be defined as the ratio of the number of favorable outcomes to the total number of outcomes of the event. Probability also refers to the chance of an event occurring.

[0188] As used herein, the term "true" refers to the unknown actual probability that an event will occur under given circumstances.

[0189] As used herein, the term "false" refers to the unknown actual probability that an event will not occur under given circumstances.

[0190] As used herein, the term "real-time location" refers to the real-time location of a person or thing (eg, a vehicle, a restricted obstacle, etc.). The real-time location may be determined continuously or upon interrogation.

[0191] As used herein, the term "video analytics" refers to a practical solution for reviewing hours of video (e.g., surveillance video) to identify incidents related to what you are looking for. Video analytics is suitable for automatically generating a description of what is actually happening in the video (so-called metadata), which can be used to list the people, cars and other objects detected in the video stream (e.g., intersections, signals, crossroads, traffic, congestion, obstacles, etc.), as well as their appearance and movement.

[0192] As used herein, the term "destination point" refers to a target location of a vehicle.

[0193] The term “cybersecurity” as used herein refers to the application of technologies, processes, and controls to protect systems, networks, programs, devices, and data from cyber-attacks.

[0194] The term "cybersecurity module" as used herein refers to a module that includes the application of technologies, processes and controls to protect systems, networks, programs, devices and data from cyber attacks and threats. It is designed to reduce the risk of cyber attacks and prevent unauthorized exploitation of systems, networks and technologies. It includes but is not limited to critical infrastructure security, application security, network security, cloud security, Internet of Things (IoT) security.

[0195] The term "encrypt" as used herein refers to the use of one or more mathematical techniques and a password or "key" for decrypting information to protect digital data, and refers to the conversion of information or data into code, especially to prevent unauthorized access. It can also refer to hiding information or data by converting it into code. It can also be called a cipher, code, encipher, encoding. A simple example is to represent the alphabet with numbers - for example, "A" is "01", "B" is "02", and so on. For example, a message like "HELLO" will be encrypted as "0805121215", and this value will be transmitted to the recipient over the network.

[0196] The term "decryption" as used herein refers to the process of converting an encrypted message back to its original format. It is generally the reverse process of encryption. It decodes the encrypted information so that only authorized users can decrypt the data, as a secret key or password is required for decryption. The term can be used to describe methods of decrypting data manually or using an appropriate code or key.

[0197] The term "cybersecurity threat" as used herein refers to any possible malicious attack that attempts to illegally access data, disrupt digital operations, or destroy information. Malicious behavior includes, but is not limited to, destroying data, stealing data, or disrupting digital life. Cyber ​​threats include, but are not limited to, malware, spyware, phishing attacks, ransomware, zero-day exploits, Trojans, advanced persistent threats, wiper attacks, data manipulation, data destruction, rogue software, malicious advertising, unpatched software, computer viruses, man-in-the-middle attacks, data breaches, denial of service (DoS) attacks, and other attack vectors.

[0198] The term "hash value" as used herein can be thought of as a fingerprint of a file. The contents of a file are processed through an encryption algorithm and a unique value (i.e., a hash value) is generated to identify the contents of the file. If the content is modified in any way, the hash value will also change significantly. Example algorithms for generating hash values: Message Digest-5 (MD5) algorithm and Secure Hash Algorithm-1 (SHA1).

[0199] The term "integrity verification" as used herein refers to verifying the accuracy and consistency of system-related files, data, etc. It can be performed using verification tools that can detect whether any critical system files have been changed, thereby enabling system administrators to look for unauthorized changes to the system. For example, data integrity corresponds to the quality of data in a database and the level at which users verify data quality, integrity, and reliability. Data integrity verification verifies that the data in a database is accurate and operates as expected in a given application.

[0200] The term "alert" as used herein refers to a trigger when a system or a component in a system fails or does not perform as expected. A system may enter an alert state when a specific event occurs. An alert indicator signal is a visual signal indicating an alert state. For example, when a network security threat is detected, an alert may be issued to a system administrator via an audible alert, a message, an illuminated LED, a pop-up window, etc. The alert indicator signal may be reported downstream of the detection device to prevent adverse conditions or cascading effects.

[0201] The term "autonomous vehicle" as used herein, also known as self-driving vehicle, unmanned vehicle, robotic vehicle, refers to a vehicle that incorporates vehicle automation, that is, a ground vehicle that can sense its environment and move safely with little or no human input. Self-driving vehicles incorporate a variety of sensors to perceive their surroundings, such as thermal imaging cameras, radio detection and ranging (RADAR), light detection and ranging (LIDAR, also known as laser radar), sound navigation and ranging (sonar), global positioning system (GPS), odometer, and inertial measurement unit. A control system designed for this purpose interprets the sensor information to identify the appropriate navigation path as well as obstacles and related landmarks.

[0202] As used herein, the term "connection" refers to a communication link. It refers to a communication channel that connects two or more devices for the purpose of data transfer. It can refer to a physical transmission medium, such as a wire, or to a logical connection through a multiplexed medium, such as a radio channel in telecommunications and a computer network. A channel is used to transmit information, such as a digital bit stream, from one or several transmitters to one or several receivers. A channel has a certain information transmission capacity, which is usually measured by its bandwidth in Hertz (Hz) or data rate in bits per second. For example, vehicle-to-vehicle (V2V) communication can wirelessly exchange information about the speed, location, and direction of surrounding vehicles.

[0203] As used herein, the term "communication" refers to the transmission of information and / or data from one point to another. Communication can be by means of electromagnetic waves. Communication is also the flow of information from one point (called the source) to another point (called the receiver). Communication includes one of the following: transmitting data, instructions, information, or a combination of data, instructions and information. Communication occurs between any two communication systems or communication units.

[0204] The term "communicates with" may refer to any coupling, connection, or interaction using any system, hardware, software, protocol, or mode to exchange information or data using electrical signals, whether the exchange occurs wirelessly or through a wired connection. The term communicate includes systems that combine other more specific types of communications, such as: V2I (vehicle to infrastructure), V2N (vehicle to network), V2V (vehicle to vehicle), V2P (vehicle to pedestrian), V2D (vehicle to device), V2G (vehicle to grid), and vehicle to everything (V2X) communications. V2X communications refer to the transmission of information from a vehicle to any entity that may affect the vehicle, and vice versa. The main motivations for developing V2X are occupant safety, road safety, traffic efficiency, and energy efficiency. Depending on the underlying technology adopted, there are two types of V2X communication technologies: cellular networks and other technologies that support direct device-to-device communication (such as dedicated short-range communications (DSRC), port community systems (PCS), wait).

[0205] As used herein, the term "vehicle-to-vehicle (V2V) communication" refers to technology that allows vehicles to broadcast and receive messages. The messages can be omnidirectional, creating a 360-degree "awareness" of other vehicles in the vicinity. Vehicles can be equipped with appropriate software (or safety applications or safety situation detection) that can use information from surrounding vehicles to determine potential collision threats as they progress.

[0206] The term "protocol" as used herein refers to the procedures required to initiate and maintain communications; a formal set of conventions governing the format and relative timing of message exchanges between two communicating terminals; a set of conventions governing the interaction of processes, devices, and other components within a system; a set of signaling rules for passing information or commands between boards connected to a bus; a set of signaling rules for passing information between agents; a set of semantic and syntactic rules that determine the behavior of interacting entities; a set of rules and formats (semantics and syntax) that determine the communication behavior of simulated applications; a set of conventions or rules governing the interaction of processes or applications within a computer system or network; a set of formal conventions governing the format and relative timing of message exchanges in a computer system; a set of semantic and syntactic rules that determine the behavior of functional units in achieving meaningful communication; a set of semantic and syntactic rules for exchanging information.

[0207] The term "communication protocol" as used herein refers to standardized communications between any two systems. An example of a communication protocol is Health Level 7 (HL7). HL7 is an international set of standards for providing guidance for transmitting and sharing data between various medical providers. HL7 is a general framework for the exchange, integration, sharing, and retrieval of health information.

[0208] The term "two-way communication" as used herein refers to the exchange of data between two components. In one example, the first component can be a vehicle, and the second component can be an infrastructure that can be used through a system of hardware, software, and firmware.

[0209] As used herein, the term "nearby vehicle" refers to vehicles surrounding the user's vehicle and within or beyond at least the communication range of the user's vehicle, where the communication range is defined as the maximum distance at which communication can exist between two antennas, one of which is the user's vehicle antenna in a wireless network. In one embodiment, "nearby vehicles" are written as surrounding vehicles, trailing vehicles, or preceding vehicles. Nearby vehicles may also include vehicles from nearby lanes, oncoming lanes, or adjacent lanes.

[0210] The term "maneuvering" as used herein means to carefully move, steer, or steer a vehicle in order to move from one point to another.

[0211] The term "automatic brake" as used herein refers to an advanced system specifically designed to prevent a possible collision or reduce the speed of a moving vehicle before a collision with another vehicle, a pedestrian, or some restricted obstacle. The vehicle may include an automatic braking unit that receives commands from the electric drive unit or the control module.

[0212] As used herein, the term "probability" refers to the likelihood of the outcome of any random event (e.g., a vehicle passing a restricted obstacle safely without collision, etc.). This term means to examine the degree to which any event is likely to occur. The term probability can also be defined as the ratio of the number of favorable outcomes to the total number of event outcomes. Probability further refers to the chance of an event occurring.

[0213] As used herein, the term "height warning module" is generally a module that controls one or more subsystems. Here, the height warning module can be installed in a vehicle, a nearby vehicle, a restricted obstacle, or any other external infrastructure. In one example, the height warning module can be an embedded system in an automotive electronic device. In another example, the height warning module is wirelessly coupled to the automotive electronic device. The height warning module can communicate with the vehicle and provide assistance to the vehicle. The vehicle can be a manually driven vehicle, a self-driving vehicle, or an autonomous vehicle. In the case of a manually driven vehicle, the height warning module communicates with the vehicle and displays instructions or warnings or warnings or suggestions to the driver by displaying them on the dashboard. In the case of a self-driving vehicle or an autonomous vehicle, the height warning module transmits commands to the electric drive unit and / or control module of the vehicle to manipulate the vehicle according to the commands from the height warning module. The height warning module can provide commands such as braking commands (e.g., automatic braking, braking distance, etc.), maneuvering commands (e.g., maneuvering under a restricted obstacle in a place with maximum clearance, etc.), a green signal to pass a restricted obstacle, a red signal to stop before a restricted obstacle, and a yellow signal to carefully maneuver under a restricted obstacle (according to the command provided by the height warning module or autonomously). The height warning module works in conjunction with the width warning module.

[0214] As used herein, the term "width warning module" is generally a module that controls one or more subsystems. Here, the width warning module can be installed in a vehicle, a nearby vehicle, a limiting obstacle, or any other external infrastructure. In one example, the width warning module can be an embedded system in an automotive electronic device. In another example, the width warning module is wirelessly coupled to the automotive electronic device. The width warning module can communicate with the vehicle and provide assistance to the vehicle. The vehicle can be a manually driven vehicle, a self-driving vehicle, or an autonomous vehicle. In the case of a manually driven vehicle, the width warning module communicates with the vehicle and displays instructions or warnings or warnings or suggestions to the driver by displaying them on the dashboard. In the case of a self-driving vehicle or an autonomous vehicle, the width warning module transmits commands to the electric drive unit and / or control module of the vehicle to operate the vehicle according to the commands from the width warning module. The width warning module may provide commands such as braking instructions (e.g., automatic braking, braking distance, etc.), maneuvering commands (e.g., maneuver under a restrictive obstacle at a location with maximum clearance width, etc.), a green signal to pass a restrictive obstacle, a red signal to stop before a restrictive obstacle, and a yellow signal to carefully (according to commands provided by the width warning module or autonomously) maneuver through a restrictive obstacle without causing any damage or even scratches to the vehicle and / or one or more objects attached to the roof (e.g., load, packages, etc.). The width warning module works in conjunction with the height warning module.

[0215] As used herein, the term "travel route" refers to the path or route that a vehicle travels or is to travel to reach a destination point. A travel route may have restrictive obstacles along its path that may cause obstacles to the vehicle.

[0216] As used herein, the term "height restriction information" refers to information about the height of a limiting obstacle. The height restriction information may include the height between the ground and the surface of the limiting obstacle, the clearance height between the vehicle (with or without a load) and the surface of the limiting obstacle.

[0217] As used herein, the term "width restriction information" refers to information about the width of a restricting obstacle. The width restriction information may include the width between the side of the vehicle and the side of the restricting obstacle, the clearance width between the vehicle (with or without a load) and the side of the restricting obstacle.

[0218] As used herein, the term "headroom" refers to the minimum clearance required between a vehicle (with or without a load) and the surface of a restraining obstacle. The minimum clearance is required to enable the vehicle (with or without a load) to pass through the restraining obstacle without collision or damage and scratches.

[0219] As used herein, the term "clearance width" refers to the minimum clearance required between a vehicle (with or without a load) and the side of a restraining obstacle. The minimum clearance is required to enable a vehicle (with or without a load) to pass through a restraining obstacle without collision or damage and scrapes.

[0220] As used herein, the term "object" refers to a load attached to a vehicle at the top or side of the vehicle. In one embodiment, the load is attached to the top of the vehicle at the cargo rack (e.g., vertically). In another embodiment, the load is attached to the side of the vehicle at the cargo rack (e.g., horizontally).

[0221] As used herein, the term "external infrastructure" refers to any external object, building, bridge, frame, structure, tree, etc., that resides outside of the vehicle and limiting obstacles. The external infrastructure may be in view of the vehicle and / or limiting obstacles.

[0222] As used herein, the term "command" refers to an instruction to be followed. The instruction may be issued in an official manner.

[0223] As used herein, the term "natural language processing (NLP)" refers to machine learning techniques that give computers the ability to interpret, manipulate, and understand human language. Natural language processing is applicable to scenarios where content in written, pictorial representations, text, speech, or other forms is understood. NLP combines computational linguistics (a rule-based modeling of human language) with statistics, machine learning, and deep learning models. NLP drives computer programs to translate text from one language to another, respond to verbal commands, and quickly summarize large amounts of text - even in real time.

[0224] As used herein, the term "artificial intelligence (AI)" refers to the intelligence of perceiving, synthesizing, and inferring information exhibited by machines, rather than the intelligence exhibited by humans or other animals. Artificial intelligence combines reliable data sets and computer technology to solve problems by analyzing, interpreting, understanding patterns, learning, and making decisions accordingly. Artificial intelligence can be used to further train the system from previous data sets and dynamically update in decision making and providing output in subsequent learning iterations.

[0225] As used herein, the term "adjustable roof rack" refers to a roof rack (e.g., a cargo rack) attached to a vehicle that can be adjusted to raise or lower the overall height of the vehicle. In one embodiment, the adjustable roof rack is an automatically adjustable roof rack. The adjustable roof rack receives commands from a control module, a height warning module, and / or an artificial intelligence module, and automatically adjusts according to the commands. The adjustable roof rack can automatically adjust the height with or without a load. The adjustable roof rack can be mechanically operated. The adjustable roof rack can be electronically operated. The adjustable roof rack can be vacuum operated. The adjustable roof rack can be adjusted to a predetermined height at different predetermined levels. In one embodiment, the adjustable roof rack can be adjusted to a custom height between different predetermined levels by activating an electromagnetic spring. In another embodiment, the adjustable roof rack can be dynamically adjusted in real time.

[0226] As used herein, the term "alternative route" refers to one or more different routes leading to the same destination. The alternative route may provide less obstacles for the vehicle to pass and reach the destination with or without a load.

[0227] As used herein, the term "overall width" refers to the width of the vehicle with or without a load. The overall width refers to the sum of the width of the vehicle and the maximum width of one or more loads. For example, consider a vehicle with one or more loads. The width of the vehicle is 2.5 meters. The width of one load is 0.25 meters and the width of another load is 0.50 meters. The overall width of the vehicle is then 2.5 + 0.5 (maximum width in load) = 3 meters. The width takes into account both sides of the vehicle. As another example, consider a vehicle without a load. The width of the vehicle is 2.5 meters. The overall width of the vehicle is then 2.5 meters. The width of the vehicle includes any external protrusions (such as side mirrors) that extend out of the vehicle.

[0228] As used herein, the term "components" is broadly interpreted as hardware, firmware, and / or a combination of hardware, firmware, and software.

[0229] The embodiments described herein can be directed to one or more of the systems, methods, devices and / or computer program products of any possible level of integrated technical detail. The computer program product can include a computer-readable storage medium (or medium) having computer-readable program instructions thereon, for causing a processor to perform aspects of one or more embodiments described herein. The computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. For example, a computer-readable storage medium can be, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a superconducting storage device and / or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media can also include the following: a portable computer floppy disk (diskette), a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable optical disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk (floppydisk), a mechanical encoding device, such as a punch card or a protruding structure in a groove on which instructions are recorded, and / or any suitable combination of the foregoing. The computer-readable storage media used in this document is not to be construed as transient signals per se, such as radio waves and / or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides and / or other transmission media (e.g., light pulses through optical cables), and / or electrical signals transmitted through wires.

[0230] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a corresponding computing / processing device and / or to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical transmission optical fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives a computer-readable program instruction from the network, and forwards the computer-readable program instruction to be stored in a computer-readable storage medium in the corresponding computing / processing device. The computer-readable program instructions for performing the operation of one or more embodiments described herein can be assembly instructions, instruction set architecture (instruction-set-architecture, referred to as ISA) instructions, machine instructions, machine dependent instructions (machine dependent instructions), microcode, firmware instructions, state setting data (state-setting data), configuration data of an integrated circuit, and / or source code and / or object code written in any combination of one or more programming languages ​​(including object-oriented programming languages, such as Smalltalk, C++, etc., and / or process programming languages, such as "C" programming languages ​​and / or similar programming languages). The computer-readable program instructions can be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and / or partially on a remote computer or entirely on a remote computer and / or server. In the latter scenario, the remote computer can be connected to the computer via any type of network, including a local area network (LAN) and / or a wide area network (WAN), and / or can be connected to an external computer (e.g., via the Internet using an Internet service provider). In one or more embodiments, electronic circuits including, for example, programmable logic circuits, field programmable gate arrays (FPGAs) and / or programmable logic arrays (PLAs) can run computer-readable program instructions to personalize the electronic circuits by utilizing the state information of the computer-readable program instructions, so as to perform aspects of one or more embodiments described herein.

[0231] Aspects of one or more embodiments described herein are described with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to one or more embodiments described herein. Each block of the flowchart and / or block diagram and the combination of the blocks in the flowchart and / or block diagram can be realized by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer and / or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device can create a device (or module, means) for realizing the function / action specified in the flowchart and / or block diagram block. These computer-readable program instructions can also be stored in a computer-readable storage medium, which can guide a computer, a programmable data processing device and / or other devices to work in a specific manner, so that a computer-readable storage medium having instructions stored therein can include a product, which includes instructions that can realize various aspects of the function / action specified in the flowchart and / or block diagram block. Computer-readable program instructions can also be loaded onto a computer, other programmable data processing devices and / or other devices to cause a series of operational actions to be performed on the computer, other programmable devices and / or other devices, thereby producing a computer-implemented process, so that the instructions executed on the computer, other programmable devices and / or other devices implement the functions / actions specified in the flowchart and / or block diagram blocks.

[0232] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and / or operations of the system, computer-implemented method and / or computer program product according to one or more embodiments described herein. In this regard, each block in the flowchart or block diagram can represent a module, segment and / or part of an instruction, which includes one or more executable instructions for implementing a specified logical function. In one or more alternative implementations, the functions recorded in the block can appear in a sequence not recorded in the figure. For example, depending on the functions involved, two blocks shown in succession can be executed substantially simultaneously, and / or these blocks can sometimes be executed in reverse order. It will also be noted that each block in the block diagram and / or flowchart, and / or the combination of blocks in the block diagram and / or flowchart, can be implemented by a hardware-based dedicated system that can perform specified functions and / or actions and / or perform one or more combinations of dedicated hardware and / or computer instructions.

[0233] Although the subject matter described herein is in the general context of computer executable instructions of a computer program product running on one and / or multiple computers, those skilled in the art will recognize that one or more embodiments herein can also be implemented in conjunction with one or more other program modules. Program modules include routines, programs, components, data structures, etc. that perform specific tasks and / or implement specific abstract data types. In addition, other computer system configurations, including single-processor and / or multi-processor computer systems, microcomputing devices, mainframe computers, and computers, handheld computing devices (e.g., PDAs, phones), microprocessor-based or programmable consumer and / or industrial electronic devices, and / or similar devices, can practice the computer-implemented methods described herein. In a distributed computing environment, remote processing devices linked by a communication network perform tasks and can also practice the aspects shown. However, a stand-alone computer can practice one or more aspects of one or more embodiments described herein, if not all aspects. In a distributed computing environment, program modules can be located in local and remote memory storage devices.

[0234] As used in this application, the term "component", "system", "platform", "interface" and / or the like can refer to and / or can include an entity associated with a computer or an entity associated with an operating machine having one or more specific functions. The entity described herein can be hardware, a combination of hardware and software, software or software in execution. For example, a component can be, but is not limited to, a process, a processor, an object, an executable file, an execution thread, a program and / or a computer running on a processor. For example, both the application program and the server running on the server can be components. One or more components can reside in the process and / or thread of execution, and the component can be localized on a computer and / or distributed between two or more computers. In another example, each component can be operated by various computer-readable media having various data structures stored thereon. These components can communicate via local and / or remote processes, for example, according to a signal with one or more data packets (for example, data from a component interacting with another component of a local system, a distributed system via a signal and / or interacting with other systems across a network (such as the Internet)). As another example, a component can be a device having a specific function provided by a mechanical component operated by an electrical or electronic circuit, which is operated by a software and / or firmware application executed by a processor. In this case, the processor can be located inside and / or outside the device and can execute at least a portion of the software and / or firmware application. As yet another example, a component can be a device that provides a specific function without a mechanical component by an electronic component, wherein the electronic component can include a processor and / or other device to execute at least part of the software and / or firmware that gives the electronic component its function. In one aspect, the component can simulate the electronic component via a virtual machine, for example, within a cloud computing system.

[0235] As used in this subject specification, the term "processor" can refer to any computational processing unit and / or device, including but not limited to: a single-core processor; a single processor with software multi-threaded execution capability; a multi-core processor; a multi-core processor with software multi-threaded execution capability; a multi-core processor using hardware multi-threading technology; a parallel platform; and / or a parallel platform with distributed shared memory. In addition, a processor can refer to an integrated circuit, an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic controller (PLC), a complex programmable logic device (CPLD), discrete gate or transistor logic, discrete hardware components, and / or any combination thereof designed to perform the functions described herein. In addition, a processor can utilize nanoscale architectures, such as but not limited to molecular-based transistors, switches, and / or gates, in order to optimize space usage and / or enhance the performance of associated devices. A combination of computational processing units can implement a processor.

[0236] As used herein, terms such as "storage," "storage," "data storage," "data storage," "database," and any other information storage component related to the operation and functionality of a component refer to a "memory component," an entity contained in a "memory," or a component that includes a memory. The memory and / or memory components described herein can be volatile memory or nonvolatile memory, or can include volatile memory and nonvolatile memory. By way of illustration and not limitation, nonvolatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), flash memory, and / or nonvolatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM)). Volatile memory can include RAM, which can, for example, be used as an external cache memory. By way of illustration and not limitation, RAM can have a variety of forms, such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and / or Rambus dynamic RAM (RDRAM). In addition, the memory components of the systems and / or computer-implemented methods described herein include, but are not limited to, including these and / or any other suitable types of memory.

[0237] The embodiments described herein include only examples of systems and computer-implemented methods. Of course, it is not possible to describe every conceivable combination of components and / or computer-implemented methods for purposes of describing one or more embodiments, but one of ordinary skill in the art will recognize that many further combinations and / or permutations of one or more embodiments are possible. In addition, where the terms "including," "having," "containing," and the like are used in the detailed description, claims, appendices, and / or drawings, these terms are intended to be inclusive in a manner similar to the term "comprising," as interpreted when "including" is used as a transitional word in a claim.

[0238] The description of one or more embodiments is for illustrative purposes, but is not exhaustive or limited to the embodiments described herein. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein best explain the principles of the embodiments, practical applications, and / or technical improvements over technologies found on the market, and / or enable others of ordinary skill in the art to understand the embodiments described herein.

[0239] In one aspect, a system is described. Figure 1 A system according to one or more embodiments is shown. The system includes a height warning module 102. The system also includes a width warning module 104. The height warning module 102 is configured to determine the total height of the vehicle and calculate whether the vehicle safely passes through a restricted obstacle. The width warning module 104 is configured to determine the total width of the vehicle and calculate whether the vehicle safely passes through a restricted obstacle. The height warning module 102 and the width warning module 104 help the vehicle and / or the driver of the vehicle to safely pass through when approaching a restricted obstacle.

[0240] The height warning module 102 is configured to: detect one or more objects attached to the vehicle; determine the total height of the vehicle; obtain a first driving route for the vehicle to reach a destination point; extract first height limit information of one or more first limiting obstacles located along the first driving route; determine a first clearance height based on the total height of the vehicle and the first height limit information of the one or more first limiting obstacles; and when the first clearance height is greater than a threshold clearance, calculate a first probability that the vehicle and the one or more objects safely pass through the one or more first limiting obstacles as true. The total height of the vehicle includes the first height of the vehicle and the second height of the one or more objects. The second height of the one or more objects may include a maximum height among the one or more objects.

[0241] In another embodiment, the system includes a width warning module 104 that cooperates with the height warning module. The width warning module 104 is configured to: detect one or more objects attached to the vehicle; determine the total width of the vehicle; obtain a first driving route for the vehicle to reach a destination; extract first width restriction information of one or more first limiting obstacles located along the first driving route; determine a first clearance width based on the total width of the vehicle and the first width restriction information of one or more first limiting obstacles; and when the first clearance width is greater than the threshold clearance width, calculate the second probability that the vehicle passes through the one or more first limiting obstacles safely as true. The total width of the vehicle includes the first width of the vehicle and the second width of the one or more objects. The width warning module 104 can transmit a command to the electric drive unit of the vehicle through the communication module when the second probability that the vehicle passes through the one or more first limiting obstacles safely together with the one or more objects is calculated to be false. In one embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0242] In another embodiment, the system includes an artificial intelligence module 106. The artificial intelligence module 106 is pre-trained using a first data set including one or more traffic signs, one or more messages, one or more instructions, one or more texts, one or more images, and one or more videos to recognize, interpret, and understand one or more contexts. In another embodiment, the artificial intelligence module 106 understands one or more contexts and transmits commands to the electric drive unit. In another embodiment, the artificial intelligence module 106 is trained using a second data set to learn, improve, and understand one or more contexts in an optimized manner. The command instructs at least one of the electric drive unit and the control module to perform a predetermined action when reaching one or more first limiting obstacles. In another embodiment, the predetermined action includes at least one of the following: applying automatic braking, passing one or more first limiting obstacles, stopping before one or more first limiting obstacles, taking a second driving route, and adjusting the roof rack.

[0243] In another embodiment, the system further comprises a communication module 108. The communication module 108 is configured to establish wireless communication with at least one of the vehicle, one or more first limiting obstacles, external infrastructure, and one or more nearby vehicles. The system transmits a command to an electric drive unit of the vehicle via the communication module. In one embodiment, the system transmits a command when a first probability that the vehicle safely passes the one or more first limiting obstacles together with the one or more objects is calculated to be false. In one embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0244] In another embodiment, the system includes one or more sensors 112. The one or more sensors 112 include laser sensors, range finders, distance sensors, cameras, photoelectric sensors, measurement sensors, and ultrasonic sensors. In one embodiment, the camera captures at least one of an image and a video of the vehicle that can hold one or more objects attached to the vehicle. The one or more sensors 112 can be configured to determine the distance between the vehicle and one or more first limiting obstacles. In another embodiment, the one or more sensors are configured to determine the total height of the vehicle. In another embodiment, the one or more sensors 112 are configured to determine the distance between the vehicle and one or more nearby vehicles. In another embodiment, the one or more sensors 112 are configured to determine the distance between the vehicle and external infrastructure. The system also includes a database 110 that stores data for future use. The database 110 stores data sets for training the artificial intelligence module 106.

[0245] In one embodiment, the system is part of one or more first limiting obstacles along a first travel route. In another embodiment, the system is part of a vehicle. In another embodiment, the system is part of one or more nearby vehicles. In another embodiment, the system is part of external infrastructure. In another embodiment, the system is portable and can be part of any structure in the field of view of the vehicle and limiting obstacles. In another embodiment, the system communicates with the vehicle. In another embodiment, the system communicates with one or more nearby vehicles.

[0246] Figure 2 Components of a vehicle according to one or more embodiments are shown. The vehicle includes a control module 202, an electric drive unit 204, an automatic braking unit 206, and an artificial intelligence module 208. The control module 202 includes a natural language processing module. The control module 202 provides commands to the electric drive unit. The electric drive unit 204 also receives commands directly from the artificial intelligence module 208. In one embodiment, the electric drive unit 204 receives commands from the control module 202 via the artificial intelligence module 208. Then, in the case of an autonomous vehicle, the electric drive unit 204 automatically operates the vehicle according to the received commands. In one embodiment, in the case of a manually driven vehicle, the electric drive unit 204 then provides assistance to the driver via commands to operate the vehicle. The commands to the driver can be provided in the form of audio, text, video, picture representation (e.g., navigation map). The driver can follow the instructions for the vehicle to pass safely.

[0247] A system including a height warning module and a width warning module can be part of the restricted obstacle. In this case, the system can provide instructions / commands in the form of at least one of audio, video, text and picture formats via a display and / or a speaker when the vehicle approaches the restricted obstacle. The artificial intelligence module 208 in the vehicle is configured to understand the instructions and provide commands to the electric drive unit. The artificial intelligence module 208 is pre-trained with a robust (robust, also known as a robust) data set to understand, learn and make decisions so as to provide commands to the electric drive unit in real time. The artificial intelligence module 208 is trained with subsequent data sets to further improve the understanding, learning and rapid decision-making in real time relative to the scene. The data set includes one or more traffic signs, one or more messages, one or more instructions, one or more texts, one or more images and one or more videos. The data set can also include predefined actions taken on situations and scenes.

[0248] The natural language processing module analyzes the instructions / commands and understands one or more scenarios associated with the instructions / commands or suggestions provided. The natural language processing module identifies, interprets and analyzes one or more scenarios of at least one of a message, audio, instructions, traffic signs, text and images through artificial intelligence provided by a system associated with a restrictive obstacle. The natural language processing module provides commands to the electric drive unit when the one or more scenarios are understood. The electric drive unit 204 then takes a predetermined action. The predetermined action includes applying automatic braking, passing one or more first restrictive obstacles, stopping before one or more first restrictive obstacles, taking a second driving route, and adjusting the roof rack.

[0249] The vehicle also includes an infotainment unit. The control module 202 provides a user interface via the infotainment unit 212, through which the system receives the total height of the vehicle from the user as input. The control module 202 transmits the total height to the height warning module and the width warning module. In one embodiment, the user can provide input as a vehicle type and model and a load type and model. The control module 202 retrieves the actual height of the vehicle based on the specifications of the vehicle (from a third party database, such as a vehicle database). In another embodiment, the control module 202 retrieves the actual height of the load based on the specifications of the load (from a third party database). Then, the control module 202 determines the total height of the vehicle.

[0250] The vehicle also includes an adjustable roof rack 214 that holds one or more objects (e.g., a load). In one embodiment, the vehicle includes a control module 202 that instructs the adjustable roof rack 214 to dynamically adjust so as to reduce the overall height of the vehicle. In another embodiment, the adjustable roof rack 214 is configured to adjust to one of a first level, a second level, and a third level. The first level includes a first predetermined height. The second level includes a second predetermined height. The third level includes a third predetermined height. In another embodiment, the adjustable roof rack 214 is configured to adjust to a custom height to adjust the overall height of the vehicle.

[0251] The adjustable roof rack 214 is attached to the vehicle. The adjustable roof rack 214 can be manually adjusted to raise or lower the overall height of the vehicle. In one embodiment, the adjustable roof rack 214 is an automatically adjustable roof rack 214. The adjustable roof rack 214 receives commands from the control module 202, the height warning module and / or the artificial intelligence module and automatically adjusts according to the commands. The adjustable roof rack 214 can automatically adjust the height with or without a load. The adjustable roof rack 214 can be mechanically operated. The adjustable roof rack 214 can be electronically operated. The adjustable roof rack 214 can be vacuum operated. The adjustable roof rack 214 can be adjusted to a predetermined height at different predetermined levels. In one embodiment, the adjustable roof rack 214 can be adjusted to a custom height between different predetermined levels by activating an electromagnetic spring. In another embodiment, the adjustable roof rack 214 can be dynamically adjusted in real time.

[0252] The adjustable roof rack 214 receives commands from the artificial intelligence module 208 and automatically adjusts according to the commands. The artificial intelligence module 208 is pre-trained using a first data set including vehicle information, vehicle specifications, predetermined height information of one or more objects, travel route information, height limit information of one or more first limiting obstacles, and height information of the adjustable roof rack. The artificial intelligence module 208 can be trained using a second data set to learn and improve. The artificial intelligence module 208 transmits a command to the adjustable roof rack via the control module. The command instructs the adjustable roof rack to automatically adjust to one of the first level, the second level, and the third level. The vehicle also includes a database 210 that stores data for future use. The database 210 internally stores data sets for training the artificial intelligence module 106 and the natural language processing module.

[0253] Figure 3A and Figure 3BA vehicle approaching a restricted obstacle according to one or more embodiments is shown. Vehicle 302 can be any model with a predetermined height. Vehicle 302 can be any type of vehicle, such as a car, a truck, a bus, a personal vehicle, a taxi, etc. Vehicle 302 can also be a self-driving vehicle or an autonomous vehicle. Vehicle 302 can also be a manually driven vehicle. Vehicle 302 approaching restricted obstacle 304 can carry one or more objects (e.g., loads) 306. One or more objects 306 can be one or more loads (e.g., bicycles, luggage, packages, cargo boxes, etc.). One or more objects 306 can be attached to the vehicle at the roof or roof rack (e.g., a cargo rack). The height of vehicle 302 includes the height of the roof rack (e.g., a cargo rack). In one embodiment, the cargo rack can be an adjustable luggage rack so that the height and width of the cargo rack can be adjusted. Vehicle 302 includes a control module that can automatically adjust the height of the cargo rack, which in turn adjusts the overall height of the vehicle from the ground. The overall height of the vehicle 302 is equal to the sum of the height of the vehicle 302 and the height of one or more objects carried by the vehicle 302. The limiting obstacle 304 may be, for example, an underpass, a bridge, a tree, a tunnel, a roof structure, a building, a parking area, and the like.

[0254] Vehicle 302 (e.g., autonomous vehicle) may not know the size of the attached load or object. Typically, the load is held on the roof rack by the vehicle. Since vehicle 302 (e.g., autonomous vehicle) is not aware of the fact of fixed load, there may be a possibility of collision on the restricted obstacle, resulting in damage to the vehicle and / or the object attached to the vehicle. Vehicle 302 includes a height warning module, which provides assistance so that the vehicle can safely pass through the restricted obstacle without collision. Vehicle 302 may also include a width warning module, which provides assistance so that the vehicle can safely pass through the restricted obstacle without collision. The height warning module works in conjunction with the width warning module. In one embodiment, the width warning module works in conjunction with the height warning module. The height warning module and the width warning module monitor the height and width of the vehicle 302 and the load, and compare the data with the size of the restricted obstacle to estimate the clearance gap (e.g., clearance width and clearance height). The height warning module calculates the probability of the vehicle safely passing through the restricted obstacle. Similarly, the width warning module calculates the probability of the vehicle safely passing through the restricted obstacle. In one embodiment, the system including the height warning module and the width warning module as a whole determines the probability of the vehicle safely passing the restricted obstacle 304 in the height direction and the width direction. Then, the system transmits a command or a warning or a warning to the vehicle.

[0255] In one embodiment, the system is part of one or more restriction barriers 304 (e.g. Figure 3A). One or more restrictive obstacles 304 include a display 307 located within a system 308 that displays a message to the vehicle. The message may include a traffic sign. In another embodiment, the vehicle 302 includes a control module. The control module includes a natural language processing module that is configured to recognize, interpret and understand at least one of a message, audio, instruction, traffic sign, text, and image. In one embodiment, the natural language processing module is configured to recognize, interpret and understand one or more scenarios of at least one of the message, audio, instruction, traffic sign, text, and image through an artificial intelligence module. In another embodiment, the control module transmits a command to the electric drive unit based on one or more scenarios. The command instructs the electric drive unit to take a predetermined action. The predetermined action includes applying automatic braking, passing one or more first restrictive obstacles, stopping before one or more first restrictive obstacles, taking a second driving route, and adjusting at least one of the roof rack.

[0256] In one embodiment, system 308 is part of external infrastructure 310 (e.g. Figure 3B 308 is shown). System 308 operates in the same manner as described above. System 308 includes display 307 as part of external infrastructure 310. In another embodiment, system 308 is part of a vehicle (not shown). The infotainment unit displays messages, alerts, commands, warnings and / or any instructions to the vehicle. In one embodiment, the system transmits the instructions / commands directly to the control module or electric drive unit for direct automatic execution.

[0257] Figure 4 A system according to one or more embodiments is shown. The system includes a height warning module. The height warning module is configured to: detect one or more objects attached to the vehicle at step 402; determine the total height of the vehicle at step 404; obtain a first driving route for the vehicle to reach a destination at step 406; extract first height limit information of one or more first limiting obstacles located along the first driving route at step 408; determine a first clearance height based on the total height of the vehicle and the first height limit information of one or more first limiting obstacles at step 410; calculate a first probability that the vehicle and the one or more objects safely pass through the one or more first limiting obstacles as true at step 412, and transmit a maneuvering command to an electric drive unit to maneuver the vehicle; and transmit a signal to a control module to dynamically adjust an adjustable roof rack to change the total height of the vehicle at step 414 when the first probability is calculated to be false. When the first clearance height is less than the threshold clearance height, the first probability is calculated to be false.

[0258] The total height of the vehicle includes the first height of the vehicle and the second height of the one or more objects. The second height of the one or more objects may include the maximum height of the one or more objects.

[0259] The height warning module transmits a command to the electric drive unit based on the calculated probability. The command may include a predefined action to be performed by the vehicle. In one embodiment, the height warning module may instruct the vehicle to stop before a restrictive obstacle. In one embodiment, the height warning module may instruct the vehicle to pass through a restrictive obstacle. In one embodiment, the height warning module may instruct the vehicle to adjust the adjustable roof rack to lower the height to a predetermined / customized height and pass through the restrictive obstacle. In one embodiment, the height warning module may instruct the vehicle to take a different route to reach the destination point without any collisions. The height warning module may project the different routes onto the dashboard of the vehicle.

[0260] In certain embodiments, the system for calculating the route of a vehicle includes a routing module, which includes computer hardware. The routing module is capable of receiving an indication of a starting node and an ending node of a route that the vehicle is to travel. The routing module can use a first routing network to route (or plan) a first route from a starting node toward an ending node until a first groove node is identified. The first groove node can be a point where a limiting obstacle is located and the vehicle cannot pass due to a height restriction. In some cases, the first groove node is not an ending node. The routing module is also capable of routing (or planning) an alternative route to the ending node. The routing module can check for limiting obstacles within an alternative route and determine whether a vehicle with a total height can pass. In addition, the routing module is capable of using a second routing network to identify a groove route from a first groove node to a second groove node to generate an initial route including a first route, a groove route, and a second route. The second routing network can include a subset of nodes of the first routing network. In addition, the routing module can refine the initial route using the first routing network to generate an output route by evaluating the trench route based at least in part on the distance from the trench route and the one or more routing factors to identify an alternative route to at least a portion of the trench route. In one embodiment, the routing module considers fuel availability of the vehicle and suggests an alternative route. The routing module suggests a shorter route of the one or more alternative routes based on the fuel availability.

[0261] In some embodiments, a routing module for calculating a route can include a street classification module that includes computer hardware. The street classification module can assign values ​​to streets of a street network in a geographic area in order to effectively determine how to route a vehicle. These values ​​can indicate the location of the limiting obstacle and its limiting information (e.g., height, width, etc.). The street classification module can also store the assigned values ​​in a computer database. The system can also include a route calculation module that can use the assigned values ​​stored in the computer database to calculate a first route on a street network in a geographic area for a vehicle to penalize or favor certain directions of travel rather than other directions of travel at an intersection. The route calculation module can also output the first route to a navigation device associated with the first vehicle to present it to the driver of the first vehicle.

[0262] In one embodiment, the routing module determines the availability of fuel and communicates with the control module of the vehicle when there is insufficient fuel for the vehicle to take an alternate route. The control module provides a warning regarding the availability of fuel. In one embodiment, the control module transmits a suggestion to the driver via the instrument panel to reduce the air volume in the tires to a predetermined volume (e.g., 25 psi) of the vehicle to reduce the overall height of the vehicle. In one embodiment, the control module transmits a suggestion to the driver via the instrument panel to separate the load at the roof from the vehicle to reduce the overall height of the vehicle and proceed to the destination point without collision.

[0263] In another aspect, a method is described. Figure 5A method according to one or more embodiments is shown. The method includes the following technical steps: In step 502, the height warning module detects one or more objects attached to the vehicle. Then, in step 504, the height warning module determines the total height of the vehicle. The total height of the vehicle includes a first height of the vehicle and a second height of one or more objects. Then, in step 506, the height warning module obtains a first driving route for the vehicle to reach the destination. Then, in step 508, the height warning module extracts the first height limit information of one or more first limiting obstacles located along the first driving route. Then, in step 510, the height warning module determines the first clearance height based on the total height of the vehicle and the first height limit information of one or more first limiting obstacles. Then, in step 512, when the first clearance height is greater than the threshold clearance, the height warning module calculates the first probability that the vehicle passes through the one or more first limiting obstacles safely with the one or more objects as true, and transmits the maneuvering command to the electric drive unit to maneuver the vehicle. The second height of the one or more objects includes the maximum height among the one or more objects. Then, in step 514, the height warning module transmits a signal to the control module when the first probability calculation is false to dynamically adjust the adjustable roof rack to change the total height of the vehicle. When the first headroom height is less than the threshold headroom height, a first probability is calculated as false.

[0264] In another embodiment, the method further includes the following technical steps performed by the height warning module. The height warning module calculates one or more second driving routes for the vehicle to reach the destination point. The height warning module calculates one or more second driving routes for the vehicle to reach the destination point including the following technical steps. The height warning module identifies the current position of the vehicle. The height warning module obtains the destination point of the vehicle. The height warning module determines one or more third driving routes leading to the destination point based on the current position and the destination point. Then, the height warning module extracts the second height limit information of one or more second limiting obstacles located along the one or more third driving routes. Then, the height warning module determines the second clearance height based on the total height of the vehicle and the second height limit information of the one or more second limiting obstacles. Then, when the second clearance height is greater than the threshold clearance, the height warning module calculates the second probability that the vehicle safely passes through the one or more second limiting obstacles together with the one or more objects as true. Then, the height warning module calculates one or more second driving routes in the one or more third driving routes for the vehicle to reach the destination point, wherein, for the one or more second driving routes, the second probability is calculated as true.

[0265] In another embodiment, the altitude warning module transmits a command to an electric drive unit of the vehicle through the communication module when the first probability of safe passage of the vehicle is calculated to be false. The command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles. The system establishes wireless communication with at least one of the vehicle, the one or more first limiting obstacles, the external infrastructure, and the one or more nearby vehicles through the communication module.

[0266] In another embodiment, the method further comprises the following steps performed by an NLP module. The NLP module recognizes, interprets and analyzes one or more contexts of at least one of a message, audio, instructions, traffic signs, text and images through artificial intelligence provided to the vehicle. The NLP module transmits the command to the control module and / or the electric drive unit.

[0267] In another embodiment, the method further includes the following steps performed by the AI ​​module. The AI ​​module is pre-trained using a first data set including one or more traffic signs, one or more messages, one or more instructions, one or more texts, one or more images, and one or more videos to recognize, interpret, and understand one or more scenarios. The AI ​​module is then further trained using a second data set to learn, improve, and understand the one or more scenarios in an optimized manner. The AI ​​module then interprets and analyzes the one or more scenarios and transmits commands to the electric drive unit based on the analyzed scenarios.

[0268] In another embodiment, the method further comprises the following steps performed by a control module. The control module dynamically adjusts the adjustable roof rack to reduce the overall height of the vehicle. In another embodiment, the control module dynamically adjusts the adjustable roof rack to one of the first level, the second level, and the third level. In another embodiment, the control module dynamically adjusts the adjustable roof rack to one of the first level, the second level, and the third level based on a command received from the artificial intelligence module.

[0269] In another embodiment, the method further includes the following steps performed by a width warning module. The width warning module detects one or more objects attached to the vehicle. The width warning module determines the total width of the vehicle. The total width of the vehicle includes a first width of the vehicle and a second width of the one or more objects. The width warning module obtains a first driving route for the vehicle to reach a destination. The width warning module extracts first width restriction information of one or more first limiting obstacles located along the first driving route. The width warning module determines a first clearance width based on the total width of the vehicle and the first width restriction information of the one or more first limiting obstacles. When the first clearance width is greater than the threshold clearance width, the width warning module calculates a second probability that the vehicle and the one or more objects safely pass through the one or more first limiting obstacles as true.

[0270] In one embodiment, when the second probability calculation that the vehicle, together with the one or more objects, safely passes through the one or more first limiting obstacles is false, the width warning module transmits a command to the electric drive unit of the vehicle through the communication module. In another embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0271]

[0011] In yet another aspect, a non-transitory storage medium storing sequences of instructions is described. Figure 6 A non-transitory storage medium according to one or more embodiments is shown. The non-transitory storage medium, when executed by a processor, causes: in step 602, detecting one or more objects attached to a vehicle; in step 604, determining a total height of the vehicle, wherein the total height of the vehicle includes a first height of the vehicle and a second height of one or more objects; in step 606, obtaining a first driving route for the vehicle to reach a destination point; in step 608, extracting first height restriction information of one or more first limiting obstacles located along the first driving route; in step 610, determining a first clearance height based on the total height of the vehicle and the first height restriction information of one or more first limiting obstacles; in step 612, when the first clearance height is greater than a threshold clearance, calculating a first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true, and transmitting a maneuvering command to an electric drive unit to maneuver the vehicle; and in step 614, when the first probability is calculated to be false, transmitting a signal to a control module to dynamically adjust the adjustable roof rack to change the total height of the vehicle. When the first clearance height is less than the threshold clearance height, the first probability is calculated to be false.

[0272] The non-transitory storage medium also enables: calculating one or more second driving routes for the vehicle to reach the destination. In one embodiment, the non-transitory storage medium calculates one or more second driving routes for the vehicle to reach the destination so as to: identify the current position of the vehicle; obtain the destination of the vehicle; determine one or more third driving routes leading to the destination based on the current position and the destination; extract the second height limit information of one or more second limiting obstacles located along the one or more third driving routes; determine the second clearance height based on the total height of the vehicle and the second height limit information of the one or more second limiting obstacles; and when the second clearance height is greater than the threshold clearance, calculate the second probability that the vehicle and the one or more objects safely pass through the one or more second limiting obstacles as true; and calculate the one or more second driving routes in the one or more third driving routes so that the vehicle reaches the destination, wherein the second probability is calculated as true for the one or more second driving routes.

[0273] In another embodiment, the non-transitory storage medium further enables: when the first probability calculation that the vehicle and the one or more objects safely pass through the one or more first limiting obstacles is false, a command is transmitted to the electric drive unit of the vehicle through the communication module.

[0274] In another embodiment, the command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before one or more first limiting obstacles.

[0275] In another embodiment, the non-transitory storage medium further causes: establishing, by the communication module, wireless communication with at least one of the vehicle, the one or more first limiting obstacles, external infrastructure, and one or more nearby vehicles.

[0276] In another embodiment, the non-transitory storage medium further enables: recognizing, interpreting and analyzing, by a natural language processing (NLP) module through artificial intelligence, one or more contexts of at least one of a message, audio, instruction, traffic sign, text and image.

[0277] In another embodiment, the non-transitory storage medium further enables: pre-training an artificial intelligence module using a first data set comprising one or more traffic signs, one or more messages, one or more instructions, one or more texts, one or more images, and one or more videos to recognize, interpret, and understand one or more scenarios.

[0278] In another embodiment, the non-transitory storage medium further causes: using the second data set to train the artificial intelligence module to learn, improve, and understand one or more scenarios in an optimized manner.

[0279] In another embodiment, the non-transitory storage medium further causes: interpreting and analyzing the one or more scenarios by an artificial intelligence module, and transmitting commands to the electric drive unit based on the analyzed scenarios.

[0280] In another embodiment, the non-transitory storage medium further causes: dynamically adjusting the adjustable roof rack to lower the overall height of the vehicle.

[0281] In another embodiment, the non-transitory storage medium further causes: dynamically adjusting the adjustable roof rack to one of the first level, the second level, and the third level.

[0282] In another embodiment, the non-transitory storage medium further causes: dynamically adjusting the adjustable roof rack to one of the first level, the second level, and the third level based on the command received from the artificial intelligence module.

[0283] In another embodiment, the non-transitory storage medium also enables: detecting one or more objects attached to the vehicle; determining the total width of the vehicle, wherein the total width of the vehicle includes a first width of the vehicle and a second width of the one or more objects; obtaining the first driving route for the vehicle to reach the destination point; extracting first width limitation information of the one or more first limiting obstacles located along the first driving route; determining a first clearance width based on the total width of the vehicle and the first width limitation information of the one or more first limiting obstacles; and when the first clearance width is greater than a threshold clearance width, calculating a second probability that the vehicle together with the one or more objects safely passes through one or more first limiting obstacles as true.

[0284] In another embodiment, the non-transitory storage medium is further configured to: when the second probability that the vehicle and the one or more objects safely pass through the one or more first limiting obstacles is calculated to be false, transmit a command to the electric drive unit of the vehicle through the communication module. The command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance before the one or more first limiting obstacles.

[0285] Figure 7 A flow chart showing determining the total height of a vehicle including an overhead load and providing assistance to the vehicle according to one or more embodiments is shown. In step 702, the system is placed as part of an external infrastructure to determine the total height of the vehicle including the load using sensors. In step 704, the system is placed as part of a nearby vehicle to determine the total height of the target vehicle including the load using sensors. In step 706, the total height of the target vehicle is determined. In step 708, the external infrastructure may include a warning system to provide a warning when the target vehicle approaches a restricted obstacle. The warning system is configured to use video analysis to identify the identity of the vehicle and provide a warning by scanning the vehicle's license plate or number plate or identity tag. In step 710, a control module in the vehicle receives the total height of the vehicle. In step 712, the vehicle records and stores the total height of the vehicle for future use. The artificial intelligence module can learn using the stored data set and the corresponding actions taken by the vehicle. In step 714, the control module analyzes the total height of the vehicle and the allowable height allowed by the restricted obstacle, and can calculate the threshold clearance to calculate the probability of safe passage. The control module then issues a warning or alert based on the analysis and calculation. In one embodiment, the control module instructs the electric drive unit to apply automatic braking via the automatic braking unit.

[0286] Figure 8Vehicle-to-vehicle data transfer according to one or more embodiments is shown. In one embodiment, the system is part of a nearby vehicle and is configured to detect the overall height of a target vehicle. The system residing in a nearby vehicle includes a sensor for determining the overall height of the vehicle. In one embodiment, the sensor may reside outside the system in one or more external infrastructures. The system determines the probability of the vehicle safely passing a limiting obstacle when calculating the overall height of the vehicle before reaching the limiting obstacle. The system determines the probability of safe passage in terms of height and width. The system then transmits commands to surrounding or nearby vehicles via vehicle-to-vehicle (V2V) data transfer.

[0287] Nearby vehicles travelling in the same direction towards the limiting obstacle are informed about the probability of safe passage for a predetermined height. The system in the respective vehicle then performs a probability calculation of its own height (including the height of the load attached to the respective vehicle). The control module in the respective vehicle then transmits appropriate commands to the electric drive unit to take appropriate actions (such as one of passing, stopping before the limiting obstacle, adjusting the roof rack, etc.).

[0288] Fig. 9A Determination of the overall height of a vehicle according to one or more embodiments is shown. The system is part of a restraining barrier. The system includes a sensor secured to the restraining barrier. The sensor determines the overall height of the vehicle, including a load attached to the vehicle. "H" refers to the overall height of the vehicle. H is equal to the sum of the vehicle height and the load height. A system for determining the overall height has been described.

[0289] The sensor transmits the total height of the vehicle to the system. The system knows the height of the limiting obstacle and the permitted height to pass through the limiting obstacle. For example, in case of a railway crossing with overhead wires, the permitted height is strictly maintained and followed as it may provide inductance and deliver shock to the vehicle regardless of the available clearance height.

[0290] The system then identifies the identity of the vehicle approaching the restrictive obstacle. Upon identifying the vehicle, if the overall height of the vehicle is greater than the permitted height, the system provides an external warning to the vehicle. The system also transmits commands / messages / instructions to at least one of the control module and the electric drive unit. The message may include a command to apply automatic braking, or to pass through the restrictive obstacle, or to stop before the restrictive obstacle, or to adjust the roof rack, or to take a different route to the destination point.

[0291] Fig. 9BDetermination of the distance between a vehicle and a limiting obstacle according to one or more embodiments is shown. A system is part of a limiting obstacle. The system includes a sensor fixed to the limiting obstacle. The sensor determines the distance between the vehicle and the limiting obstacle. "d" refers to the distance between the vehicle and the limiting obstacle. The sensor transmits the distance "d" to the system. The system knows the height of the limiting obstacle and the allowed threshold height for passing the limiting obstacle. For example, in case of a railway crossing with overhead wires, the allowed height is strictly maintained and followed as it may provide inductance and provide shock to the vehicle regardless of the available clearance height.

[0292] The system then identifies the identity of the vehicle approaching the limiting obstacle. Upon identifying the vehicle, the system provides an external warning to the vehicle when the distance "d" is reached. The system also transmits a command / message / instruction to at least one of the control module and the electric drive unit. The message may include a command to apply automatic braking, or to pass the limiting obstacle, or to stop before the limiting obstacle, or to adjust the roof rack, or to take a different route to the destination point. The distance "d" is sufficient for the vehicle (either a manually driven vehicle or a self-driving vehicle) to take a predefined safe passage action.

[0293] As an example, Fig. 10A , Fig. 10B and Fig. 10C Messages received by a target vehicle are shown according to one or more embodiments. The target vehicle receives a sample message from the system. Figures 10A-10C The sample message shown in includes fields such as Event Type, Vehicle ID, Probability, Pass, Stop, Possible Height Collision, Possible Width Collision, Roof Rack Adjustment, Alternate Route, and Target Speed.

[0294] The "Vehicle ID" field may include a serial identification number or a tag associated with the electric vehicle configured to identify and locate the electric vehicle. The "Event Type" field may be a safe passage through a restricted obstacle. The "Probability" field of safely passing a restricted load based on the current scenario is one of true or false. The field "Pass" indicates yes or no as appropriate. The field "Stop" indicates yes or no as appropriate. The "Possible Height Collision" field indicates yes or no as appropriate. The field "Possible Width Collision" indicates yes or no as appropriate. If the Roof Rack Adjustment indicates "Yes", the field Roof Adjustment Level may indicate the adjustment level (e.g., Level 1, Level 2, Level 3). "Speed" defines the speed of the vehicle when passing (e.g., 15mph).

[0295] In one embodiment, the system further comprises a network security module, wherein the network security module comprises an information security management module, which provides isolation between the communication module and the server.

[0296] In one embodiment, the information security management module is operable to receive data from the communication module, exchange security keys at the start of communication between the communication module and the server, receive the security key from the server, authenticate the identity of the server by verifying the security key, analyze the security key for potential network security threats, negotiate encryption keys between the communication module and the server, encrypt data, and send the encrypted data to the server when no network security threat is detected.

[0297] In one embodiment, the information security management module is operable to exchange security keys at the beginning of communication between the communication module and the server, receive the security keys from the server, authenticate the identity of the server by verifying the security keys, analyze the security keys for potential network security threats, negotiate encryption keys between the system and the server, receive encrypted data from the server, decrypt the encrypted data, perform an integrity check on the decrypted data, and send the decrypted data to the communication module when no network security threat is detected.

[0298] In one embodiment, the system may include a network security module. In one aspect, a secure communication management (SCM) computer device for providing a secure data connection is provided. The SCM computer device includes a processor in communication with a memory. The processor is programmed to receive a first data message from a first device. The first data message is in a standardized data format. The processor is also programmed to analyze the first data message for potential network security threats. If it is determined that the first data message does not contain a network security threat, the processor is also programmed to convert the first data message into a first data format associated with a vehicle environment, and send the converted first data message to the first data format associated with the vehicle environment, and send the converted first data message to the communication module using a first communication protocol associated with the negotiation protocol.

[0299] According to one embodiment, secure authentication for data transmission includes: supplying a hardware-based security engine (HSE) located in a network security module, the HSE having been manufactured in a secure environment and authenticated as part of an approved network in the secure environment; using the HSE to perform asynchronous authentication, verification and encryption of data, storing user permission data and connection status data in an access control list for defining an allowed data communication path of the approved network, enabling the network security module to communicate with the access control list using other computing system entities (e.g., a communication module), and using the security engine to perform asynchronous verification and encryption of data includes: using a hardware-based module equipped with one or more security aspects of protecting the system to identify a user device (UD) containing credentials in hardware, wherein the security aspects include the hardware-based module communicating with a user of the user device and the HSE.

[0300] Fig.11A A block diagram of a network security module according to one embodiment is shown. In one embodiment, Fig.11A A block diagram of a network security module is shown. Data communications between the system 1100 and the server 1170 via the communication module 1112 are first verified by the information security management module 1132 before being transmitted from the system to the server or from the server to the system. The information security management module is operable to analyze data for potential network security threats, encrypt data when no network security threats are detected, and transmit the encrypted data to the system or server. The system 1100 includes a processor 1108.

[0301] In one embodiment, the network security module further includes an information security management module that provides isolation between the system and the server. Fig. 11B A flow chart of protecting data by the network security module 1130 is shown. In step 1140, the information security management module is operable to receive data from the communication module. In step 1141, the information security management module exchanges security keys at the beginning of communication between the communication module and the server. In step 1142, the information security management module receives the security key from the server. In step 1143, the information security management module authenticates the identity of the server by verifying the security key. In step 1144, the information security management module analyzes the security key for potential network security threats. In step 1145, the information security management module negotiates an encryption key between the communication module and the server. In step 1146, the information security management module receives the encrypted data. In step 1147, when no network security threat is detected, the information security management module transmits the encrypted data to the server.

[0302] In one embodiment, Fig. 11CA flow chart for protecting data security through the network security module 1130 is shown. In step 1151, the information security management module is operable to: exchange security keys at the beginning of communication between the communication module and the server. In step 1152, the information security management module receives the security key from the server. In step 1153, the information security management module authenticates the identity of the server by verifying the security key. In step 1154, the information security management module analyzes the security key for potential network security threats. In step 1155, the information security management module negotiates an encryption key between the communication module and the server. In step 1156, the information security management module receives the encrypted data. In step 1157, the information security management module decrypts the encrypted data and performs an integrity check on the decrypted data. In step 1158, when no network security threat is detected, the information security management module transmits the decrypted data to the communication module.

[0303] In one embodiment, the integrity check is a hash signature verification using Secure Hash Algorithm 256 (SHA256) or a similar method. In one embodiment, the information security management module is configured to perform asynchronous authentication and verification of communications between the communication module and the server.

[0304] In one embodiment, the information security management module is configured to issue a warning if a network security threat is detected. In one embodiment, the information security management module is configured to discard the received encrypted data if the integrity check of the encrypted data fails.

[0305] In one embodiment, the information security management module is configured to verify the integrity of the decrypted data by verifying accuracy, consistency, and any possible data loss during communication through the communication module.

[0306] In one embodiment, the server is physically isolated from the system through an information security management module, such as Fig.11A When the system communicates with the server, as shown in Fig. 11BAs shown, the system and server are first authenticated. The system is responsible for communicating / exchanging the system's public key and the signature of the public key with the server. The system's public key and the signature of the public key are sent to the information security management module. The information security management module decrypts the signature and verifies whether the decrypted public key is consistent with the original public key received. If the decrypted public key is verified, the authentication is passed. Similarly, the system and server authenticate the information security management module. After the authentication is passed to the information security management module, the communicating parties, the system, and the server negotiate the encryption key and integrity verification key for the data communication between the communicating parties through the authenticated asymmetric key. A session ID number is transmitted during the authentication process, so that the key needs to be bound to the session ID number; when the system sends data to the outside, the information security gateway receives the data through the communication module, performs integrity authentication on the data, and then encrypts the data through the negotiated secret key, and finally transmits the data to the server through the communication module and the network security module. When the information security management module receives data through the communication module, as shown Fig. 11C As shown, the data is first decrypted, and the integrity of the decrypted data is verified. If the data passes the verification, the data is sent out through the communication module; otherwise, the data is discarded. In one embodiment, an asymmetric key with a signature is used to implement identity authentication.

[0307] In one embodiment, the signature is implemented by a pair of asymmetric keys trusted by the information security management module and the system, where the private key is used to sign the identities of the two communicating parties, and the public key is used to verify whether the identities of the two communicating parties are signed. The signing identity includes a public key and a private key pair. In other words, the signing identity is called the common name of the certificate installed in the user's machine.

[0308] In one embodiment, both communicating parties need to authenticate their own identities through a pair of asymmetric keys, and the task responsible for communicating with the information security management module of the system is marked by a unique pair of asymmetric keys.

[0309] In one embodiment, the dynamic negotiation key is encrypted by using the Rivest-Shamir-Adleman (RSA) encryption algorithm. RSA is a public key cryptographic system widely used for secure data transmission. The negotiated key includes a data encryption key and a data integrity check key.

[0310] In one embodiment, the data encryption method is a triple data encryption algorithm (3DES) encryption algorithm. The integrity check algorithm is a hash-based message authentication code (HMAC-MD5-128) algorithm. When the data is output, the data is integrity checked and calculated, and the calculated message authentication code (MAC) value is added to the header of the data message of the value, and then the 3DES algorithm is used to encrypt the data (including the MAC of the header), and the header information of the security layer is added after the data is encrypted, and then the data is sent to the next layer for processing. In one embodiment, the next layer refers to the transport layer in the Transmission Control Protocol / Internet Protocol (TCP / IP) model.

[0311] The information security management module ensures the security, reliability and confidentiality of the communication between the system and the server through identity authentication when the communication between the two parties begins data encryption and data integrity authentication. This method is particularly suitable for embedded platforms with fewer resources and not connected to the public key infrastructure (PKI) system, and by ensuring the security and reliability of the communication between the system and the server, it can ensure that the data security on the server will not be damaged by hacker attacks under Internet conditions.

[0312] In one embodiment of the system, the machine learning model is configured to learn using labeled data using a supervised learning method, wherein the supervised learning method includes logic using at least one of a decision tree, logistic regression, a support vector machine, k-nearest neighbors, naive Bayes, random forest, linear regression, polynomial regression, and a support vector machine for regression.

[0313] In one embodiment of the system, the machine learning model is configured to learn from real-time data using an unsupervised learning method, wherein the unsupervised learning method includes logic using at least one of k-means clustering, hierarchical clustering, a hidden Markov model, and an apriori algorithm.

[0314] In one embodiment of the system, the machine learning model has a feedback loop where the output from the previous step is fed back to the model in real time to improve the performance and accuracy of the output of the next step.

[0315] In one embodiment of the system, the machine learning model includes a recurrent neural network model.

[0316] In one embodiment of the system, the machine learning model has a feedback loop where learning is further reinforced by a reward for each true value output by the system.

[0317] Fig. 12AThe structure of a neural network / machine learning model with a feedback loop is shown. The artificial neural network (ANN) model includes an input layer, one or more hidden layers, and an output layer. Each node or artificial neuron is connected to another node and has an associated weight and threshold. If the output of any single node is above a specified threshold, the node is activated and the data is sent to the next layer of the network. Otherwise, no data is passed to the next layer of the network. A machine learning model or ANN model can be trained on a set of data to accept a request in the form of input data, make a prediction on the input data, and then provide a response. The model can learn from the data. Learning can be supervised learning and / or unsupervised learning, and can be based on different scenarios and use different data sets. Supervised learning includes the logic of using at least one of a decision tree, logistic regression, and a support vector machine. Unsupervised learning includes the logic of using at least one of a k-means clustering, a hierarchical clustering, a hidden Markov model, and an apriori algorithm. The output layer can predict or detect the probability of safe passage, the adjustment of the roof rack based on the input data set.

[0318] In one embodiment, the ANN may be a deep neural network (DNN), which is a multi-layer tandem neural network including an artificial neural network (ANN), a convolutional neural network (CNN), and a recurrent neural network (RNN), which is capable of identifying features from inputs, conducting expert reviews, and performing actions that require prediction, creative thinking, and analysis. In one embodiment, the ANN may be a recurrent neural network (RNN), which is a type of artificial neural network (ANN) that uses sequential data or time series data. Deep learning algorithms are often used for sequential or temporal problems, such as language translation, natural language processing (NLP), speech recognition, and image recognition. Like feedforward and convolutional neural networks (CNNs), recurrent neural networks use training data to learn. Their difference lies in their "memory" because they take information from previous inputs via feedback loops to affect current inputs and outputs. The output from the output layer in the neural network model is fed back to the model via feedback. When training the model, the weight changes in the hidden layer will be adjusted to better fit the expected output. This will allow the model to provide results with far fewer errors.

[0319] Neural networks are characterized by having feedback loops to dynamically adjust the system output as it learns from new data. In machine learning, backpropagation and feedback loops are used to train an AI model and continuously improve it as it is used. As more incoming data is received by the model, the model has more opportunities to learn from the data. The feedback loop or backpropagation algorithm identifies inconsistencies and feeds the corrected information back into the model as input.

[0320] Even if an AI / ML model is well trained using large sets of labeled data and concepts, after a while the performance of the model may degrade when new unlabeled inputs are added due to many reasons including but not limited to concept drift, recall-precision degradation due to distance from the true value, and data drift over time. The model’s feedback loop maintains the accuracy of the AI ​​results and ensures that the model maintains its performance and improves even as new unlabeled data is ingested. A feedback loop refers to the process by which the prediction output of an AI model is reused to train a new version of the model.

[0321] Initially, when training an AI / ML model, several labeled samples, including both positive and negative examples of concepts (e.g., safe passing probability), are used, which are intended for the model to learn. Afterwards, the model is tested using unlabeled data. By using, for example, deep learning and neural networks, the model is then able to predict whether the desired concept (e.g., safe passing probability to be detected) is in an unlabeled image. Each image is assigned a probability score, where a higher score represents a higher confidence in the model's prediction. When the model gives an image a high probability score, it is automatically labeled as the predicted concept. However, in the case where the model returns a low probability score, this input can be sent to a controller (which can be a human moderator) that verifies and, if necessary, corrects the result. A human moderator can only be used in special cases. The feedback loop dynamically feeds the labeled data, either automatically labeled or verified by the controller, back to the model and uses it as training data so that the system can improve its predictions in real time and dynamically.

[0322] Fig. 12B The structure of a neural network / machine learning model with reinforcement learning is shown. The network receives feedback from an authorized networked environment. While this system is similar to supervised learning, the feedback obtained in this case is evaluative rather than instructive, meaning there is no teacher as in supervised learning. After receiving the feedback, the network performs adjustments to the weights to obtain better predictions in the future. Machine learning techniques, such as deep learning, allow the model to take labeled training data and learn to recognize these concepts in subsequent data and images. The model can be fed new data for testing, so training is reinforced by feeding the model with data it has already predicted. If the machine learning model has a feedback loop, the learning is further reinforced with rewards for each true value output by the system. Feedback loops ensure that the AI ​​results do not stagnate. By incorporating feedback loops, the model outputs continue to dynamically improve with use / time.

[0323] Fig.13An adjustable roof rack according to one or more embodiments is shown. As shown in the figure: the adjustable roof rack includes two body side frames 132. Each body side frame 132 has two ends and has legs 1331, 1332 fixed in the roof 131. The two legs 1331, 1332 have an L-shaped cross section. The cross-sectional opening portions are arranged oppositely. One side wall of the legs 1331, 1332 is fixed by movable body side frames 1341, 1342 connected by hinges of hinges, respectively. The movable body side frames 1341, 1342 are hollow tube structures, and perforations 13411, 13412, 13421, 13422 are vertically arranged in two directions on the inside. The tops of the movable body side frames 1341, 1342 are respectively provided with flexible connection mechanisms. The adjustable roof rack has forward and rearward spacings 135, 136 on the roof 131. The forward and rearward intervals 135, 136 are the same as the intervals of the body side frames 132 having two legs 1331, 1332, and have through holes 1351, 1361 arranged oppositely on the forward and rearward intervals 135, 136. The through holes 13411, 13412, 13421, 13422, 1351, 1361 are consistent. Another arrangement is that the length of the telescopic tube link 137 is arranged in the through holes with the same spacing as the forward and rearward intervals 135, 136 of a certain length. The same length of the internal telescopic tube link 138 is arranged in the spaced holes between the two body side frames 132 of a certain length.

[0324] In one embodiment, each movable body side frame 1341, 1342 can be in a state perpendicular to the roof. The telescopic tube links 137, 138 are in a vertical position and are arranged on the movable body side frames 1341, 1342 in two directions using through holes 13411, 13412, 13421, 13422, so that a high fence structure can be formed.

[0325] In another embodiment, when the luggage rack is not in use, the telescopic tube links 137, 138 are arranged in the through holes 1351, 1361, 13411, 13421. The movable body side frames 1341, 1342 are rotated downward to return and connected with the flexible connection mechanism 13413, 13423 at the top thereof. In addition, the forward and rearward spaces 135, 136 can be higher than the legs 1331, 1332. When the movable body side frames 1341, 1342 just form a common luggage rack after returning, the roof rack can be rotated downward. The telescopic tube link 137 is arranged in the holes 1351, 1361. In one embodiment, the adjustable roof rack disclosed herein is automated.

[0326] Fig.13The adjustable roof rack shown includes an adjustable roof rack with two side frames, each of which is provided with support feet fixedly arranged on the top of the car at both ends, the support feet having an L-shaped cross section and arranged relatively at the opening of the cross section, one side wall of the support feet being hingedly connected to the movable side frame, the movable side frame being vertically provided with through holes in two inward directions, and the top of the movable side frame being respectively provided with elastic connection mechanisms; the top of the car is also provided with a front frame and a rear frame, the distance between the front frame and the rear frame is the same as the distance between the two support feet of the side frame, and the front frame and the rear frame are provided with through holes arranged relatively; in addition, a plurality of extendable connecting rods are arranged, wherein the extendable connecting rods have the same length as the distance between the front frame and the rear frame and can be arranged in the through holes. The adjustable roof frame solves the technical problem that the height of the support feet of the side frames of the luggage carrier at the top of the car cannot be adjusted, so it is not convenient to fix large luggage, and the height of the luggage carrier can be selected and prepared according to the required size.

[0327] The description of one or more embodiments is for illustrative purposes, but is not exhaustive or limited to the embodiments described herein. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein best explain the principles of the embodiments, practical applications, and / or technical improvements over technologies found on the market, and / or enable others of ordinary skill in the art to understand the embodiments described herein.

[0328] The embodiments described herein include only examples of systems and computer-implemented methods. Of course, for the purpose of describing one or more embodiments, it is not possible to describe every conceivable combination of components and / or computer-implemented methods, but one of ordinary skill in the art will recognize that many further combinations and / or permutations of one or more embodiments are possible. In addition, to the extent that the terms "including," "having," "having," and the like are used in the detailed description, claims, appendices, and / or drawings, such terms are intended to be inclusive in a manner similar to the term "comprising," as "comprising" is interpreted when "comprising" is used as a transitional word in a claim.

[0329] Without departing from the spirit or features of the present invention, other specific forms may embody the present invention. The described embodiments are illustrative and non-restrictive in all respects. Therefore, the appended claims rather than the description herein indicate the scope of the present invention. All changes falling within the meaning and scope of the equivalent of the claims are within their scope.

Claims

1. A system comprising: An altitude warning module, wherein the altitude warning module is configured to: detecting one or more objects attached to the vehicle; determining an overall height of the vehicle, wherein the overall height of the vehicle comprises a first height of the vehicle and a second height of the one or more objects; Obtaining a first driving route for the vehicle to reach a destination; extracting first height limit information of one or more first limiting obstacles located along the first driving route; determining a first clearance height based on the overall height of the vehicle and first height limit information of the one or more first limit obstacles; When the first clearance height is greater than a threshold clearance height, calculating a first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true, and transmitting a maneuvering instruction to an electric drive unit to maneuver the vehicle; and When the first probability is calculated as false, a signal is transmitted to a control module to dynamically adjust the adjustable roof rack to reduce the overall height of the vehicle, wherein the first probability is calculated as false when the first headroom height is less than the threshold headroom height.

2. The system of claim 1, wherein: The system includes one or more sensors, and the one or more sensors include a laser sensor, a rangefinder, a distance sensor, a camera, a photoelectric sensor, a measurement sensor, and an ultrasonic sensor.

3. The system of claim 1, wherein: When the first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles is calculated to be false, the system transmits a command to the electric drive unit of the vehicle through a communication module.

4. The system of claim 3, wherein: The command instructs the electric drive unit to apply automatic braking to stop at a predetermined distance in front of the one or more first limiting obstacles.

5. The system of claim 1, wherein: The vehicle includes the control module, which transmits commands to the electric drive unit.

6. The system of claim 5, wherein: The control module includes a natural language processing module configured to recognize, interpret and understand at least one of messages, audio, instructions, traffic signs, text and images.

7. The system of claim 1, wherein: The system includes an artificial intelligence module that is pre-trained using a first data set including one or more traffic signs, one or more messages, one or more instructions, one or more texts, one or more images, and one or more videos to recognize, interpret, and understand one or more scenarios.

8. The system of claim 7, wherein: The artificial intelligence module is trained using the second data set to learn, improve and understand the one or more scenarios in an optimized manner.

9. The system of claim 8, wherein: The artificial intelligence module understands the one or more scenarios and transmits a command instructing at least one of the electric drive unit and the control module to perform a predetermined action when the one or more first limiting obstacles are reached.

10. The system of claim 9, wherein: The predetermined action includes at least one of applying automatic braking, passing the one or more first limiting obstacles, stopping before the one or more first limiting obstacles, taking a second driving path, and adjusting the adjustable roof rack.

11. The system of claim 1, wherein: The vehicle includes the adjustable roof rack that holds the one or more objects, and the adjustable roof rack is dynamically adjusted to one of a first level, a second level, and a third level based on a command received from the control module.

12. The system of claim 1, wherein: The width warning module is configured to: detecting the one or more objects attached to the vehicle; determining an overall width of the vehicle, wherein the overall width of the vehicle comprises a first width of the vehicle and a second width of the one or more objects; Acquire the first driving route for the vehicle to arrive at the destination; extracting first width restriction information of the one or more first restriction obstacles located along the first driving route; determining a first clearance width based on the overall width of the vehicle and the first width limiting information of the one or more first limiting obstacles; and When the first clearance width is greater than a threshold clearance width, a second probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles is calculated as true.

13. The system of claim 12, wherein: When the second probability that the vehicle together with the one or more objects safely passes the one or more first limiting obstacles is calculated to be false, the width warning module transmits a command to the electric drive unit of the vehicle through the communication module.

14. A method comprising: detecting one or more objects attached to the vehicle; determining an overall height of the vehicle, wherein the overall height of the vehicle comprises a first height of the vehicle and a second height of the one or more objects; Obtaining a first driving route for the vehicle to reach a destination; extracting first height limit information of one or more first limiting obstacles located along the first driving route; determining a first clearance height based on the overall height of the vehicle and first height limit information of the one or more first limit obstacles; When the first clearance height is greater than a threshold clearance height, calculating a first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true, and transmitting a maneuvering instruction to an electric drive unit to maneuver the vehicle; and When the first probability is calculated as false, a signal is transmitted to a control module to dynamically adjust an adjustable roof rack to change the overall height of the vehicle, wherein the first probability is calculated as false when the first headroom height is less than the threshold headroom height.

15. The method according to claim 14, further comprising: One or more second driving routes for the vehicle to reach the destination are calculated.

16. The method according to claim 15, wherein calculating the one or more second driving routes for the vehicle to reach the destination point comprises: identifying a current location of the vehicle; Obtaining a destination point of the vehicle; determining one or more third travel routes leading to the destination point based on the current location and the destination point; extracting second height restriction information of one or more second restriction obstacles located along the one or more third driving routes; determining a second clearance height based on the overall height of the vehicle and second height limit information of the one or more second limit obstacles; and When the second clearance height is greater than the threshold clearance height, calculating a second probability that the vehicle together with the one or more objects safely passes through the one or more second limiting obstacles as true; and The one or more second driving routes among the one or more third driving routes for the vehicle to reach the destination point are calculated, wherein the second probability is calculated to be true for the one or more second driving routes.

17. A non-transitory storage medium storing a sequence of instructions which, when executed by a processor, causes: detecting one or more objects attached to the vehicle; determining an overall height of the vehicle, wherein the overall height of the vehicle comprises a first height of the vehicle and a second height of the one or more objects; Obtaining a first driving route for the vehicle to reach a destination; extracting first height limit information of one or more first limiting obstacles located along the first driving route; determining a first clearance height based on the overall height of the vehicle and first height limit information of the one or more first limit obstacles; When the first clearance height is greater than a threshold clearance height, calculating a first probability that the vehicle together with the one or more objects safely passes through the one or more first limiting obstacles as true, and transmitting a maneuvering instruction to an electric drive unit to maneuver the vehicle; and When the first probability is calculated as false, a signal is transmitted to a control module to dynamically adjust an adjustable roof rack to change the overall height of the vehicle, wherein the first probability is calculated as false when the first headroom height is less than the threshold headroom height.

18. The non-transitory storage medium of claim 17, further causing: One or more second driving routes for the vehicle to reach the destination are calculated.

19. The non-transitory storage medium of claim 18, wherein: The one or more second driving routes for the vehicle to reach the destination are calculated such that: identifying a current location of the vehicle; Obtaining a destination point of the vehicle; determining one or more third travel routes leading to the destination point based on the current location and the destination point; extracting second height restriction information of one or more second restriction obstacles located along the one or more third driving routes; determining a second clearance height based on the overall height of the vehicle and the second height limit information of the one or more second limit obstacles; and When the second clearance height is greater than the threshold clearance height, calculating a second probability that the vehicle together with the one or more objects safely passes through the one or more second limiting obstacles as true; and The one or more second driving routes among the one or more third driving routes for the vehicle to reach the destination point are calculated, wherein the second probability is calculated to be true for the one or more second driving routes.

20. The non-transitory storage medium of claim 17, further causing: The adjustable roof rack is dynamically adjusted to one of a first level, a second level, and a third level based on commands received from an artificial intelligence module.

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