Vehicle tire positioning system and method using tire and / or wheel sensors and directional antennas

Abstract

A system for identifying vehicle wheel positions includes sensors mounted on each tire of a vehicle. Each axle of the vehicle is associated with a first directional antenna configured to capture wireless output signals from each tire on one side and a second directional antenna configured to capture wireless output signals from each tire on the other side. A data processing unit (e.g., an in-vehicle controller, a remote server) receives output signals from each sensor via at least respective directional antennas and automatically identifies each wheel position on the vehicle based on the mapped relative positions for each of the directional antennas and further based on the detected relative output signal strengths for any tire and / or wheel sensor associated with an axle having a plurality of tires on each side of the vehicle. A switching device may optionally enable selection between each directional antenna for implementation of respective output signals.

Description

Technical Field

[0001] The present invention generally relates to the automatic location of tires and / or wheel sensors on wheeled vehicles. More specifically, the systems, methods, and related algorithms disclosed herein can use tire and / or wheel sensors, directional antennas, and in some embodiments a relative signal strength indicator (RSSI) for tire location, which can be used for the improvement of fleet management, cost prediction, and tire wear prediction of wheeled vehicles including, but not limited to, motorcycles, consumer vehicles (e.g., passenger cars and light trucks), commercial vehicles, and off-road (OTR) vehicles.

Background Art

[0002] Knowing the relative position of tire and / or wheel sensors, such as tire pressure monitoring system (TPMS) sensors, vehicle-mounted sensors, or tire-mounted sensors (TMS), is an important feature regardless of whether the vehicle is a passenger vehicle or a commercial vehicle. In commercial vehicles, which often have 18 tires and where tire positions can change during maintenance, the importance can increase. However, most fleet management systems cannot adequately track or otherwise document such information. This can pose difficulties for a number of important fleet management tasks, such as the generation of maintenance alerts, prediction of the amount of remaining wear life, prediction of which (and when) tires need to be replaced, cost prediction, etc.

Summary of the Invention

[0003] The methods disclosed herein can accurately and reliably track a tire and / or wheel sensor, or its output signal, for a given tire on a given vehicle.

[0004] A first exemplary embodiment of the system disclosed herein for vehicle wheel positioning includes at least one tire and / or wheel sensor associated with each of a plurality of tires mounted on a vehicle, wherein the vehicle comprises a plurality of axles having at least one tire on each of a first and second side of the vehicle. For each of the axles, a first directional antenna is positioned to capture radio output signals from each of the at least one tires associated with the axle on the first side, and a second directional antenna is positioned to capture radio output signals from each of the at least one tires associated with the axle on the second side. A data processing unit is configured to receive output signals from each of the tire and / or wheel sensors via at least each directional antenna and is further configured to automatically identify the respective wheel position on the vehicle for each of the tire and / or wheel sensors based on the mapped relative position for each of the directional antennas.

[0005] In a second embodiment, further exemplary aspects of the first embodiment referenced above include the vehicle comprising at least one axle having a single tire on each of the first and second sides, and at least one axle having multiple tires on each of the first and second sides, and the data processing unit being configured to automatically identify the respective wheel position on the vehicle for each of the tire and / or wheel sensors based on the mapped relative position for each of the directional antennas, and further based on the detected relative output signal intensity for at least the tire and / or wheel sensors associated with the multiple axles having multiple tires on each of the first and second sides.

[0006] In a third embodiment, further exemplary aspects according to the first or second embodiment referenced above may include the wireless output signal from each tire containing data corresponding to one or more measured tire characteristics.

[0007] A further exemplary embodiment of the third embodiment referenced above may include a wireless output signal from a single tire and / or wheel sensor for at least one tire, which includes an identifier unique to each tire and data corresponding to one or more measured tire characteristics.

[0008] Alternatively, the radio output signal from at least one tire may include a radio frequency identification (RF) signal specific to each tire via an RFID tag acting as a first tire and / or wheel sensor, and data corresponding to one or more measured tire characteristics from a second tire and / or wheel sensor.

[0009] A further exemplary embodiment of the third embodiment referenced above may include the data processing unit being configured to associate at least one of one or more measured tire characteristics in the data storage with each of the identified tire and / or wheel sensors and the wheel position on the vehicle.

[0010] A further exemplary embodiment of the third embodiment referenced above may include the data processing unit being configured to detect changes in the position of identified tires and / or wheel sensors and corresponding tires from a first wheel position on the vehicle to a second wheel position, and to aggregate at least one of one or more measured tire characteristics received from the identified tires and / or wheel sensors at each of the first and second wheel positions into data storage.

[0011] In the fourth embodiment, an exemplary further aspect of one of the first to third embodiments referenced above may include an RF receiver comprising multiple channels, each corresponding to one of the directional antennas associated with the vehicle, in order to simultaneously implement each output signal.

[0012] Alternatively, the system may include an RF switching device configured to allow selection between each of the directional antennas associated with the vehicle in order to implement each output signal.

[0013] A further exemplary embodiment according to one of the first to fourth embodiments referenced above may include a case in which at least one tire and / or wheel sensor includes at least a tire pressure monitoring system (TPMS) sensor and / or a tire-mounted sensor (TMS).

[0014] In the fifth embodiment, a further exemplary aspect of one of the first to fourth embodiments referenced above may include the data processing unit being further configured to store historical information relating to the tire wear of each tire in data storage and to estimate the current tire wear state of each tire based on the stored historical information relating to at least the identified wheel position and tire wear.

[0015] Further exemplary embodiments of the fifth embodiment referenced above may include the data processing unit being configured to predict one or more tire traction characteristics for each tire based on at least an estimated tire wear state, to provide one or more predicted tire traction characteristics to the vehicle control unit, and to automatically modify one or more vehicle operating settings based on at least one or more predicted tire traction characteristics via the vehicle control unit.

[0016] A further exemplary embodiment of the fifth embodiment referenced above may include the data processing unit being further configured to predict, for each tire, when it is time to replace it, based on one or more of the current tire wear condition and predicted tire wear conditions, compared with one or more tire wear thresholds.

[0017] A further exemplary embodiment of the fifth embodiment referenced above may include the fact that each tire wear threshold for a given tire corresponds to an identified wheel position associated with the tire.

[0018] Further exemplary embodiments according to any one of the first to fifth embodiments referenced above may include an in-vehicle vehicle control unit comprising a data processing unit.

[0019] Alternatively, the system may include a server-based network or mobile computing devices equipped with data processing units.

[0020] Alternatively, the data processing unit may consist of distributed, functionally interacting modules associated with one or more of the following: an in-vehicle control unit, a server-based network, and / or a mobile computing device. [Brief explanation of the drawing]

[0021] The embodiments of the present invention will be illustrated in more detail below with reference to the drawings. [Figure 1] Figure 1 is a block diagram representing one embodiment of a tire positioning system disclosed herein. [Figure 2] Figure 2 is a modified top view illustrating an exemplary configuration of a tire and / or wheel sensor and a directional antenna in one embodiment of the system disclosed herein. [Figure 3] Figure 3 is a flowchart illustrating an exemplary embodiment of the operating method disclosed herein.

Best Mode for Carrying Out the Invention

[0022] Generally, referring to FIGS. 1-3, various exemplary embodiments of the present invention can be described in detail herein. When various figures may describe embodiments that share various common elements and features with other embodiments, the same elements and features may be given the same reference numerals, and their duplicate descriptions may be omitted hereinafter.

[0023] First, referring to FIG. 1, an exemplary embodiment of the system 100 disclosed herein can generally be applied to both commercial vehicles and passenger vehicles, and includes at least one tire and / or wheel sensor 114 provided for each of a plurality of tires 112 mounted on the vehicle. The tire and / or wheel sensor 114 may include any of various tire-mounted sensors, and in some embodiments, for example, may include a tire pressure monitoring system (TPMS) sensor such as is currently often included in certain large trucks. Examples of conventional TPMS include a sensor transmitter that is functionally linked to a TPMS receiver, which itself is further linked to a data processing unit. The TPMS sensor transmitter may be provided, for example, within the internal air cavity of the tire 112, either on the tire wheel or on the inner surface of the tire. The transmitter detects the internal pressure of the tire at predetermined time intervals and wirelessly transmits an output signal corresponding to the internal pressure value of the tire to the receiver, along with a unique identifier associated with the tire. The transmitter may be mounted on the wheel rim, for example, so as to be integrated with the tire valve. Alternatively, the transmitter may be attached to the inner surface of the tire. The receiver further relays the signal from the transmitter to the data processing unit via a communication means such as Bluetooth.

[0024] Other examples of tire and / or wheel sensors 114 within the scope of the present disclosure can include sensors mounted to the valve stem of the tire 112, and further can include sensors mounted to the outer surface of the tire 112.

[0025] In certain embodiments, a single tire and / or wheel sensor 114 may be configured to transmit an output signal that includes an identifier, for example, as part of a data string, along with other data corresponding to the measured tire characteristics. In other embodiments, one or more tire and / or wheel sensors 114 on a given tire may be configured to generate output signals corresponding to the measured tire characteristics, while another tire and / or wheel sensor 114 on the same tire may be configured to generate identification data, for example, via an RFID tag separate from the first set of one or more tire and / or wheel sensors 114. In such embodiments, the output signals from each of the tire and / or wheel sensors 114 may be generated sequentially, or the output signal from the RFID tag may be generated selectively or otherwise triggered, for example, based on the initialization of the output signal when the vehicle starts operating, via a command from an external source or from other tire and / or wheel sensors from the first set of one or more tire and / or wheel sensors.

[0026] The embodiment of system 100 shown in FIG. 1 further includes a pair of directional antennas 120 mounted on the vehicle in relation to each vehicle axle 104 of the vehicle, and each of the directional antennas 120 is directed outwardly from an inner position, for example, with respect to the tire 112 of the corresponding vehicle axle 104. In the case of a single-tire axle 104, a directional antenna 120 is assigned to each tire 112x. However, in the case of a dual-tire axle 104 as shown, for example, in FIG. 2, a single directional antenna 120 is assigned to two tires 112x1, 112x2, and the antenna 120 is focused on one of those tires. Thus, the antenna 120 is more sensitive to the signals of the tire and / or wheel sensor 114 attached to the tire in close proximity to the antenna 120 and less sensitive to the tire and / or wheel sensor 114 of the tire 112 that is further away from the antenna 120 on the same axle side. This sensitivity can be converted to a relative signal strength indicator (RSSI), and the RSSI of the signals from the nearby tire and / or wheel sensor 114 is higher than the RSSI of the signals coming from the tire and / or wheel sensor 114 that is further away from the antenna.

[0027] For example, referring to Figure 2, a single-tire axle 104a is provided with a directional antenna 120a for a single tire 112a on one side of the axle / vehicle and a directional antenna 120b for a single tire 112b on the other side of the axle / vehicle. In this situation, RSSI is not required as an element to identify each tire 112. Note that the illustrated positions of the directional antennas 120a and 120b are not limiting to the scope of the embodiment and may vary at least in part based on the design needs of a given vehicle, axle, antenna, etc., as long as the field of the directional antennas is positioned to reliably capture output signals from the associated tire and / or wheel sensors. While the illustrated embodiments and the description herein may state that a given directional antenna 120 is provided or directed to one or more corresponding tires 112, it should be further noted that the directional antenna 120 may be further provided or directed to one or more corresponding tire and / or wheel sensors 114 associated with these tires 112.

[0028] In the case of the first dual-tire axle 104b as shown in Figure 2, the directional antenna 120c on the first side of the axle / vehicle is pointed towards tires 112c1 and 112c2, and the directional antenna 120d on the second side of the axle / vehicle is pointed towards tires 112d1 and 112d2. In this example, the RSSI of the tire and / or wheel sensor 114c2 associated with tire 112c2 is higher than the RSSI of the tire and / or wheel sensor 114c1 associated with tire 112c1, based on the received signal strength of antenna 120c, and the RSSI of the tire and / or wheel sensor 114d2 associated with tire 112d2 is higher than the RSSI of the tire and / or wheel sensor 114d1 associated with tire 112d1, based on the received signal strength of antenna 120c. Comparisons of equivalent configurations and exemplary RSSIs will be readily apparent to those skilled in the art for each of the remaining dual-tire axles 104b in Figure 2.

[0029] The ten directional antennas 120 on the commercial vehicle shown in Figure 2 can be connected to a data processing unit 140 via an RF switch 130, thereby allowing for the selective reception and separate analysis of the output signals from each directional antenna 120. In an alternative embodiment, the directional antennas 120 may be communicatively coupled or functionally linked to the data processing unit 140 via a multi-channel receiver to simultaneously implement their respective output signals from each of the tire and / or wheel sensors 114. In yet another alternative embodiment, the directional antennas 120 may be connected to the data processing unit 140 via their respective independent receivers (i.e., ten receivers in the embodiment involving ten directional antennas).

[0030] The data processing unit 140 may take any of the various forms within the scope of this disclosure, including, for example, a fleet management device or server, a third-party server network, or a computing device mounted in a vehicle and configured to at least acquire data, transmit such data to a remote server, and / or perform related calculations as disclosed herein. The in-vehicle computing device as the data processing unit 140, its components, or the intermediary between the directional antenna 120 and the data processing unit 140 may be portable or otherwise modular as part of a distributed vehicle data acquisition and control system, or otherwise provided integrally with a central vehicle data acquisition and control system, for example, an electronic control unit (ECU) 160. The data processing unit 140 may include, for example, a display unit 142, a processor 148, a memory / computer-readable medium 144 in which program logic resides, and data storage 146, which may include, for example, the mapped positions of each directional antenna 120, tire data and / or vehicle operation data (whether directly or indirectly measured and stored), and models derived therefrom over time. The data processing unit 140 may further include a communication unit 150 for wired or wireless connections to various vehicle components, control units, server networks, etc.

[0031] Accordingly, a system 100 as disclosed herein may implement a number of components distributed across one or more vehicles, but may not necessarily be associated with a fleet management entity, and may further implement a central server or server network that functionally communicates with each of the vehicles via a communication network. Vehicle components may typically include one or more sensors 116 in addition to the tire and / or wheel sensors 114 and related on-board components described above, such as position sensors including vehicle accelerometers, gyroscopes, inertial measurement units (IMUs), global positioning system (GPS) transponders, ambient temperature sensors, and engine sensors, which are linked to a controller area network (CAN) bus network and thereby provide signals to a data processing unit 140 or other local processing units.

[0032] Given the following considerations, other sensors for collecting and transmitting vehicle data related to speed, acceleration, braking characteristics, etc., will be readily apparent to those skilled in the art and will not be further discussed herein. Various bus interfaces, protocols, and associated networks are well known in the art for communication of vehicle dynamics data, etc., between their respective data sources and local computing devices, and those skilled in the art will recognize a wide range of such tools and implementations for doing so.

[0033] System 100 may include a data processing unit 140 that is not essentially discrete, even in the case of an in-vehicle computing device, but further comprises, for example, additional distributed program logic residing on a fleet management server or other user computing device 140, or a user interface for a device (not shown) residing in the vehicle or associated with its driver for real-time notifications (e.g., via visual and / or audio indicators), the fleet management device being functionally linked to the in-vehicle device via a communication network in some embodiments. System programming information may be provided onboard, for example, by the driver or by the fleet manager.

[0034] Referring next to Figure 3, an exemplary embodiment of Method 300 according to the present disclosure may include a first step (step 310) of mapping a plurality of directional antennas 120 to their respective wheel positions on a vehicle. As previously mentioned, the use of directional antennas 120 makes it possible to isolate and easily identify output signals from tire and / or wheel sensors 114 in the relevant field with respect to the mapped wheel position.

[0035] In one embodiment, the tire and / or wheel sensor 114 may further comprise a unique identifier transmitted via a directional antenna 120 and a receiver / RF switch 130. Thus, method 300 may further include the step (step 320) of mapping the tire and / or wheel sensor identifier to each of the corresponding tire sets, in particular, if the output signals from the tire and / or wheel sensor in use include such identifiers, for example using radio frequency identification (RFID), the data processing unit 140 can distinguish the signals provided from each sensor 114 on the same vehicle, and further, for example in a fleet management context, the signals provided from tires 112 and associated tire and / or wheel sensors 114 across multiple vehicles can be distinguished. In other words, the sensor output values ​​may, in various embodiments, be associated with a particular tire, a particular vehicle, and / or a particular tire vehicle system for the purpose of on-board or remote / downstream data storage and implementation disclosed herein. Therefore, a tire 112 repositioned from the first wheel on the vehicle may be easily identifiable as having been moved from the first wheel to another wheel on the same vehicle or a different vehicle, since an output signal is subsequently sent to the respective data processing unit 140. In various embodiments, for example, the tire and / or wheel sensor 114 is mounted inside the tire or otherwise attached to the tire so as to be substantially fixed, but in the case where the first tire and / or wheel sensor is predictably removable from the initial tire and is interchangeable with another (e.g., a second) tire and / or wheel sensor, the system 100 may be further configured to map the duration associated with the first tire and / or wheel sensor mounted on a given tire to the duration associated with the second tire and / or wheel sensor mounted on the same tire, for example, for the purpose of monitoring the tire condition over time.

[0036] An exemplary method 300 further includes the steps of receiving the output signal of the tire and / or wheel sensor 114 in a corresponding directional antenna 120 during vehicle operation (step 330), and routing the output signal to a data processing unit 140 via, for example, the RF switch or multi-channel receiver 130 described above.

[0037] Signals received from specific tire and / or wheel sensors 114 may be stored in an in-vehicle device memory or an equivalent data storage unit functionally linked to an in-vehicle device processor for selective acquisition as needed for modeling, calculation, or displaying alerts, in accordance with the methods disclosed herein. In some embodiments, raw data signals from various tire and / or wheel sensors 114 may be communicated from the vehicle to a remote server in substantially real time. Alternatively, taking into account the inherent inefficiencies in continuous data transmission, particularly of high-frequency data, the data may be compiled, encoded, and / or summarized for more efficient transmission (e.g., periodic time-based or alternatively defined event-based) from the vehicle to the remote server, for example, via a suitable communication network.

[0038] In step 350, the wheel position for each tire and / or wheel sensor 114 generating the output signal can be further determined using the mapped position in the data storage for each of the relative directional antennas 120 in relation to the output signal received via each directional antenna 120. For example, referring again to Figure 2, the directional antenna 120k may be digitally mapped in relation to two known wheel positions along one side of a particular dual-tire axle 104b. The output signals received via the directional antenna 120k are distinguishable by taking into account at least the respective identifiers associated with the tire and / or wheel sensors 114 of tires 112k1 and 112k2, and / or their relative signal strength (RSSI). Therefore, the data processing unit 140 or other relevant parts of the system 100 can store and optionally aggregate tire data and / or vehicle tire data related to one or more of the following: tire and / or wheel sensors 114 (and thus tires 112k1 and 112k2 to which the sensors are mounted or otherwise associated), wheel position on the vehicle, axle, vehicle, driver, etc.

[0039] Following this example, tire 112k1 may later be moved to another location on the vehicle to replace tire 112d2 for illustrative purposes, as shown in Figure 2. During the subsequent operation of the vehicle, the data processing unit 140 (via the directional antenna 120d) receives output signals from the tire and / or wheel sensor 114 associated with tire 112k1 and the tire and / or wheel sensor 114 associated with tire 112d1, and verifies that the tire and / or wheel sensor 114 associated with tire 112k1 is in the new wheel position, based on the identifier associated with the tire and / or wheel sensor and taking into account the relative signal strength (RSSI). The data processing unit 140 or other relevant parts of the system 100 then continue to store the tire data and / or vehicle tire data associated with tire 112k1, taking into account the new wheel position, and may optionally aggregate this data.

[0040] As described above, the output signals from the tire and / or wheel sensors 114, such as a tire pressure monitoring system (TPMS) sensor, may include real-time measurements of values ​​such as tire pressure, air temperature, and acceleration, or may correspond to them otherwise. Such measurements may be directly or indirectly verified by the data processing unit 140 or other downstream computing devices such as a remote server or fleet management network, and may be used to determine whether an alert should be generated for a given wheel position for a given vehicle and tire combination, driver, etc., based on the tire characteristics (e.g., based on low tire inflation pressure) (step 360). Such alerts may take the form of visual displays or audiovisual alerts generated on a separate display unit, such as on an in-vehicle user interface / display unit or on a mobile computing device associated with the vehicle operator (step 365).

[0041] In one embodiment, tire data and / or vehicle tire data may be transmitted via a communication network to a remote server or fleet management network and stored, for example, in an associated database. The server / device / network may include, or be associated with, a tire wear model and / or tire traction model to selectively acquire and process tire vehicle data and / or tire data as appropriate input (step 370). The model may be implemented manually or automatically selectively based on identified trigger activity or measurement, or may be implemented periodically on a time basis, for example, and may further enable the acquisition of vehicle data and / or tire data and electronic communication for input of any additional relevant data or algorithms from a database, lookup table, etc., stored in association with the server.

[0042] Various tire wear values ​​may be estimated based on, for example, "digital twin" virtual representations of various physical parts, processes, or systems, with digital and physical data paired and combined with a learning system such as a neural network. For example, real data from the vehicle and associated location / path information may be provided to generate a digital representation of the vehicle tires for tire wear estimation, and subsequent comparison of the estimated tire wear with the determined actual tire wear may be performed as feedback to a machine learning algorithm. The wear model may be implemented in the vehicle for processing via an onboard system, or the tire data and / or vehicle data may be processed to provide representative data to a hosted server for remote wear estimation.

[0043] Tire wear conditions (e.g., tread depth) may be provided as input to a traction model, for example, along with specific vehicle data, and the traction model may be configured to provide estimated traction conditions or one or more traction characteristics for each tire. Similar to the wear model described above, the traction model may include a “digital twin” virtual representation of a physical part, process, or system, where digital and physical data are paired and combined with a learning system, such as an artificial neural network. Actual vehicle data and / or tire data from a specific tire, vehicle, or tire vehicle system may be provided throughout the lifecycle of each asset to generate a virtual representation of the vehicle tire for tire traction estimation, and a subsequent comparison of the estimated tire traction with the corresponding measured or determined actual tire traction may result in an alert, for example, corresponding to an identified active safety problem (step 380), the alert being generated substantially in real time to notify an operator on a relevant display unit (step 365), and / or implemented as feedback for machine learning algorithms running at the remote server and / or fleet management device / network level.

[0044] In various embodiments, the traction model may utilize results from prior tests, such as stopping distance test results and tire traction test results, collected with respect to associated combinations of values ​​of numerous tire-vehicle systems and input parameters (e.g., tire tread, inflation pressure, road surface characteristics, vehicle speed and acceleration, slip ratio and angle, vertical force, braking pressure and load), and the tire traction output may be effectively predicted for a given setting of current vehicle data and tire data inputs.

[0045] In one embodiment, the output from this traction model may be provided to a vehicle control unit, for example, to be incorporated into an active safety system (step 390). As used herein, the term “active safety system” may encompass systems commonly known to those skilled in the art, including but not limited to collision avoidance systems, advanced driver-assistance systems (ADAS), and anti-lock braking systems (ABS), which may be configured to utilize traction model output information to achieve optimal performance. For example, a collision avoidance system is typically configured to take avoidance actions, such as automatically engaging the brakes of the vehicle, to avoid or mitigate a potential collision with a target vehicle, and extended information regarding the traction capability of the tires, i.e., the braking capability of the tire vehicle system, is highly desirable.

[0046] In another embodiment, a rideshare autonomous fleet may use output data from a traction model to disable or otherwise selectively remove vehicles with low tread depth during adverse weather conditions, or potentially limit their maximum speed.

[0047] In various embodiments, the method may further include comparing the current wear value to a threshold to determine whether (or when) the tire needs to be replaced. Alternatively or further, the method may include predicting the wear value at one or more future points in time, such predicted values ​​may be compared to the respective thresholds. A feedback signal corresponding to the predicted tire wear condition (e.g., predicted tread depth at a given distance, time, etc.) may be provided via an interface to an in-vehicle display unit associated with the vehicle itself (step 365), which integrates a user interface configured to provide alerts or notifications / recommendations that the tire should be replaced or will soon need to be replaced, for example, via an interface to a mobile device associated with the user.

[0048] As another example, an autonomous vehicle fleet may include a number of vehicles with various minimum tread state values, and the vehicle fleet management system may be configured to disable the deployment of vehicles that fall below a minimum threshold. The fleet management system may further implement various minimum tread state values ​​corresponding to wheel positions. The system may therefore be configured to act on the minimum tire tread value of each of the multiple tires associated with the vehicle, or, in one embodiment, it may calculate an aggregated tread state of the multiple tires for comparison with a minimum threshold.

[0049] In various embodiments, the method may further include data streaming even if no threshold violation is detected, and the estimated and / or predicted wear values ​​can be displayed in real time on a local user interface and / or remote display (e.g., associated with a fleet management server), and the displayed data may further include, for example, the contained air temperature.

[0050] Throughout this specification and the claims, unless the context indicates otherwise, the following terms have at least the meanings expressly relating to this specification. The meanings identified below are not necessarily limiting and are merely illustrative examples of the terms. The meanings of “a,” “an,” and “the” may include multiple references, and the meaning of “in” may include “in” and “on.” When used herein, the phrase “in one embodiment” may, but not necessarily, refer to the same embodiment.

[0051] Various illustrative logic blocks, modules, and algorithmic steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this hardware and software compatibility, various illustrative components, blocks, modules, and steps are generally described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. The described functionality can be implemented in various ways for each specific application, but such implementation decisions should not be construed as causing a departure from the scope of this disclosure.

[0052] Various illustrative logic blocks and modules described in relation to the embodiments disclosed herein can be implemented or executed by machines, such as general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but alternatively, the processor may be a controller, microcontroller, or state machine, or a combination thereof. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors working with a DSP core, or any other combination of such configurations.

[0053] Steps of methods, processes, or algorithms described in relation to embodiments disclosed herein may be implemented directly in hardware, in software modules executed by a processor, or in combination of both. The software modules may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of computer-readable medium known in the art. An exemplary computer-readable medium may be coupled to a processor so that the processor can read information from and write information to the memory / storage medium. Alternatively, the medium may be integrated with the processor. The processor and medium may reside within an ASIC. The ASIC may reside within a user terminal. Alternatively, the processor and medium may reside as separate components within a user terminal.

[0054] Conditional language used herein, in particular, such as “can,” “might,” “may,” and “e.g.,” is generally intended to convey that certain embodiments include certain features, elements, and / or states, while other embodiments do not include those features, elements, and / or states, unless otherwise specifically stated or understood in the context in which they are used. Accordingly, such conditional language is generally not intended to suggest that features, elements, and / or states are required in any way for one or more embodiments, nor is it generally intended to suggest that one or more embodiments necessarily include logic for determining, with or without author input or prompting, whether these features, elements, and / or states are included in or should be performed in any particular embodiment.

[0055] Certain preferred embodiments of the present invention may typically be described herein for fleet management systems, more specifically for tire wear estimation for autonomous vehicle fleets or commercial truck applications, but the present invention is not expressly limited thereto, and where used herein, the term “vehicle” means, unless otherwise stated, an automobile, truck, or any equivalent thereof, which may include one or more tires, whether self-propelled or not, and therefore may require accurate estimation or prediction of tire wear, as well as potential deactivation, replacement, or intervention, for example, in the form of direct vehicle control adjustment.

[0056] When used herein, unless otherwise specified, the term “User” may refer to, for example, a driver, passenger, mechanic, technician, fleet management officer, or any other person or entity associated with a device having a user interface for providing the features and steps disclosed herein.

[0057] The detailed explanations provided above are for illustrative and illustrative purposes only. While specific embodiments of the novel and useful invention have been described, such references are not intended to be construed as limiting the scope of the invention, except as stated in the following claims.

Claims

1. A system (100) for determining the position of a vehicle wheel, At least one tire and / or wheel sensor (114) associated with each of a plurality of tires (112) mounted on a vehicle, wherein the vehicle comprises a plurality of axles (104), at least one axle having a single tire on each of the first and second sides of the vehicle, and at least one axle having a plurality of tires on each of the first and second sides, and at least one tire and / or wheel sensor (114), Each of the axles is provided with a first directional antenna (120) configured to capture a radio output signal from at least one tire associated with the axle on a first side, and a second directional antenna (120) configured to capture a radio output signal from at least one tire associated with the axle on a second side, A system (100) for determining the position of a vehicle wheel, comprising: a data processing unit (140) configured to receive the output signals from each of the tire and / or wheel sensors via at least each of the directional antennas (330), and further configured to automatically identify the respective wheel position on the vehicle for each of the tires based on the mapped relative position (350) for each of the directional antennas, and further based on the detected relative output signal intensity for at least the tire and / or wheel sensors associated with the plurality of axles having a plurality of tires on each of the first and second sides.

2. The system according to claim 1, wherein the wireless output signal from each tire includes data corresponding to one or more measured tire characteristics.

3. The system according to claim 2, wherein the wireless output signal from a single tire and / or wheel sensor for at least one tire includes an identifier unique to each tire and the data corresponding to one or more measured tire characteristics.

4. The system according to claim 2, wherein the wireless output signal from at least one tire includes a radio frequency identification (RF) signal specific to each of the tires via an RFID tag as a first tire and / or wheel sensor, and the data corresponding to one or more measured tire characteristics from a second tire and / or wheel sensor.

5. The aforementioned data processing unit is Associating at least one of the one or more measured tire characteristics in the data storage with each of the identified tire and / or wheel sensors and the wheel position on the vehicle, To detect changes in the position of the identified tire and / or wheel sensor and the corresponding tire from the first wheel position to the second wheel position on the vehicle, The system according to claim 2, configured to aggregate at least one of the one or more measured tire characteristics received from the identified tire and / or wheel sensor at each of the first wheel position and the second wheel position into a data storage.

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