SYSTEMS AND METHODS FOR MULTI-SOURCE VEHICLE WEAR AND MAINTENANCE DETECTION USING MACHINE LEARNING TECHNIQUES

A system described herein may provide a technique for determining a measure of wear and tear on a vehicle as well as one or more actions to take, such as increased maintenance and/or particular types of maintenance or repairs. The system may maintain models associating vehicle input information with respective vehicle wear classifications, and may receive vehicle input information associated with a particular vehicle, including sensor data measured by a User Equipment (“UE”), and/or vehicle information provided by the particular vehicle. The system may compare the received particular set of vehicle input to the models and may determine, based on the comparing, a vehicle wear classification associated with the particular vehicle. The system may identify one or more actions associated with the determined one or more vehicle wear classifications; and may output, to the UE, information indicating the identified one or more actions.

BACKGROUND

Vehicles, such as cars, trucks, etc. may be equipped with on-board diagnostics and/or telematics monitoring equipment. Such vehicles may make diagnostic and/or telematic information available via an on-board diagnostics (“OBD”) port, such as an OBD port conforming to an OBD-II standard. User Equipment (“UEs”), such as mobile phones, may have wireless communication capability, such that UEs are able to wirelessly communicate with servers or other devices via a wireless network.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

Embodiments described herein provide for the monitoring of vehicle usage patterns in order to determine measures of wear, abuse, etc. to which vehicles are subjected. As shown inFIG.1, embodiments described herein may, for example, receive vehicle-related data associated with a given vehicle101from multiple sources, such as from an OBD monitor103communicatively coupled to vehicle101, navigation and/or information source105, UE107(e.g., sensor data collected by UE107located within vehicle101while vehicle101is operating), and/or other suitable sources. Vehicle Wear Determination System109may, for example, receive some or all of the above-mentioned information (e.g., from UE107via a wireless network), and may determine metrics, classifications, actions, recommendations, alerts, etc. related to wear and tear, degradations, etc. (referred to herein simply as “wear” for the sake of clarity) based on the received information.

Generally, for example, a vehicle that is “driven harder,” such as with relatively high measures of acceleration or braking, more severe lateral forces (e.g., sharper and/or faster turns), with more engine ignitions, more “stop and go” traffic, more steep ascent and/or decline angles, etc. may experience greater measures of wear than vehicles that are driven more conservatively, less frequently, etc. A driver, owner, an insurer, etc. of such vehicle may desire to gain insight as to how worn the vehicle is becoming, as performing maintenance and/or repairs may be costly, or otherwise advisable to keep the vehicle in safe, working order. As discussed below, Vehicle Wear Determination System109may utilize artificial intelligence/machine learning (“AI/ML”) techniques or other suitable techniques in order to train models based on which Vehicle Wear Determination System109may identify how worn vehicle101is becoming, may identify specific types of wear on vehicle101(e.g., engine wear, tire wear, brake wear, electrical system wear, etc.), and/or may identify remedial actions based on identifying measures of wear on vehicle101. As discussed below, remedial actions may include recommending different driving habits in order to reduce wear, recommending different driving routes in order to reduce wear, recommending specific types of maintenance or repairs to perform in order to repair or replace worn parts, modifying service intervals, and/or other suitable actions.

As another example, the actions may include reporting measures of wear to a governmental agency, such as a local or state agency that enforces periodic (e.g., annual) safety inspections, where reporting relatively minimal wear (or wear below a threshold) may place vehicle101in compliance for a particular period. For instance, vehicle101may “pass an annual inspection” based on information determined and provided by Vehicle Wear Determination System109. As another example, the actions may include reporting measures of wear to a bank, lender, car dealer, etc., which may set or modify a value of the vehicle based on the determined measure of wear (e.g., less worn vehicles may be in “good” or “excellent” condition, based on which the value of such vehicles may be higher than vehicles that are in “fair” or “poor” condition).

FIG.2illustrates an example of monitoring and/or collecting information based on which Vehicle Wear Determination System109may determine a measure of wear of vehicle101. As shown, OBD monitor103may receive vehicle diagnostics, telematics, and/or other information (referred to herein simply as “vehicle information” for the sake of simplicity) via OBD port201. OBD monitor103may implement the same interface, communication protocol(s), etc. as vehicle OBD port201. For example, vehicle OBD port201and OBD monitor103may implement an OBD-II standard, or other suitable standard or protocol, via which vehicle OBD port201outputs vehicle information to OBD monitor103. In some embodiments, OBD monitor103may include a physical mating apparatus, adapter, plug, etc. that physically interfaces with (e.g., “plugs into”) vehicle OBD port201. In some embodiments, OBD monitor103and vehicle OBD port201may communicate in come other suitable manner, such as via one or more intervening interfaces or communication devices.

In some embodiments, such vehicle information may include vehicle attributes or parameters, such as make, model, year, vehicle information number (“VIN”), vehicle type (e.g., sedan, truck, etc.), and/or other information pertaining to attributes of vehicle101. In some embodiments, vehicle information provided by vehicle OBD port201may include historical and/or logged information, such as error codes, mileage traveled, events, alerts, drive cycles since last error code reset, average trip duration (e.g., average duration between starting and stopping an engine of vehicle101), “redline” incidences (e.g., quantity of occurrences that an engine of vehicle101has met or exceeded a threshold number of rotations per minute (“RPMs”)), and/or other such information. In some embodiments, vehicle information provided via vehicle OBD port201may include real-time diagnostics, such as current mileage, fuel level, battery voltage, throttle inputs, braking inputs, steering inputs, vehicle climate system operational status (e.g., temperature, fan speed, etc. of air vents within vehicle101), electrical system current draw (e.g., which may indicate components or systems of vehicle101that are drawing electrical current, such as a battery, a power outlet within a cabin of vehicle101, etc.), and/or other real-time diagnostics. In some embodiments, the vehicle information may include service and/or maintenance information, which may be based on inputs provided by a technician during a vehicle service visit, such as dates of maintenance or repairs, types of maintenance or repairs performed, etc. In some embodiments, vehicle OBD port201may provide other types of information in addition to, or in lieu of, the examples provided above.

OBD monitor103may, in some embodiments, include wireless communication circuitry (e.g., utilizing Bluetooth, WiFi, and/or some other suitable wireless communication technology) via which OBD monitor103may provide some or all of the received vehicle information (e.g., as received from vehicle101via vehicle OBD port201) to UE107. For example, UE107may be “paired with” or otherwise communicatively coupled to OBD monitor103via a wireless interface. Additionally, or alternatively, UE107and OBD monitor103may communicate via physical communication pathway, such as via a wire, cable, universal serial bus (“USB”) port, etc. In some embodiments, some or all of the functionality described herein with respect to OBD monitor103may be performed by UE107. For example, in some embodiments, UE107may include and/or may be communicatively coupled to a cable, interface, adapter, etc. via which UE107may receive vehicle information from vehicle101via vehicle OBD port201. In some embodiments, UE107may execute an application, application programming interface (“API”), and/or other suitable communication mechanism by which UE107receives and maintains the vehicle information provided via vehicle OBD port201.

UE107may, as shown, further collect sensor data, which may be collected, measured, etc. by one or more sensors or other suitable devices that are integrated within or are otherwise communicatively coupled to UE107. For example, UE107may include one or more accelerometers, gyroscopes, barometers, thermometers, hydrometers, microphones, photosensors, etc. via which UE107may collect or measure sensor data. Such sensor data may include raw data, such as raw values measured or recorded by such sensors. Additionally, or alternatively, the sensor data may include processed and/or classified data, which may be determined by UE107(e.g., by an application executing on UE107) and/or some other suitable device or system (e.g., a remote application server that processes the sensor data using AI/ML techniques or other suitable techniques). Assume, for example, that the processed and/or classified data includes impact detection. The impact detection may be determined by UE107and/or some other suitable device or system based on accelerometer data and/or other suitable sensor data. For example, one or more models that indicates or predicts impacts based on such data may be compared to sensor data (e.g., accelerometer data) collected by UE107, and a match between such models and the accelerometer data may indicate that an impact occurred, a likely severity of the impact (e.g., low, medium, severe, etc.), a potential object with which the impact occurred (e.g., speed bump, another vehicle, wildlife, etc.), and/or other classifications. In other examples, UE107may determine other types of events, classifications, etc. determined based on sensor data collected or measured by one or more sensors associated with UE107. In this sense, the “sensor data” discussed with respect to UE107may include raw sensor data values, and may further include processed or categorized information based on raw sensor data values.

In some embodiments, UE107may collect, maintain, generate, etc. other types of information in addition to the sensor data discussed above. For example, in some embodiments, UE107may maintain or receive location information, such as a geographical location (e.g., latitude and longitude coordinates, Global Positioning System (“GPS”) coordinates, etc.) of UE107. In some embodiments, UE107may determine its own location, and/or may receive its location from a wireless network to which UE107is connected (e.g., a Long-Term Evolution (“LTE”) network, a Fifth Generation (“5G”) network, etc.). As another example, UE107may maintain information associated with one or more users, which may be associated with a driver profile (e.g., where a user of UE107may also be a driver of vehicle101). In some embodiments, UE107may maintain other types of information that may ultimately be used in determining a measure of wear on vehicle101.

In some embodiments, UE107may communicate with Navigation/Information Source105, which may provide navigation instructions, traffic information, road condition information, and/or other information to UE107. For example, UE107may execute an application that receives or determines a destination of vehicle101(e.g., a user of UE107and/or of vehicle101may specify the destination in a navigation request), and communicates with Navigation/Information Source105, which may provide navigation directions from a specified starting point (e.g., a present location of UE107) to the destination. In order to determine the navigation directions, Navigation/Information Source105may have access to traffic information, emergency alerts, indicating traffic density, road closures, accidents, average speed of vehicles on a given roadway, etc. In some embodiments, Navigation/Information Source105may provide some or all of such information to UE107(e.g., information pertaining to a navigation route requested via UE107, and/or information otherwise pertaining to roads on which vehicle101is traveling or has traveled).

UE107may provide some or all of the above-discussed information (e.g., vehicle information received from vehicle101via vehicle OBD port201, sensor data collected or measured by UE107and/or by one or more devices (e.g., wearable devices or other separate devices) that are communicatively coupled to UE107, and/or road/route information provided by Navigation/Information Source105) to Vehicle Wear Determination System109. UE107may provide such information via network203, which may be an LTE network, a 5G network, and/or some other suitable type of wireless network. In some embodiments, UE107may be communicatively coupled to a WiFi “hotspot” or other type of access point integrated in vehicle101, and may communicate with Vehicle Wear Determination System109via network203by way of such hotspot.

UE107may, in some embodiments, record sensor data, request or receive road/route information from Navigation/Information Source105, and/or perform other operations based on detecting that UE107is present within vehicle101and/or that vehicle101is in motion, is operational (e.g., an engine and/or electrical system is powered on). For example, UE107may detect that UE107is present within vehicle101and/or that vehicle101is operational based on connecting to one or more vehicle systems, such as a wireless infotainment system (e.g., using Bluetooth, WiFi, and/or some other wireless technique). Additionally, or alternatively, UE107may detect that UE107is present within vehicle101and/or that vehicle101is operational based on connecting to OBD monitor103and/or vehicle OBD port201, and/or based on information received via vehicle OBD port201(e.g., information indicating an operational status of vehicle101). In this manner, UE107may be able to collect, aggregate, etc. information that is relevant to determining measures of wear on vehicle101, without mixing such information with other, potentially irrelevant information (e.g., sensor data and/or other information collected or received by UE107while UE107is outside of vehicle101).

Vehicle Wear Determination System109may aggregate the information received from UE107, in order to gain a “big picture” analysis of information that may indicate how to what extent vehicle101is being subjected to factors that may contributed to wear on vehicle101. For example, Vehicle Wear Determination System109may “stitch together” some or all of the received information in order to determine time-based and/or location-based insights as to what types of events, usage patterns, etc. vehicle101is experiencing. For example, Vehicle Wear Determination System109may identify, based on a location of vehicle101(e.g., as determined by UE107and/or Navigation/Information Source105), traffic density information (e.g., as provided by Navigation/Information Source105), throttle and/or braking information (e.g., as provided by vehicle101via vehicle OBD port201), motion and/or acceleration sensor data (e.g., as collected by UE107), etc. that vehicle101is experiencing a relatively high measure of wear during certain times. For example, the location information and/or road/route information, along with an associated timestamp, may indicate that vehicle101is located on a relatively busy stretch of road (e.g., relatively high traffic density, relatively low average speed relative to a speed limit of the road, etc.) during a relatively busy time (e.g., “rush hour”). The throttle and/or braking information (and/or other vehicle telematics) may indicate that vehicle101is braking relatively frequently (e.g., within 10 seconds of a throttle being applied). The sensor data collected by UE107may indicate that vehicle101is starting and stopping relatively abruptly (e.g., short, quick bursts of acceleration or deceleration). As discussed below, Vehicle Wear Determination System109may compare the received information to one or more models, and may determine that vehicle101is experiencing relatively high levels of wear during such times based on comparing the aggregated data to one or more wear models.

As another example, Vehicle Wear Determination System109may receive vehicle information indicating that a climate system of vehicle101is frequently turned on while the engine of vehicle101is turned off. Vehicle Wear Determination System109may determine (e.g., based on one or more models, as discussed below) that this type of usage may contribute to excessive battery wear.

As yet another example, Vehicle Wear Determination System109receive sensor data (e.g., as measured or collected by UE107) and road/route information (e.g., from Navigation/Information Source105), based on which Vehicle Wear Determination System109may determine that tires of vehicle101are wearing unevenly, or in some other abnormal manner. For example, Vehicle Wear Determination System109may receive acceleration or motion information (e.g., as collected by one or more accelerometers of UE107) indicating relatively high lateral forces, and may receive road/route information (e.g., as provided by Navigation/Information Source105) indicating that vehicle101is traveling on relatively windy roads while such forces are being measured by UE107. If vehicle101routinely exhibits such behaviors, this may indicate that tires of vehicle101are experiencing greater rates of wear than tires of vehicles that are driven in a different manner (e.g., with lower lateral forces, on straighter roads, etc.).

As still another example, Vehicle Wear Determination System109may receive sensor data (e.g., as measured or collected by UE107) and road/route information (e.g., from Navigation/Information Source105), based on which Vehicle Wear Determination System109may determine that vehicle101has impacted obstacles, potholes, or other objects while traveling along a road. For example, accelerometer and/or impact detection information (e.g., as measured and/or determined by UE107) may indicate one or more impacts at a particular time. Location information associated with UE107may indicate that vehicle101was located on a particular road or at a particular location at the same time. Further, road/route information may indicate that the particular road or location is associated with a construction zone, that debris or objects on the road have been reported, and/or that other road conditions are present on the particular road or at the particular location. In such an instance, Vehicle Wear Determination System109may determine that vehicle101has experienced a relatively high amount of wear to suspension components of vehicle101(e.g., shocks, struts, etc.).

As yet another example, Vehicle Wear Determination System109may receive vehicle information (e.g., via vehicle OBD port201) and sensor data (e.g., as measured or collected by UE107), based on which Vehicle Wear Determination System109may determine that vehicle101has traveled on dirt or gravel roads, and therefore has experienced extra levels of wear by virtue of such events. For example, vehicle information may indicate that vehicle101has issued a lane departure warning (e.g., in the event that vehicle101is equipped with sensors or other devices that are able to detect and report when vehicle101has veered out of a lane or has otherwise departed the lane, such as without signaling) at a particular time. Sensor data collected by UE107may indicate that impacts, bumps, etc. were detected at the particular time as well. Based on these pieces of information, Vehicle Wear Determination System109may infer or determine that vehicle101has veered out of a lane, potentially inadvertently, and has traveled on an unpaved or rough road. Further, Vehicle Wear Determination System109may accordingly determine that tires, paint, etc. of vehicle101have experienced an excess level of wear based on such an occurrence.

In order to make such determinations as to types or degree of wear that vehicle101is experiencing, Vehicle Wear Determination System109may compare information associated with vehicle101(e.g., vehicle information received from vehicle101via vehicle OBD port201, sensor data collected or measured by UE107, and/or road/route information received from Navigation/Information Source105) to one or more models that associate such information with wear categories, classifications, etc.

As shown inFIG.3, for example, Vehicle Wear Determination System109may maintain one or more wear models301(e.g., vehicle wear models301-1,301-2,301-N, etc.). In some embodiments, each vehicle wear model301may be associated with a different make, model, type, or other attribute of vehicle101. For example, a first vehicle of a first make and model may be associated with a first vehicle wear model301-1, while a second vehicle of a second make and model may be associated with a second vehicle wear model301-2. In some embodiments, different criteria or attributes may be used for different vehicle wear models301, such as temporal criteria (e.g., time of day, day of week, season, etc.), driver criteria (e.g., driver age, quantity of past traffic accidents, or other driver attributes), location-based criteria (e.g., different vehicle wear models301may be associated with different cities or states, different types of locations such as urban or suburban, etc.), and/or other suitable criteria.

Each vehicle wear model301may, in some embodiments, include a set of vehicle wear information303, vehicle wear classifications305, and actions/recommendations307. Vehicle wear input information303for a given vehicle wear model301may be considered “inputs” to vehicle wear model301, while vehicle wear classifications305and/or actions/recommendations307may be considered “outputs” of vehicle wear model301. That is, Vehicle Wear Determination System109may generate or identify one or more vehicle wear classifications305and/or actions/recommendations307based on vehicle wear input information303received from UE107and/or some other source. Vehicle wear input information303may, for example, receive training information, feedback information, and/or other suitable information based on which vehicle wear input information303may automatically, iteratively, and/or otherwise associate particular sets of vehicle wear input information303with particular vehicle wear classifications305and/or actions/recommendations307. For example, vehicle wear input information303may utilize AI/ML techniques or other suitable techniques to associate particular sets of vehicle wear input information303with particular vehicle wear classifications305and/or actions/recommendations307.

In this manner, since different vehicle wear models301may be associated with different criteria (e.g., different makes and/or models of cars, different driver profiles, different times, different locations, etc.), the same or similar set of inputs (e.g., vehicle wear input information303) may yield different outputs (e.g., vehicle wear classifications305and/or307). As one example, assume that a first vehicle wear model301-1is associated with a pickup truck, while a second vehicle wear model301-2is associated with a sports coupe. Similar inputs, such as inputs indicating impacts with obstacles, potholes, etc. on the same stretch of road may have different effects on the determination of wear on such vehicles. For example, vehicle wear model301-1, associated with the pickup truck, may indicate that such impacts have a minimal or no effect on vehicle wear of the pickup truck, whereas vehicle wear model301-2, associated with the sports coupe, may indicate that such impacts have a substantial effect on vehicle wear of the sports coupe.

Examples of different vehicle wear input information303are provided inFIG.3, and are discussed above. In practice, vehicle wear input information303may include different information elements, additional information elements, and/or fewer information elements. Further, in some embodiments, different vehicle wear models301may include different information elements than each other (e.g., not all vehicles may be equipped with lane departure sensing devices, etc.).

The training, refining, etc. of a given vehicle wear model301may include associating different sets of values associated with different information elements of vehicle wear input information303with different vehicle wear classifications305and/or actions/recommendations307. For example, a first set of values of acceleration, mileage, and turning forces for a given vehicle wear model301may be associated with a first vehicle wear classification305(e.g., “standard wear”), while a second set of values of acceleration, mileage, and turning forces (e.g., higher acceleration, higher mileage, higher turning forces, etc.) for the same vehicle wear model301may be associated with a second vehicle wear classification305(e.g., “high wear”). Further, as noted above, particular sets of values of vehicle wear input information303may be associated with different types of vehicle wear classifications305. For example, relatively high values for turning forces (e.g., an information element of vehicle wear input information303) may be associated with a “high tire wear” vehicle wear classification305. In some embodiments, one set of values for vehicle wear input information303may be associated with multiple vehicle wear classifications305(e.g., may be associated with a “high tire wear” and “high alignment wear” classification).

In some embodiments, different actions/recommendations307may be associated with different vehicle wear classifications305. For example, a given vehicle101for which a “standard wear” vehicle wear classification305has been determined may be associated with a “normal service intervals” action/recommendation307. For example, vehicle101may be associated with a default or standard service interval (e.g., every 5,000 miles, every 20,000 miles, every year, etc.), and certain vehicle wear classifications305may indicate that no change should be recommended. On the other hand, vehicles that are driven harder or in more adverse conditions (e.g., associated with a “high wear,” “high electrical system wear,” “high alignment wear,” etc. vehicle wear classification305) may be associated with more frequent service intervals (e.g., “1.5× shorter service intervals,” “2.0× shorter service intervals,” etc.). As another example, a given vehicle101that is associated with a “high tire wear” vehicle wear classification305may be associated with a “re-balance tires” action/recommendation307.

In this manner, Vehicle Wear Determination System109may collect a holistic view of vehicle101from multiple different sources, including from vehicle101itself, one or more UEs107that are located within vehicle101while vehicle101is operating, one or more remote sources (e.g., Navigation/Information Source105), etc. Vehicle Wear Determination System109may, based on information from all of these sources in addition to models refined using AI/ML techniques (e.g., which may be refined based on “crowdsourced” real-world data and feedback and/or simulations), identify particular types of wear on vehicle101as well as actions that may be taken to remedy or preemptively prevent issues due to the identified types of wear. As such, an unprecedented level of insight may be provided as to how to maintain a vehicle, as well as how to determine whether a vehicle has been subjected to excessive wear and may therefore be devalued and/or in need of maintenance or repair. Further, based on vehicle wear classifications305and/or actions/recommendations307determined by Vehicle Wear Determination System109, Vehicle Wear Determination System109may generate or determine real-time metrics relating to wear, based on which a vehicle owner or other entity may be able to perform or schedule maintenance, adjust driving habits, or otherwise mitigate wear that vehicle101has been subjected to.

FIG.4illustrates an example graphical user interface (“GUI”)401that may be presented to a user (e.g., via an application executing on UE107and/or on some other suitable device) based on operations described above. For example, Vehicle Wear Determination System109may provide some or all of the information shown inFIG.4, and/or UE107may receive portions of such information from other sources (e.g., from vehicle101via vehicle OBD port201and/or OBD monitor103). For example, GUI401may include a current mileage of vehicle101, an oil life indicator, a tire life indicator, and a recommendation of a next service for vehicle101. In some embodiments, as noted above, metrics such as oil life and tire life may be determined based on vehicle wear input information303(and/or vehicle wear classifications305determined based on vehicle wear input information303) associated with vehicle101. For example, that oil or engine wear of vehicle101is within a normal or default set of parameters (e.g., few or no redlines, a relatively nominal or minimal amount of stop and go traffic, etc.), and therefore may calculate the oil life as a function of mileage according to such default set of parameters. Further, Vehicle Wear Determination System109may provide, via GUI401, an indication that the wear on the oil or engine of vehicle101is “normal,” which may be based on a particular vehicle wear classification305determined based on vehicle wear input information303associated with vehicle101.

As another example, GUI401may indicate a tire life of vehicle101, which may be based on one or more vehicle wear classifications305determined based on vehicle wear input information303(e.g., a “low tire wear” vehicle wear classification305) and may further be a function of the mileage driven. That is, even if a relatively high number of miles have been driven, the tire life may remain relatively high if wear is relatively low. For example, vehicle wear input information303may indicate relatively low turning forces, relatively few turns, driving on well-paved roads, etc., based on which Vehicle Wear Determination System109may determine that the tire wear of vehicle101is relatively low. Vehicle Wear Determination System109may accordingly indicate, via GUI401, that relatively lower tire wear has been detected (e.g., as compared to a particular vehicle wear model301associated with the same vehicle101). In other words, vehicle wear model301may, for example, indicate that most other vehicles101of the same make and model experience more tire wear than the particular vehicle101to which GUI401pertains.

GUI401may also include an indication that a next recommended service is at 22,000 miles (e.g., in approximately 10,000 more miles). This indication may be based on, for example, a determined action/recommendation307indicating a lesser service interval due to a relatively lower amount of wear associated with vehicle101. In this manner, an owner of vehicle101may be able to save time and/or other resources by virtue of delaying the service interval of vehicle101, without negatively impacting the operation of vehicle101.

FIG.5illustrates another example GUI501that may be presented by Vehicle Wear Determination System109based on vehicle wear input information303associated with another vehicle101. In this example, Vehicle Wear Determination System109may have detected excessive engine wear and tire wear based on driving habits of vehicle101(e.g., as indicated by vehicle wear input information303). In this example, Vehicle Wear Determination System109may have also determined that a battery life of vehicle101is relatively low, as a function of time and/or mileage, voltages reported via vehicle OBD port201, comfort accessory usage reported by vehicle OBD port201(e.g., use of radio, climate controls, etc. while an engine of vehicle101is off), and/or other criteria. GUI501may further indicate multiple actions/recommendations307determined based on the above information. For example, Vehicle Wear Determination System109may gave determined that a 100,000 mile service should be performed early, that tires should be changed, and that the battery of vehicle101should be replaced (e.g., in the event that the 100,000 mile service does not already include a tire change and battery replacement).

FIG.6illustrates an example process600for using one or more models to determine a measure of vehicle wear based on vehicle information and/or other types of information. In some embodiments, some or all of process600may be performed by Vehicle Wear Determination System109. In some embodiments, one or more other devices may perform some or all of process600in concert with, and/or in lieu of, Vehicle Wear Determination System109.

As shown, process600may include generating and/or refining (at602) a set of vehicle wear models301. For example, as discussed above, Vehicle Wear Determination System109may receive training data, feedback data (e.g., indicating whether respective determined vehicle wear classifications305and/or actions/recommendations307were correct or incorrect), and/or other suitable information based on which Vehicle Wear Determination System109and/or some other device or system may generate or refine such vehicle wear models301using AI/ML techniques or other suitable techniques. As discussed above, vehicle wear models301may associate respective sets of vehicle wear input information303(e.g., different values for different information elements of vehicle wear input information303) with different vehicle wear classifications305and/or actions/recommendations307.

Process600may further include receiving (at604) a set of vehicle wear input information303associated with a particular vehicle101. For example, as discussed above, vehicle wear input information303may be received from a particular UE107or other suitable source. Vehicle wear input information303may include sensor data collected or measured by UE107(e.g., while UE107has determined that UE107is within vehicle101and/or that vehicle101is in operational status), vehicle information provided by vehicle101(e.g., telematics, diagnostics, log information, etc.) via vehicle OBD port201or some other suitable interface, and/or some other source (e.g., Navigation/Information Source105or some other device or system). As discussed above, vehicle wear input information303may include raw data, processed and/or classified data (e.g., detected events such as impacts, heavy traffic, construction zones, hard turning, etc.), and/or other suitable information. The received information may include timestamps and/or other suitable key information based on which Vehicle Wear Determination System109may “stitch” together information from different sources in order to gain a holistic view of events, attributes, etc. that may affect wear and tear on vehicle101. For example, based on information from multiple sources (e.g., from UE107and vehicle101, from UE107and Navigation/Information Source105, from Navigation/Information Source105and vehicle101, etc.), Vehicle Wear Determination System109may identify one or more events or occurrences (e.g., an impact, a traffic slowdown, etc.), and/or may identify such events or occurrences with a higher confidence level than if such information was received from only one source.

Process600may additionally include comparing (at606) the received vehicle wear input information303to some or all of the vehicle wear models301. For example, Vehicle Wear Determination System109may select a particular vehicle wear model301(and/or one or more vehicle wear models301) that pertain to the received vehicle wear input information303, such as a particular vehicle wear model301that is associated with a same vehicle type (e.g., make, model, classification, etc.) as vehicle101, that is associated with a same timeframe as vehicle wear input information303(e.g., same day of week, same time of day, etc.), that is associated with a same driver profile or type (e.g., where vehicle101may be associated with a particular driver or driver profile), and/or is otherwise associated with vehicle wear input information303and/or vehicle101. Vehicle Wear Determination System109may analyze particular values of the received vehicle wear input information303to identify the same or similar values (e.g., “matching” values) of vehicle wear model301.

Process600may also include determining (at608), based on the comparing, vehicle wear classifications305and/or actions/recommendations307. For example, Vehicle Wear Determination System109may identify, based on comparing particular values of vehicle wear input information303to particular values of vehicle wear model301, which particular vehicle wear classifications305and/or actions/recommendations307are associated with the received vehicle wear input information303. For example, as discussed above, vehicle wear model301may associate particular sets of values of vehicle wear input information303to particular vehicle wear classifications305and/or actions/recommendations307, of which Vehicle Wear Determination System109may identify or select one or more particular vehicle wear classifications305and/or actions/recommendations307that are associated with the received vehicle wear input information303associated with vehicle101. As discussed above, the actions may include recommendations and/or other information indicating maintenance, repairs, etc. Additionally, or alternatively, the actions may include providing alerts, reports, etc. regarding particular types of determined vehicle wear and/or a degree to which wear on vehicle101has been identified.

Process600may further include outputting (at610) information associated with vehicle wear classifications305and/or actions/recommendations307. For example, Vehicle Wear Determination System109may output such information to UE107, from which some or all of vehicle wear input information303associated with vehicle101was received. UE107may present such information in a user interface (e.g., GUI401, GUI501, etc.). As such, a user of UE107(e.g., an owner or driver of vehicle101and/or some other suitable entity) may gain insight as to how worn vehicle101is, as compared to a “normal” or “average” level of wear. Further such user may be able to perform maintenance or repairs that the user would have otherwise not been aware of. Additionally, such user may avoid performing excessive maintenance or repairs in situations where lower than expected wear on vehicle101has occurred.

FIG.7illustrates an example environment700, in which one or more embodiments may be implemented. In some embodiments, environment700may correspond to a Fifth Generation (“5G”) network, and/or may include elements of a 5G network. In some embodiments, environment700may correspond to a 5G Non-Standalone (“NSA”) architecture, in which a 5G radio access technology (“RAT”) may be used in conjunction with one or more other RATs (e.g., a Long-Term Evolution (“LTE”) RAT), and/or in which elements of a 5G core network may be implemented by, may be communicatively coupled with, and/or may include elements of another type of core network (e.g., an evolved packet core (“EPC”)). In some embodiments, portions of environment700may represent or may include a 5G core (“5GC”). As shown, environment700may include UE701, RAN710(which may include one or more Next Generation Node Bs (“gNBs”)711), RAN712(which may include one or more evolved Node Bs (“eNBs”)713), and various network functions such as Access and Mobility Management Function (“AMF”)715, Mobility Management Entity (“MME”)716, Serving Gateway (“SGW”)717, Session Management Function (“SMF”)/Packet Data Network (“PDN”) Gateway (“PGW”)-Control plane function (“PGW-C”)720, Policy Control Function (“PCF”)/Policy Charging and Rules Function (“PCRF”)725, Application Function (“AF”)730, User Plane Function (“UPF”)/PGW-User plane function (“PGW-U”)735, Unified Data Management (“UDM”)/Home Subscriber Server (“HSS”)740, and Authentication Server Function (“AUSF”)745. Environment700may also include one or more networks, such as Data Network (“DN”)750. Environment700may include one or more additional devices or systems communicatively coupled to one or more networks (e.g., DN750), such as Navigation/Information Source105, Vehicle Wear Determination System109, and/or one or more other devices or systems.

The example shown inFIG.7illustrates one instance of each network component or function (e.g., one instance of SMF/PGW-C720, PCF/PCRF725, UPF/PGW-U735, UDM/HSS740, and/or AUSF745). In practice, environment700may include multiple instances of such components or functions. For example, in some embodiments, environment700may include multiple “slices” of a core network, where each slice includes a discrete and/or logical set of network functions (e.g., one slice may include a first instance of SMF/PGW-C720, PCF/PCRF725, UPF/PGW-U735, UDM/HSS740, and/or AUSF745, while another slice may include a second instance of SMF/PGW-C720, PCF/PCRF725, UPF/PGW-U735, UDM/HSS740, and/or AUSF745). The different slices may provide differentiated levels of service, such as service in accordance with different Quality of Service (“QoS”) parameters.

The quantity of devices and/or networks, illustrated inFIG.7, is provided for explanatory purposes only. In practice, environment700may include additional devices and/or networks, fewer devices and/or networks, different devices and/or networks, or differently arranged devices and/or networks than illustrated inFIG.7. For example, while not shown, environment700may include devices that facilitate or enable communication between various components shown in environment700, such as routers, modems, gateways, switches, hubs, etc. In some implementations, one or more devices of environment700may be physically integrated in, and/or may be physically attached to, one or more other devices of environment700. Alternatively, or additionally, one or more of the devices of environment700may perform one or more network functions described as being performed by another one or more of the devices of environment700.

Elements of environment700may interconnect with each other and/or other devices via wired connections, wireless connections, or a combination of wired and wireless connections. Examples of interfaces or communication pathways between the elements of environment700, as shown inFIG.7, may include an N1 interface, an N2 interface, an N3 interface, an N4 interface, an N5 interface, an N6 interface, an N7 interface, an N8 interface, an N9 interface, an N10 interface, an N11 interface, an N12 interface, an N13 interface, an N14 interface, an N2 interface, an N26 interface, an S1-C interface, an S1-U interface, an S5-C interface, an S5-U interface, an S6a interface, an S11 interface, and/or one or more other interfaces. Such interfaces may include interfaces not explicitly shown inFIG.7, such as Service-Based Interfaces (“SBIs”), including an Namf interface, an Nudm interface, an Npcf interface, an Nupf interface, an Nnef interface, an Nsmf interface, and/or one or more other SBIs. In some embodiments, environment700may be, may include, may be implemented by, and/or may be communicatively coupled to network203.

UE701may include a computation and communication device, such as a wireless mobile communication device that is capable of communicating with RAN710, RAN712, and/or DN750. UE701may be, or may include, a radiotelephone, a personal communications system (“PCS”) terminal (e.g., a device that combines a cellular radiotelephone with data processing and data communications capabilities), a personal digital assistant (“PDA”) (e.g., a device that may include a radiotelephone, a pager, Internet/intranet access, etc.), a smart phone, a laptop computer, a tablet computer, a camera, a personal gaming system, an Internet of Things (“IoT”) device (e.g., a sensor, a smart home appliance, a wearable device, a Machine-to-Machine (“M2M”) device, or the like), or another type of mobile computation and communication device. UE701may send traffic to and/or receive traffic (e.g., user plane traffic) from DN750via RAN710, RAN712, and/or UPF/PGW-U735.

RAN710may be, or may include, a 5G RAN that includes one or more base stations (e.g., one or more gNBs711), via which UE701may communicate with one or more other elements of environment700. UE701may communicate with RAN710via an air interface (e.g., as provided by gNB711). For instance, RAN710may receive traffic (e.g., user plane traffic such as voice call traffic, data traffic, messaging traffic, etc.) from UE701via the air interface, and may communicate the traffic to UPF/PGW-U735and/or one or more other devices or networks. Further, RAN710may receive signaling traffic, control plane traffic, etc. from UE701via the air interface, and may communicate such signaling traffic, control plane traffic, etc. to AMF715and/or one or more other devices or networks. Additionally, RAN710may receive traffic intended for UE701(e.g., from UPF/PGW-U735, AMF715, and/or one or more other devices or networks) and may communicate the traffic to UE701via the air interface.

RAN712may be, or may include, a LTE RAN that includes one or more base stations (e.g., one or more eNBs713), via which UE701may communicate with one or more other elements of environment700. UE701may communicate with RAN712via an air interface (e.g., as provided by eNB713). For instance, RAN712may receive traffic (e.g., user plane traffic such as voice call traffic, data traffic, messaging traffic, signaling traffic, etc.) from UE701via the air interface, and may communicate the traffic to UPF/PGW-U735(e.g., via SGW717) and/or one or more other devices or networks. Further, RAN712may receive signaling traffic, control plane traffic, etc. from UE701via the air interface, and may communicate such signaling traffic, control plane traffic, etc. to MME716and/or one or more other devices or networks. Additionally, RAN712may receive traffic intended for UE701(e.g., from UPF/PGW-U735, MME716, SGW717, and/or one or more other devices or networks) and may communicate the traffic to UE701via the air interface.

AMF715may include one or more devices, systems, Virtualized Network Functions (“VNFs”), Cloud-Native Network Functions (“CNFs”), etc., that perform operations to register UE701with the 5G network, to establish bearer channels associated with a session with UE701, to hand off UE701from the 5G network to another network, to hand off UE701from the other network to the 5G network, manage mobility of UE701between RANs710and/or gNBs711, and/or to perform other operations. In some embodiments, the 5G network may include multiple AMFs715, which communicate with each other via the N14 interface (denoted inFIG.7by the line marked “N14” originating and terminating at AMF715).

MME716may include one or more devices, systems, VNFs, CNFs, etc., that perform operations to register UE701with the EPC, to establish bearer channels associated with a session with UE701, to hand off UE701from the EPC to another network, to hand off UE701from another network to the EPC, manage mobility of UE701between RANs712and/or eNBs713, and/or to perform other operations.

SGW717may include one or more devices, systems, VNFs, CNFs, etc., that aggregate traffic received from one or more eNBs713and send the aggregated traffic to an external network or device via UPF/PGW-U735. Additionally, SGW717may aggregate traffic received from one or more UPF/PGW-Us735and may send the aggregated traffic to one or more eNBs713. SGW717may operate as an anchor for the user plane during inter-eNB handovers and as an anchor for mobility between different telecommunication networks or RANs (e.g., RANs710and712).

SMF/PGW-C720may include one or more devices, systems, VNFs, CNFs, etc., that gather, process, store, and/or provide information in a manner described herein. SMF/PGW-C720may, for example, facilitate the establishment of communication sessions on behalf of UE701. In some embodiments, the establishment of communications sessions may be performed in accordance with one or more policies provided by PCF/PCRF725.

PCF/PCRF725may include one or more devices, systems, VNFs, CNFs, etc., that aggregate information to and from the 5G network and/or other sources. PCF/PCRF725may receive information regarding policies and/or subscriptions from one or more sources, such as subscriber databases and/or from one or more users (such as, for example, an administrator associated with PCF/PCRF725).

AF730may include one or more devices, systems, VNFs, CNFs, etc., that receive, store, and/or provide information that may be used in determining parameters (e.g., quality of service parameters, charging parameters, or the like) for certain applications.

UPF/PGW-U735may include one or more devices, systems, VNFs, CNFs, etc., that receive, store, and/or provide data (e.g., user plane data). For example, UPF/PGW-U735may receive user plane data (e.g., voice call traffic, data traffic, etc.), destined for UE701, from DN750, and may forward the user plane data toward UE701(e.g., via RAN710, SMF/PGW-C720, and/or one or more other devices). In some embodiments, multiple UPFs735may be deployed (e.g., in different geographical locations), and the delivery of content to UE701may be coordinated via the N9 interface (e.g., as denoted inFIG.7by the line marked “N9” originating and terminating at UPF/PGW-U735). Similarly, UPF/PGW-U735may receive traffic from UE701(e.g., via RAN710, RAN712, SMF/PGW-C720, and/or one or more other devices), and may forward the traffic toward DN750. In some embodiments, UPF/PGW-U735may communicate (e.g., via the N4 interface) with SMF/PGW-C720, regarding user plane data processed by UPF/PGW-U735.

UDM/HSS740and AUSF745may include one or more devices, systems, VNFs, CNFs, etc., that manage, update, and/or store, in one or more memory devices associated with AUSF745and/or UDM/HSS740, profile information associated with a subscriber. AUSF745and/or UDM/HSS740may perform authentication, authorization, and/or accounting operations associated with the subscriber and/or a communication session with UE701.

DN750may include one or more wired and/or wireless networks. For example, DN750may include an Internet Protocol (“IP”)-based PDN, a wide area network (“WAN”) such as the Internet, a private enterprise network, and/or one or more other networks. UE701may communicate, through DN750, with data servers, other UEs701, and/or to other servers or applications that are coupled to DN750. DN750may be connected to one or more other networks, such as a public switched telephone network (“PSTN”), a public land mobile network (“PLMN”), and/or another network. DN750may be connected to one or more devices, such as content providers, applications, web servers, and/or other devices, with which UE701may communicate.

FIG.8illustrates an example RAN environment800, which may be included in and/or implemented by one or more RANs (e.g., RAN710, RAN712, or some other RAN). In some embodiments, a particular RAN may include one RAN environment800. In some embodiments, a particular RAN may include multiple RAN environments800. In some embodiments, RAN environment800may correspond to a particular gNB711of a 5G RAN (e.g., RAN710). In some embodiments, RAN environment800may correspond to multiple gNBs711. In some embodiments, RAN environment800may correspond to one or more other types of base stations of one or more other types of RANs. As shown, RAN environment800may include Central Unit (“CU”)805, one or more Distributed Units (“DUs”)803-1through803-N (referred to individually as “DU803,” or collectively as “DUs803”), and one or more Radio Units (“RUs”)801-1through801-M (referred to individually as “RU801,” or collectively as “RUs801”).

CU805may communicate with a core of a wireless network (e.g., may communicate with one or more of the devices or systems described above with respect toFIG.7, such as AMF715and/or UPF/PGW-U735). In the uplink direction (e.g., for traffic from UEs701to a core network), CU805may aggregate traffic from DUs803, and forward the aggregated traffic to the core network. In some embodiments, CU805may receive traffic according to a given protocol (e.g., Radio Link Control (“RLC”)) from DUs803, and may perform higher-layer processing (e.g., may aggregate/process RLC packets and generate Packet Data Convergence Protocol (“PDCP”) packets based on the RLC packets) on the traffic received from DUs803.

In accordance with some embodiments, CU805may receive downlink traffic (e.g., traffic from the core network) for a particular UE701, and may determine which DU(s)803should receive the downlink traffic. DU803may include one or more devices that transmit traffic between a core network (e.g., via CU805) and UE701(e.g., via a respective RU801). DU803may, for example, receive traffic from RU801at a first layer (e.g., physical (“PHY”) layer traffic, or lower PHY layer traffic), and may process/aggregate the traffic to a second layer (e.g., upper PHY and/or RLC). DU803may receive traffic from CU805at the second layer, may process the traffic to the first layer, and provide the processed traffic to a respective RU801for transmission to UE701.

RU801may include hardware circuitry (e.g., one or more RF transceivers, antennas, radios, and/or other suitable hardware) to communicate wirelessly (e.g., via an RF interface) with one or more UEs701, one or more other DUs803(e.g., via RUs801associated with DUs803), and/or any other suitable type of device. In the uplink direction, RU801may receive traffic from UE701and/or another DU803via the RF interface and may provide the traffic to DU803. In the downlink direction, RU801may receive traffic from DU803, and may provide the traffic to UE701and/or another DU803.

One or more elements of RAN environment800may, in some embodiments, be communicatively coupled to one or more Multi-Access/Mobile Edge Computing (“MEC”) devices, referred to sometimes herein simply as “MECs”807. For example, DU803-1may be communicatively coupled to MEC807-1, DU803-N may be communicatively coupled to MEC807-N, CU805may be communicatively coupled to MEC807-2, and so on. MECs807may include hardware resources (e.g., configurable or provisionable hardware resources) that may be configured to provide services and/or otherwise process traffic to and/or from UE701, via a respective RU801.

For example, DU803-1may route some traffic, from UE701, to MEC807-1instead of to a core network via CU805. MEC807-1may process the traffic, perform one or more computations based on the received traffic, and may provide traffic to UE701via RU801-1. In some embodiments, MEC807may include, and/or may implement, some or all of the functionality described above with respect to Navigation/Information Source105, Vehicle Wear Determination System109, AF730, UPF735, and/or one or more other devices, systems, VNFs, CNFs, etc. In this manner, ultra-low latency services may be provided to UE701, as traffic does not need to traverse DU803, CU805, links between DU803and CU805, and an intervening backhaul network between RAN environment800and the core network.

FIG.9illustrates example components of device900. One or more of the devices described above may include one or more devices900. Device900may include bus910, processor920, memory930, input component940, output component950, and communication interface960. In another implementation, device900may include additional, fewer, different, or differently arranged components.

Bus910may include one or more communication paths that permit communication among the components of device900. Processor920may include a processor, microprocessor, or processing logic that may interpret and execute instructions. In some embodiments, processor920may be or may include one or more hardware processors. Memory930may include any type of dynamic storage device that may store information and instructions for execution by processor920, and/or any type of non-volatile storage device that may store information for use by processor920.

Input component940may include a mechanism that permits an operator to input information to device900and/or other receives or detects input from a source external to input component940, such as a touchpad, a touchscreen, a keyboard, a keypad, a button, a switch, a microphone or other audio input component, etc. In some embodiments, input component940may include, or may be communicatively coupled to, one or more sensors, such as a motion sensor (e.g., which may be or may include a gyroscope, accelerometer, or the like), a location sensor (e.g., a Global Positioning System (“GPS”)-based location sensor or some other suitable type of location sensor or location determination component), a thermometer, a barometer, and/or some other type of sensor. Output component950may include a mechanism that outputs information to the operator, such as a display, a speaker, one or more light emitting diodes (“LEDs”), etc.

Communication interface960may include any transceiver-like mechanism that enables device900to communicate with other devices and/or systems. For example, communication interface960may include an Ethernet interface, an optical interface, a coaxial interface, or the like. Communication interface960may include a wireless communication device, such as an infrared (“IR”) receiver, a Bluetooth® radio, or the like. The wireless communication device may be coupled to an external device, such as a remote control, a wireless keyboard, a mobile telephone, etc. In some embodiments, device900may include more than one communication interface960. For instance, device900may include an optical interface and an Ethernet interface.