Apparatus and method for providing information indicating the level of pollution generated by vehicle

Abstract

Aspects relate to a method for providing information indicative of a level of contamination generated by vehicle tire wear to a vehicle, the method comprising, for each of at least some of a plurality of geographic locations, obtaining information indicative of vehicle tire wear at the geographic location, the vehicle wear is derived from vehicle sensor data from one or more vehicles; determining, for each of the plurality of geographic locations, pollution data, the pollution data including information derived from the acquired information indicative of vehicle tire wear at the geographic location indicative of a pollution level generated by vehicle tire wear; and in response to a request of the vehicle for information indicative of a pollution level generated by the vehicle by tire wear for the geographic location at which the vehicle is located, providing information indicative of the pollution level generated by the vehicle tire wear determined for the geographic location at which the vehicle is located.

Description

Technical Field

[0001] Various aspects of the present disclosure are directed to apparatus and methods for providing information to a vehicle indicative of contamination levels generated by wear of the vehicle's tires. Background Art

[0002] For vehicles, it may be desirable to have information about air pollution, e.g. for controlling the cabin air system. While there are air quality stations that can provide such kind of information, that information may not cover every location, at least not for all types of pollution. For example, a specific (local) measuring station may only provide information about the current (local) pollution state with respect to defined parameters (such as PM10), which may specifically exclude smaller particles caused, e.g. by vehicle tire wear.

[0003]

[0006] Therefore, what is desired is an efficient and accurate method for providing a vehicle with information indicative of the level of contamination generated by wear of the vehicle's tires. Summary of the invention

[0004] Various embodiments relate to a method for providing information indicating pollution levels generated by vehicle tire wear to a vehicle, the method comprising: for each of at least some of a plurality of geographic locations, obtaining information indicating vehicle tire wear at the geographic location, the vehicle wear being derived from vehicle sensor data from one or more vehicles; for each of the plurality of geographic locations, determining pollution data, the pollution data comprising information indicating (e.g., relating to or based on) pollution levels generated by vehicle tire wear at the geographic location derived from the obtained information indicating vehicle tire wear; and in response to a request by a vehicle (i.e., a requester or a requesting vehicle, e.g., a requesting component of a requester or a vehicle) for information indicating pollution levels generated by vehicle tire wear for the geographic location at which the vehicle is located, providing information indicating pollution levels generated by vehicle tire wear determined (e.g., calculated and / or stored) for the geographic location at which the vehicle is located.

[0005] According to one embodiment, the method further includes receiving a transmission of information indicating vehicle tire wear at a geographic location at which a corresponding vehicle in the one or more vehicles is located from each vehicle of the one or more vehicles (e.g., at a database system executing the method).

[0006] According to one embodiment, the transmission comprises an indication of a geographical location at which a respective vehicle of the one or more vehicles is located.

[0007] According to one embodiment, the pollution data is stored in said one or more vehicle-external (and / or vehicle-external) databases.

[0008] According to one embodiment, the method further comprises receiving the request and providing, via radio communication, information indicative of a pollution level generated by wear of the vehicle's tires.

[0009] According to one embodiment, the method further comprises obtaining information indicative of vehicle tire wear for a plurality of weather conditions, and determining pollution data comprising information indicative of pollution levels generated by vehicle tire wear for each of the plurality of weather conditions.

[0010] According to one embodiment, the request indicates at least one of the plurality of weather conditions and the method comprises providing information about a pollution level generated by the vehicle through tire wear at a geographical location at which the vehicle is located determined for the indicated weather condition.

[0011] According to one embodiment, the geographical location at which the vehicle is located is a road or a road segment.

[0012] According to one embodiment, the information indicative of the pollution level generated by vehicle tyre wear comprises information indicative of the condition of the road or road segment.

[0013] According to one embodiment, the information indicative of the pollution level generated by vehicle tyre wear comprises an estimate of the coefficient of friction between the vehicle's tyres and the road or road segment.

[0014] According to one embodiment, a database system is provided, the database system comprising at least one processor configured to: for each of at least some of a plurality of geographic locations, obtain information indicating vehicle tire wear at the geographic location, the vehicle wear being derived from vehicle sensor data from one or more vehicles; for each of the plurality of geographic locations, determine pollution data, the pollution data comprising information indicating (e.g., relating to or based on) a pollution level generated by vehicle tire wear at the geographic location derived from the obtained information indicating vehicle tire wear; and in response to a request from a vehicle (i.e., a requester or a requesting vehicle, e.g., a requesting component of a requester or a vehicle) for information indicating a pollution level generated by tire wear of the vehicle for the geographic location at which the vehicle is located, provide information indicating a pollution level generated by vehicle tire wear determined (e.g., calculated and / or stored) for the geographic location at which the vehicle is located.

[0015] According to one embodiment, a method for controlling a pollution control system of a vehicle is provided, the method comprising acquiring information indicative of a pollution level generated by the vehicle through tire wear, determining operating parameter values ​​of the vehicle's pollution control system depending on the acquired information, and controlling the vehicle's pollution control system according to the determined operating parameter values.

[0016] According to one embodiment, the method comprises acquiring, from a database external to the vehicle, information indicative of a pollution level generated by the vehicle through tyre wear.

[0017] According to one embodiment, the method comprises acquiring, via radio communication, from a database information indicative of a pollution level generated by the vehicle through tyre wear.

[0018] According to one embodiment, the method comprises obtaining from a database information indicative of a pollution level generated by the vehicle through tire wear by sending from the vehicle to the database a request indicative of the vehicle's position, weather conditions in which the vehicle is exposed, or both.

[0019] According to one embodiment, the information indicative of the pollution level generated by the vehicle through tyre wear comprises information indicative of the conditions of the road on which the vehicle is located.

[0020] According to one embodiment, the information indicative of the level of pollution generated by the vehicle through tyre wear comprises an estimate of the coefficient of friction between the tyres of the vehicle and the road on which the vehicle is located.

[0021] According to one embodiment, the information indicative of the pollution level generated by the vehicle through tyre wear is at least partly derived from sensor data provided by vehicle sensors.

[0022] According to one embodiment, the pollution control system of the vehicle is a cabin air system.

[0023] According to one embodiment, the method includes estimating a concentration of pollutant particles caused by tire wear of the vehicle from the acquired information, and determining operating parameters of a cabin air system to reduce the concentration of pollutant particles caused by tire wear of the vehicle in the cabin of the vehicle if the estimated concentration of pollutant particles caused by tire wear of the vehicle is above a predetermined threshold.

[0024] According to one embodiment, the pollution control system of the vehicle is a vehicle navigation system that takes into account air pollution. For example, pollution control may include selecting a suitable route by optimizing time, distance, energy, and / or pollution levels encountered during the journey. More than one of these parameters may be optimized as a combination with different weights for each parameter, for example as selected by the user.

[0025] According to one embodiment, a vehicle controller is provided, the vehicle controller comprising at least one processor configured to acquire information indicative of a pollution level generated by the vehicle through tire wear, determine operating parameter values ​​of a pollution control system of the vehicle depending on the acquired information, and control the pollution control system of the vehicle according to the determined operating parameters.

[0026] According to one embodiment, a computer program element is provided comprising program instructions which, when executed by one or more processors, cause the one or more processors to perform the method of any one of the embodiments described above.

[0027] According to one embodiment, a computer readable medium including program instructions is provided. When executed by one or more processors, the program instructions cause the one or more processors to perform the method of any one of the above-described embodiments.

[0028] It should be noted that embodiments described in the context of one of the methods are analogously valid for the apparatus (ie, database system and vehicle controller), and vice versa. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The present disclosure will be better understood with reference to the detailed description when considered in conjunction with the non-limiting examples and the accompanying drawings, in which:

[0030] - Figure 1 A vehicle having a cabin air system is shown;

[0031] - Figure 2 Illustration of the generation and enhancement of pollution maps (also called hypermaps) from raw data;

[0032] - Figure 3 A flow chart illustrating the generation of a hypermap including information about road properties using wear and friction coefficients and / or road specific friction coefficients is shown;

[0033] - Figure 4 A flow chart illustrating use of a hypermap for determining contamination from tire wear without directly measuring tire wear according to an embodiment is shown;

[0034] - Figure 5 is shown a flow chart illustrating the use of a hypermap for determining contamination from tire wear without directly measuring tire wear according to another embodiment;

[0035] - Figure 6 A flow chart illustrating an example in which a hypermap includes a friction coefficient is shown;

[0036] - Figure 7a and Figure 7b illustrates the placement of automotive sensors that may be used to acquire pollution data on a vehicle;

[0037] - Figure 8 The use of a laser sensor for determining road surface information is illustrated;

[0038] - Fig. 9The use of acoustic sensors for determining road surface information is illustrated;

[0039] - Fig.10 The use of a camera sensor for determining road surface information is illustrated;

[0040] - Fig.11 illustrates generation of a hypermap using sensor data from multiple vehicles;

[0041] - Fig.12 shows the structure of a hypermap illustrating the location of a geographic location;

[0042] - Fig.13 There is shown a flow chart illustrating a method for providing information to a vehicle indicative of a level of contamination generated by wear of the vehicle's tires; and

[0043] - Fig.14 A flow chart illustrating a method for controlling a pollution control system of a vehicle is shown. DETAILED DESCRIPTION

[0044] The following detailed description refers to the accompanying drawings, which illustrate by way of illustration the specific details and embodiments in which the present disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the present disclosure. Other embodiments may be utilized, and structural and logical changes may be made without departing from the scope of the present disclosure. Various embodiments are not necessarily mutually exclusive, as some embodiments may be combined with one or more other embodiments to form new embodiments.

[0045] Embodiments described in the context of one of the apparatus or method are analogously valid for the other apparatus or method. Similarly, embodiments described in the context of the apparatus are analogously valid for the vehicle or method, and vice versa.

[0046] Features described in the context of an embodiment may be correspondingly applicable to the same or similar features in other embodiments. Features described in the context of an embodiment may be correspondingly applicable to other embodiments, even if not explicitly described in these other embodiments. Further, additions and / or combinations and / or substitutions as described for features in the context of an embodiment may be correspondingly applicable to the same or similar features in other embodiments.

[0047] In the context of various embodiments, the articles “a,” “an,” and “the” as used with respect to features or elements include reference to one or more of the features or elements.

[0048] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0049] As used herein, the term "vehicle" includes motor-driven vehicles, such as vehicles having 2, 3, 4 or more wheels. Examples of vehicles include passenger cars, vans, buses, trucks, or rail vehicles, such as locomotives. In some embodiments, the vehicle may be an electric vehicle or a hybrid (internal combustion engine and electric) vehicle. In some embodiments, the vehicle may be an internal combustion engine (ICE) vehicle (i.e., a non-hybrid vehicle). The term vehicle may further include autonomous vehicles.

[0050] As used herein, the term "processor(s)" includes one or more circuits capable of processing data, i.e., processing circuits. A processor may include analog circuits or components, digital circuits or components, or hybrid circuits or components. According to alternative embodiments, any other kind of implementation of the corresponding functions described in more detail below may also be understood as a "circuit". A digital circuit may be understood as any kind of logical implementation entity, which may be a dedicated circuit or a processor or firmware that executes software stored in a memory.

[0051] As used herein, the term "module" refers to, forms part of, or includes an application specific integrated circuit (ASIC); an electronic circuit; a combinational logic circuit; a field programmable gate array (FPGA); a processor (shared, dedicated, or group) that executes code; other suitable hardware components that provide the described functionality; or a combination of some or all of the above, such as in a system on a chip. The term module may include a memory (shared, dedicated, or group) that stores code executed by a processor.

[0052] As used herein, the term "data" may be understood to include information in any suitable analog or digital form, for example, provided as a file, a portion of a file, a collection of files, a signal or stream, a portion of a signal or stream, a collection of signals or streams, and the like. However, the term "data" is not limited to the above examples, and may take a number of forms and represent any information as understood in the art.

[0053] As used herein, the term "obtaining", as used herein, refers to a processor that actively obtains input, or passively receives input from one or more sensors or data sources. The term obtaining may also refer to a processor that receives or obtains input from a communication interface (e.g., a user interface). The processor may also receive or obtain input via a memory, register, and / or analog-to-digital port.

[0054] Hereinafter, embodiments will be described in detail.

[0055] Figure 1 A vehicle 100 is shown having a cabin air system.

[0056] The cabin air system includes one or more of a filter 101, a fan 102, and a duct 103, which work together to provide air and circulate the air throughout the cabin of the vehicle. In some embodiments, the one or more filters 101, the fan 102, and the duct 103 may be arranged in series. The cabin air system is designed to remove pollutants, dust, and other harmful particles from the air while also regulating temperature and humidity levels. In particular, the cabin air system operates as a cabin air filtration system (and may be considered as such). Similarly, the cabin air system may operate as an in-vehicle ambient air filtration system and be considered as an in-vehicle ambient air filtration system (ambient air in the sense of air outside the vehicle).

[0057] The cabin air system includes a controller 104 that controls its operation through various control actions, such as setting fan speed and how far vents and air ducts are opened. The controller 104 may, for example, measure the interior air quality and perform corresponding control actions. The controller 104 may form at least a part of a vehicle controller.

[0058] According to various embodiments, a more optimized cabin air (filtration) system is provided, since it not only takes into account the cabin air quality, but also the outside air quality and the state of its filter 101, with the aim of providing improved cabin air quality with lower energy consumption, while optimizing filter usage, for example by extending the RUL (remaining useful life).

[0059] In order to estimate the external air quality, the controller 104 uses a pollution map, wherein at least a portion of the data of the pollution map is provided from vehicle onboard data including tire-generated pollution data (or tire usage data indicating tire-generated pollution). For example, tire usage data may include wear, usage, friction coefficient, or a combination thereof. In some embodiments, wear or friction coefficient may be estimated (e.g., by the controller 104 using additional data such as weather, traffic, and road properties). Based on the tire usage data, the controller 104 may, for example, calculate the pollution data generated by the tires, and estimate the external air quality from these pollution data. For example, an estimate of the pollution generated by the vehicle 100 (particularly tire-generated pollution, but also total pollution, which further includes other pollution depending on external conditions, such as traffic jams, etc.) may be used to anticipate the necessity of activating the operation of the cabin air system (such as filtering operation) to improve the air quality. Therefore, instead of waiting for sensor feedback (e.g., indicating poor internal air quality), the operation of the cabin air system may be activated in advance.

[0060] It should be noted that, furthermore, the calculated tire-generated pollution data can be used, for example, by another controller of the vehicle 100 (i.e., the polluting vehicle), or by the same controller 104, for determining the total (e.g., absolute or net) pollution emissions of the vehicle and possibly controlling them to reduce the net emissions (and, for example, for fault detection and troubleshooting).

[0061] Air quality data are typically available from public measuring stations (such as in particular measurements of PM10 and PM2.5 and also NO2 measurements etc.). Thus, the controller of the cabin air system can use this information. However, in addition to the available information about air quality from the measuring stations, there are other factors that may cause increased air pollution. There may be pollution that these measuring stations cannot identify, because for example a specific (local) measuring station only provides information about the current (local) pollution state about defined parameters (such as PM10), i.e. when only information about such measuring stations is used, there is a blind spot about particles smaller than PM2.5 and larger than PM10, for example.

[0062] According to various embodiments, in particular in the context of controlling a cabin air system as described above, this blind spot is covered by using data collected by car sensors (such as friction coefficient, car movement, traffic, altitude differences, etc., in particular estimating the pollution generated by the tires) to provide more accurate data on pollution, as well as to allow prediction of high pollution levels. In addition to PM10 and PM2.5, in particular the prediction of ultrafine particles (UFP, particles smaller than 0.1 microns) is possible, since it is known that high friction and high flow rates contribute essentially to UFP concentrations. Therefore, according to various embodiments, data for estimating pollution are collected from vehicles on the road and / or public databases.

[0063] It should be noted that the car can be equipped with one or more sensors, and the collected sensor data can give information about the expected pollution risk. The one or more sensors may include at least one hardware sensor, at least one software sensor, or a combination of the at least one hardware and software sensor. In some embodiments, the one or more sensors may further include an on-board sensor, a remote sensor, and / or a remote sensor. Therefore, in addition to PM10 and PM2.5 levels, the risk of increased ultrafine particle concentrations can also be evaluated using automotive sensors. For example, a friction sensor (which can be provided in a vehicle to warn of slippery roads) can provide a friction coefficient that gives an indication of the road and tire wear level. From the perspective of air quality, high friction also means an expected increase in UFP concentration and pollution levels. Therefore, the controller 104 can use this friction information, for example, to estimate the pollution generated by the tire. Similarly, data from other vehicle sensors that are collected and used to provide services (such as warnings about traffic jams, accidents, slippery roads, etc.) can be additionally used to derive air quality information and predict pollution, for example, to intelligently activate the cabin air filtration system. Using the data of these sensors allows to improve the accuracy of the information about air quality and to close the above mentioned blind spot of the measuring stations, namely taking into account influencing factors of air pollution which are ignored when using only data from UFP measuring stations (for a certain particle size).

[0064] It is envisaged that combining the measured air quality (AQ) data with the data provided by the car's sensors may give more precise information and allow prediction of expected risks of high pollution, especially with regard to UFPs. In addition to being used to control the vehicle's cabin air system (e.g., to activate specially designed filters (e.g., HEPA (High Efficiency Particulate Air) filters), the estimated pollution level may also be displayed to a user (e.g., the driver, e.g., in a digital visualization tool such as a dashboard or mobile app) to provide the user with different AQ information or recommendations, such as alternative routes or changing the cabin filter.

[0065] Data related to pollution data acquired by air quality measurement stations and vehicle sensors as described above may be collected in a database 105 (accessible via a database server) to which the controller 104 may be connected, for example. The database 105 may store pollution data for a plurality of locations in a data structure hereinafter referred to as a hypermap (i.e., a pollution map), i.e., pollution data for each of a plurality of geographic locations (e.g., an area of ​​a certain size, a street segment, an urban area, etc.).

[0066] Figure 2The generation and enhancement of a hypermap 201 from raw data 202 is illustrated as being performed, for example, by a database (eg, a corresponding database server) 105 .

[0067] The input data, ie, raw data 202, may be measured data obtained via vehicle sensors or measuring stations, or may be calculated or derived data. In some embodiments, the calculated data may include an estimate of tire wear based on driving data, weather, tire properties, etc.

[0068] Examples of measured data include

[0069] Data from optical measurement of the tire groove depth, for example using stereo vision or laser: wear can be measured, for example the reduction in radius per time.

[0070] Data measured by radio communication (e.g., radio frequency (RF) method): Data output similar to the above

[0071] Slip ratio (based on the difference between GPS vehicle speed and tire speed): easily available.

[0072] • Skiddometer data: allows the coefficient of friction to be measured (typically used at airports).

[0073] The raw data 202 may be continuously acquired and stored and used to generate and (continuously) update the hypermap 201. When the raw data 202 is acquired from the vehicle, it may be anonymized, i.e. personal data protection may be provided by the data protection module 203. Information from the hypermap 201 may be requested, for example, by the controller 104 from, for example, the database 105, to retrieve data for determining pollution in the geographical area in which the vehicle 100 is located.

[0074] According to various embodiments, raw data 202 may be stored and / or processed at various stages. For example, tire wear data may be processed into contamination data for storage in hypermap 201, or tire wear data may be stored in hypermap 201 and processing may occur when contamination data is needed (e.g., on the controller 104 side). In some embodiments, hypermap data 201 may be accessed by one or more external applications via one or more requests 205 sent by application(s) 204. Such requests 205 may be authenticated. It may be appreciated that raw data 202 may not be accessed.

[0075] Figure 3A flow chart 300 is shown illustrating the use of wear and friction coefficients and / or road-specific friction coefficients to generate a hypermap (eg, hypermap 201 ) including information about road properties, performed, for example, by the database (eg, a corresponding database server) 105 .

[0076] In 301, tire wear is calculated using raw data from tire wear measurements 302 provided by a data source 303, such as those mentioned above. The tire wear calculation may use the tire (reference) data and previous values ​​from a memory of previous results (where the current result is also stored for later use). The wear calculation may be temperature corrected (optional) since the groove depth may change with the temperature of the tire itself. By taking into account the travel distance 306 and comparing the tire wear before and after, the friction coefficient may be determined in 307. Depending on the data source 303 provided, the friction coefficient may alternatively be determined without quantifying the tire wear.

[0077] Using location information 308, for example from a global positioning system (GPS), an entry may be generated for the hypermap at 309 containing the determined friction coefficient for the corresponding location. Figure 3 As illustrated in , the hypermap may contain friction coefficients for each of a plurality of different weather conditions (e.g., "rain," "dry weather," "snow," or also temperature ranges, such as below 0°C, 0°C-15°C, 15°C-25°C, above 25°C, ...). Thus, when generating entries of the hypermap, weather data 310 may be considered. In an alternative embodiment of 309, the friction coefficient may be a dimension of the hypermap.

[0078] Figure 4 A flow chart 400 is shown illustrating the use of a hypermap (eg, hosted by database 105 ) for determining contamination from tire wear without directly measuring tire wear, according to an embodiment.

[0079] The controller 104 obtains the location 401 of the vehicle 100, for example from GPS, and determines the current weather conditions 402 that the vehicle 100 is in, for example from rain sensor data and / or a weather map, etc. In 403, the vehicle 100 then requests an entry of the hypermap for / based on the determined current weather conditions 402 and the determined vehicle location 401 from the database 105. The requested entry may be a calculation of pollution data based on the current weather conditions 402 and the determined vehicle location 401.

[0080] In 404 , the database 105 provides the requested entry, namely the pollution data stored for the current weather conditions 402 and the vehicle location 401 , and the controller 104 receives the pollution data.

[0081] The controller 104 may receive additional pollution data 405 (eg, information about traffic) as well as speed / velocity or derivatives (such as acceleration of the vehicle 100 ).

[0082] In 406, the controller 104 controls the cabin air system of the vehicle 100 based on the received pollution data, i.e. the pollution data contained in (the corresponding entry of) the hypermap and possibly the additional pollution data 405. This means that depending on the received pollution data, the controller 104 adjusts operating parameters of the cabin air system, such as filtering parameters.

[0083] In some embodiments, additional pollution data 405 may be based on one or more factors, such as traffic factors, traffic density, acceleration, and / or statistical measurements as described above.

[0084] Figure 5 A flow chart 500 is shown illustrating the use of a hypermap (eg, hosted by database 105) to determine contamination from tire wear without directly measuring tire wear according to another embodiment.

[0085] and Figure 4 Similarly, the controller 104 obtains the location 501 of the vehicle 100, for example from GPS, and then determines the current weather conditions 502 that the vehicle 100 is in. In 503, the vehicle 100 then requests an entry of the hypermap from the database 105 for the determined current weather conditions 502 and the determined vehicle location 501.

[0086] In 504, the database 505 provides the requested entry, ie, the pollution data stored for the current weather conditions 502 and the vehicle location 501, and the controller 104 receives the pollution data. The requested entry may be a calculation of the pollution data based on the current weather conditions 502 and the determined vehicle location 501.

[0087] As in Figure 4 In the example of , the controller 104 may receive additional pollution data 505 (eg, information about traffic) as well as speed / velocity information or derivatives (such as acceleration of the vehicle 100 ).

[0088] At 506 , the controller 104 may further obtain or receive the coefficient of friction 507 of one or more other vehicles in its vicinity, e.g., via vehicle-to-vehicle communications, and may consider this information about the tire conditions of the other vehicles (in addition to the received contamination information) when determining adjustments to operating parameters (e.g., filtration parameters) of the cabin air system.

[0089] At 508 , controller 104 adjusts operation of the cabin air system based on the determined adjustment.

[0090] Figure 6 A flow chart 600 is shown illustrating an example in which a hypermap includes a friction coefficient.

[0091] For example, the controller 104 obtains the location of the vehicle 601 from GPS and then determines the current weather conditions 602 in which the vehicle 100 is located (eg, from rain sensor data and / or weather maps, etc.).

[0092] In 603, it then requests an entry of the hypermap from the database 105 for the determined current weather conditions 602 and the determined vehicle position 601. In this example, the hypermap entry includes a friction component (as pollution data).

[0093] At 604 , the database 105 provides the requested entry, ie, the friction coefficient for the current weather conditions 602 and the vehicle location 601 (eg, a particular road) stored in the hypermap, and the controller 104 receives the friction coefficient.

[0094] The controller 104 may receive additional pollution data 605, such as information about its tires and its driver's driving style (eg, based on speed / velocity and acceleration data).

[0095] In 606, the controller 104 determines the actual tire generated pollution of the vehicle 100 and controls the cabin air system of the vehicle 100 accordingly. This means that depending on the received pollution data, the controller 104 adjusts operating parameters of the cabin air system, such as for example filtering parameters.

[0096] In contrast to the situation in which the pollution data stored in the hypermap are estimates of the pollution generated by the vehicle (in the corresponding location and under the corresponding weather conditions), Figure 6 The method allows a more accurate determination of the pollution generated by the tires of the vehicle (e.g. because individual parameters such as driving behavior can be taken into account). By obtaining the friction coefficient from the database 105, the controller 104 does not need to determine the friction coefficient (between the road and the tire) itself. It should be noted that the database 105 can also store road properties and provide the road properties to the controller 104 so that the controller 104 can estimate the friction coefficient itself. It should further be noted that the estimate of the pollution generated by the tires of the vehicle can be used (e.g. by another controller of the vehicle) to determine the total emissions of the vehicle, and possibly control them to reduce the net emissions (and for example for fault detection and troubleshooting).

[0097] As explained above, pollution data may be acquired by vehicle sensors or measurement sensors and used to generate Figure 2 The hypermap illustrated in , from which pollution data can then be downloaded by the vehicle (particularly the cabin air system controller).

[0098] Pollution data may include information about the following pollutants (e.g., concentrations of the following pollutants): pollen, PM10, PM2.5, PM1, NOx, CO, CO2, VOC (volatile organic compounds). The availability of information about different pollutants depends on sensors installed on the vehicle or data that can be obtained from air quality measurement stations (or providers of air quality data). Information about all those pollutants is not required, and the information can be used to determine the air quality level (e.g., by controller 104). Information about multiple pollutants can be used in combination for better accuracy, but information about individual pollutants can also be used separately (or separately) to ensure a certain level of cabin air system control. For example, PM1 and / or PM2.5 concentrations can be used to decide whether to turn on the HEPA filtration system. Based on a certain threshold of one or both of these concentrations, depending on the usage, the controller 104, for example, activates the HEPA filtration, and once it determines that the air quality is good enough, it turns off the filtration system to protect its life. For example, it uses a threshold of 10ug / m3 for PM2.5 and PM1. Therefore, if the PM2.5 and / or PM1 concentration is above 10 ug / m3, the controller 104 activates the HEPA system.

[0099] For pollen, depending on the accuracy level achieved for pollen concentration and pollutant composition details, the controller 104 may also turn on the HEPA filter to protect passenger health when it detects high pollen concentration (perhaps based on calculations). For example, when the pollen concentration is above a predefined threshold, the controller 104 activates the PM10 filter.

[0100] The CO2 concentration must be kept below a certain threshold to avoid any troubles on the passenger side (headaches, concentration problems ...). The controller 104 can, for example, use the following strategy: If CO2>1000ppm, the controller 104 controls the cabin air system to open the fresh air duct (e.g., baffle) to increase the fresh air flow. For example, the controller can include intelligent management implemented on the baffle to keep the CO2 concentration below 1000 and find a balance between thermal management and air quality. Other pollutants can also be considered to implement strategies, such as NOx and / or VOC, but the specific control action can depend on the cabin air system integrated in the corresponding vehicle. As an example for considering multiple pollutants, if the concentration of any of the above pollutants is higher than a predetermined CO2 threshold and the CO2 concentration is lower than another predetermined CO2 threshold, the controller 104 can turn off the fresh air intake. As another example, if the NOx concentration and / or the VOC concentration is higher than a predetermined threshold, the controller 104 can turn on the activated carbon filter.

[0101] As described above, various vehicle sensors may be used to acquire pollution data. This is described in more detail below.

[0102] Figure 7a and Figure 7b The diagram illustrates the placement of one or more vehicle sensors in the form of automotive sensors that can be used to obtain pollution data on the vehicle. The automotive sensors can be configured to obtain sensor data around the vehicle and / or obtain sensor data from a remotely located server.

[0103] The laser sensor 701 can perform measurements at the front or rear of the car.

[0104] Acoustic sensor 702 may measure acoustic changes at the front wheels or the rear wheels.

[0105] For example, a camera 703 positioned at the windshield may collect information about the surface of the road on which the car is driving.

[0106] Figure 8 The use of a laser sensor 801 for determining road surface information 804 is illustrated.

[0107] In some embodiments, the laser sensor 801 used for road surface detection can be a light detection and ranging (lidar) sensor. The lidar sensor uses a laser beam 802 to measure the distance between the sensor 801 and the road surface 803. By quickly emitting and detecting laser pulses, the lidar sensor creates a 3D map of the road surface. In the case of road surface detection, the laser (i.e., lidar) sensor 801 emits a laser beam onto the road surface and measures the time it takes for the light to bounce back to the sensor. By calculating the time it takes for the light to travel to the road surface and return, the laser sensor 801 can determine the distance between the sensor 801 and the road surface 803. By analyzing the data collected from the lidar sensor 801, it is possible to detect irregularities in the road surface, such as potholes, cracks, or bumps.

[0108] As described above, road surface information 804 (e.g., a 3D map or information derived therefrom, such as the roughness level of the road) can be stored (as pollution information) in a database 805 for each geographic location, i.e., the road surface information 804 can be combined or mapped to a geographic location. In some embodiments, the geographic location can be determined from GPS 806 for later request, e.g., by other vehicles.

[0109] Fig. 9 The use of an acoustic sensor 901 for determining road surface information 904 is illustrated.

[0110] In some embodiments, the acoustic sensors 901 used to determine information in the form of properties of the road surface 902 can be designed to measure the noise levels generated by vehicles as they travel over different road surfaces. The principle behind these sensors is based on the fact that when vehicles pass over different road surfaces, they generate different noise levels.

[0111] In some embodiments, the acoustic sensor 901 includes a microphone that can be embedded in the car and connected to the data collection system. When the vehicle is driving, the microphone picks up the noise generated by the tire and sends the data to the data collection system. The data is then analyzed to determine the noise level generated by the vehicle on the road surface. The determination of the noise level can include comparing with a reference database 903 storing noise level data. By comparing the noise level with a database of reference noise levels, the noise level data collected by the acoustic sensor can be used to evaluate the road surface quality as road surface information and identify the area corresponding to the road surface.

[0112] As described above, the road surface information 904 (road quality) can be stored (as pollution information) in the database 905 for each geographic location, i.e., the road surface information 904 can be combined or mapped to the geographic location. In some embodiments, the geographic location can be determined from the GPS 906 for later request by, for example, other vehicles.

[0113] Fig.10 The use of an image sensor 1001 for determining road surface information 1004 is illustrated.

[0114] In some embodiments, image sensor 1001 can be used to measure the properties of road surface 902. Image sensor 1001 can involve using camera 1001 (or multiple cameras) to capture images or videos of road surface 902, and then analyzing these images or videos to identify different types of road surfaces and classify them - that is, by comparing with reference data from reference database 1003. In some embodiments, the analysis of images and comparison with reference data can be implemented using an artificial intelligence module. In some embodiments, reference data in the form of historical data can be used to train the AI ​​module. Training can be based on supervised learning, unsupervised learning and / or semi-supervised learning.

[0115] In some embodiments, image analysis and classification based on road surface type may include the following steps:

[0116] Image or video capture: The camera 1001 is used to capture images or video of the road surface 1002 .

[0117] Pre-processing: The captured images or videos are pre-processed to enhance their quality and remove any unwanted noise or distortion.

[0118] • Feature extraction: Extract features of the road surface 1002, such as texture, color, and shape, from pre-processed images or videos.

[0119] • Classification: The extracted features are used to classify the road surface 1002 into different classes, such as asphalt, concrete, gravel, or dirt.

[0120] The result of the classification can be used, for example, to make decisions about how to navigate a road. For example, an autonomous vehicle, such as an autonomous car, might use this information to adjust its speed or steering angle. According to various embodiments, it is used as pollution data that allows estimation of tire-generated pollution as described above.

[0121] There are different types of cameras that can be used for road surface detection, including monocular cameras, stereo cameras, and depth cameras. Each type has its own strengths and weaknesses, and the choice of camera depends on the specific application and requirements.

[0122] As described above, road surface information 1004 (e.g., road class) can be stored (as pollution information) in a database 1005 for each geographic location, i.e., the road surface information 1004 can be combined or mapped to a geographic location. In some embodiments, the geographic location can be determined from GPS 1006 for later request by, for example, other vehicles.

[0123] Fig.11 The diagram illustrates the generation of a hypermap using sensor data from a plurality of vehicles 1101 , 1102 , 1103 .

[0124] Each vehicle uses Figure 8 , Fig. 9 and Fig.10 One or more of the methods uses sensor measurements to perform measurements and transmits the corresponding acquired road surface information 804, 904, 1004 to a database system (e.g., cloud) 1104 (e.g., corresponding to database 105), which stores all road surface information in a road information storage device 1105. The database system 1104 may include one or more servers.

[0125] In addition, the database system 1104 (which may be implemented as one or more cloud servers) obtains information about air quality from one or more air quality data providers 1109 (e.g., operating measurement stations as described above) and one or more traffic status data providers 1110 (e.g., operating traffic monitoring stations), which is stored in the air quality data storage device 1105. Using information from the road surface information storage device 1106 (which may have been analyzed to derive road surface information) and the air quality data storage device 1105, and possible additional parameters from the parameter storage device 1107, the server generates (or updates) a hypermap 1108.

[0126] Fig.12 A structure illustrating a hypermap in terms of geographic location is shown.

[0127] Starting with a classic map 1201 illustrating roads, geographic regions can be structured into geo-locations according to location air quality (AQ) providers (possibly using interpolation and / or extrapolation). This structure 1202 can then be further refined according to the geo-locations for which sensor data is received from vehicles (possibly using interpolation and / or extrapolation). This produces a structure 1203 of geo-locations, which can be used as the basis for a hypermap.

[0128] In summary, according to various embodiments, there is provided Fig.13 and Fig.14 The method shown in the figure.

[0129] Fig.13 A flow chart 1300 illustrating a method for providing information to a vehicle indicative of contamination levels generated by wear of the vehicle's tires is shown.

[0130] In 1301, for each of at least some of a plurality of geographic locations, information indicative of vehicle tire wear at the geographic location is obtained, wherein the vehicle wear (information indicative of vehicle wear) is derived from vehicle sensor data from one or more vehicles.

[0131] At 1302, for each of a plurality of geographic locations, pollution data is determined (and, e.g., stored), the pollution data comprising information derived from acquired information indicative of vehicle tire wear indicating (e.g., relating to or based on) pollution levels generated by vehicle tire wear at the geographic location.

[0132] In 1303, in response to a request from a vehicle (i.e., a requestor or a requesting vehicle, such as a requesting component of a requestor or a vehicle) or from another source for information indicating pollution levels generated by tire wear of the vehicle for a geographic location at which the vehicle is located, information indicating pollution levels generated by tire wear of the vehicle determined (e.g., calculated and / or stored) for a geographic location at which the vehicle is located is provided.

[0133] At 1304, method 1300 further includes receiving a transmission of information indicating vehicle tire wear at a geographic location at which a corresponding vehicle in the one or more vehicles is located from each of the one or more vehicles, and wherein the transmission may optionally include an indication of the geographic location at which the corresponding vehicle in the one or more vehicles is located.

[0134] Fig.14 A flow chart 1400 illustrating a method for controlling a pollution control system of a vehicle is shown. In some embodiments, the pollution control system may be or form part of a navigation system of the vehicle that takes air pollution into account.

[0135] At 1401 , information indicative of a level of pollution generated by a vehicle through tire wear is obtained.

[0136] At 1402 , an operating parameter value of a pollution control system of the vehicle is determined based on the acquired information.

[0137] At 1403, a pollution control system of the vehicle is controlled based on the determined operating parameter value.

[0138] According to various embodiments, in other words, vehicle tire wear data is collected based on sensor data from multiple vehicles at various locations, and this is used to build a database of pollution generated by vehicle tire wear at each geographic location, which can then be requested by the vehicle to, for example, control the vehicle's pollution control system.

[0139] The methods described herein may be performed, and the various processing or computing units and devices and computing entities described herein may be implemented by one or more circuits. In an embodiment, a "circuit" may be understood as any kind of logic implementation entity, which may be hardware, software, firmware, or any combination thereof. Therefore, in an embodiment, a "circuit" may be a hardwired logic circuit or a programmable logic circuit, such as a programmable processor, such as a microprocessor. A "circuit" may also be software implemented or executed by a processor, such as any kind of computer program, such as a computer program using a virtual machine code. According to an alternative embodiment, any other kind of implementation of the corresponding functions described herein may also be understood as a "circuit". A device (e.g., a database system or a vehicle, or a vehicle component (e.g., a vehicle controller)) that performs one of the methods may, for example, include a communication interface (to receive and send various data and information), a processing unit, and a memory.

[0140] Although the present disclosure has been particularly shown and described with reference to certain embodiments, it will be understood by those skilled in the art that various changes in form and details may be made without departing from the spirit and scope of the present disclosure as defined by the appended claims. Therefore, the scope of the present disclosure is indicated by the appended claims, and therefore, all changes that come within the meaning and range of equivalents of the claims are intended to be embraced.

Claims

1. A method (1300) for providing information to a vehicle (100) indicating a level of contamination generated by wear of a tire of the vehicle, the method (1300) comprising: For each of at least some of a plurality of geographic locations, obtaining (1301) information indicative of vehicle tire wear at the geographic location, the vehicle wear being derived from vehicle sensor data from one or more vehicles; determining (1302) pollution data (505, 605) for each of the plurality of geographic locations, the pollution data (505, 605) comprising information indicative of pollution levels generated by vehicle tire wear at the geographic location derived from the acquired information indicative of vehicle tire wear; and In response to a request (205) for information indicating a pollution level generated by tire wear of a vehicle (100) for a geographic location at which the vehicle is located, information is provided (1303) indicating a pollution level generated by tire wear of the vehicle determined for the geographic location at which the vehicle is located.

2. The method (1300) of claim 1 further comprises receiving (1304) a transmission of information indicating vehicle tire wear at a geographic location at which a corresponding vehicle in the one or more vehicles is located from each vehicle (100) of the one or more vehicles. 3 . The method of claim 2 , wherein the transmission includes an indication of a geographic location at which a corresponding vehicle of the one or more vehicles is located.

4. The method (1300) of claim 1, wherein the pollution data is stored in a database (105) external to the one or more vehicles.

5. The method (1300) of claim 1, further comprising receiving a request (205) and providing information indicative of a level of contamination generated by tire wear of the vehicle via radio communication.

6. The method (1300) of claim 1 further comprises obtaining information indicative of vehicle tire wear for a plurality of weather conditions and determining pollution data, the pollution data comprising information indicative of pollution levels generated by vehicle tire wear for each of the plurality of weather conditions.

7. A method (1300) according to claim 5, wherein the request indicates at least one of the plurality of weather conditions, and the method includes providing information about pollution levels generated by the vehicle through tire wear at a geographic location at which the vehicle is located as determined for the indicated weather condition.

8. The method (1300) of claim 1, wherein the geographic location at which the vehicle is located is a road or a road segment.

9. A method according to claim 8, wherein the information indicative of the pollution level generated by vehicle tire wear includes information indicative of the condition of a road or road segment, and wherein optionally, the information indicative of the pollution level generated by vehicle tire wear includes an estimate of the coefficient of friction between the vehicle's tires and the road or road segment.

10. A database system (1104), the database system (1104) comprising at least one processor, the at least one processor being configured to: for each of at least some of the plurality of geographic locations, obtaining information indicative of vehicle tire wear at the geographic location, the vehicle wear being derived from vehicle sensor data from one or more vehicles; For example, by the method of any one of claims 1 to 10, for each of the plurality of geographical locations, pollution data is determined, the pollution data comprising information indicative of pollution levels generated by vehicle tire wear at the geographical location derived from the acquired information indicative of vehicle tire wear; and In response to a request for information indicative of a pollution level generated by tire wear of the vehicle for a geographic location at which the vehicle is located, information indicative of a pollution level generated by tire wear of the vehicle determined for the geographic location at which the vehicle is located is provided.

11. A controller (104), the controller (104) comprising at least one processor, the at least one processor being configured to obtaining information indicative of a level of pollution generated by the vehicle (100) through tire wear; determining an operating parameter value of a pollution control system of the vehicle in dependence upon the acquired information; as well as A pollution control system of the vehicle is controlled based on the determined operating parameters.

12. A controller (104) according to claim 11, wherein information indicative of pollution levels generated by the vehicle through tire wear is obtained from a database (105) external to the vehicle, and wherein the information indicative of pollution levels generated by the vehicle through tire wear is optionally obtained from the database (105) via radio communication.

13. The controller (104) of claim 11, comprising obtaining from a database information indicative of pollution levels generated by the vehicle through tire wear by sending a request from the vehicle to the database indicative of the vehicle's location, weather conditions encountered by the vehicle, or both.

14. A controller (104) according to claim 11, wherein the information indicating the pollution level generated by the vehicle through tire wear includes information indicating the condition of the road on which the vehicle (100) is located, and wherein the information indicating the pollution level generated by the vehicle through tire wear includes an estimate of the coefficient of friction between the tires of the vehicle (100) and the road (802, 903, 1003) on which the vehicle (100) is located.

15. A controller (104) according to claim 11, wherein the information indicative of pollution levels generated by the vehicle (100) through tire wear is at least partially derived from sensor data provided by sensors (701, 702, 703) of the vehicle (100).

16. The controller (104) of claim 11, wherein the pollution control system of the vehicle is a cabin air system.

17. A controller (104) according to claim 16, wherein the at least one processor is further configured to estimate the concentration of pollutant particles caused by tire wear of the vehicle from the acquired information, and if the estimated concentration of pollutant particles caused by tire wear of the vehicle is higher than a predetermined threshold, determine operating parameters of the cabin air system to reduce the concentration of pollutant particles caused by tire wear of the vehicle in the vehicle cabin.

18. The controller (104) according to any one of claims 10 to 16, wherein the pollution control system of the vehicle (100) is a vehicle navigation system that takes air pollution into account.

19. A computer program element comprising program instructions which, when executed by one or more processors, cause the one or more processors to perform the method according to any one of claims 1 to 9.

20. A computer readable medium comprising program instructions which, when executed by one or more processors, cause the one or more processors to perform the method according to any one of claims 1 to 9.

Images