Vehicle-based air quality and noise level sampling for use with non-vehicle-mounted map software

Abstract

A host vehicle for use with a remote processing station (RPS) configured to generate a pollution report from a set of global pollution data, the host vehicle comprising a vehicle body, a vehicle telematics unit (VTU), a sensor suite, and an electronic control unit (ECU). The sensor suite comprises acoustic and / or air quality sensors respectively configured to collect pollution data samples. The pollution data samples comprise noise and / or air quality levels as part of the set of global pollution data. The ECU selectively transmits the pollution data samples to the RPS in response to predetermined conditions, receives the pollution report specifying noise and / or air quality levels at a current location or destination of the host vehicle, and performs a control action of the host vehicle or another receiving device in response to the pollution report.

Description

Background Technology

[0001] Particulate matter is typically produced as a byproduct of fuel combustion, power generation, manufacturing, and other processes. While not usually classified as an air pollutant itself, particulate matter also exists in the form of naturally occurring airborne irritants such as pollen, mold, or ragweed. Particulate matter is present in the air we breathe, and its concentration and size distribution can vary considerably depending on location, time of day, week, month, or year, ambient temperature, prevailing winds, humidity levels, and other factors. Manufacturing pollutants are often emitted at higher levels in industrial areas or around power plants, chimneys, forest fires, and around airports. Emissions from motor vehicles, train chimneys, aircraft propulsion systems, and exhaust pipes of inboard and outboard motors on ships and other marine vessels also contribute to particulate concentrations. The harmful health effects of a given concentration, size, and type of particulate matter on an individual user can vary, as users' personal desires to live, work, or travel in more polluted areas, or their lack thereof, can also differ.

[0002] Poor air quality can lead to numerous adverse health effects, including respiratory distress and cardiovascular disease. Furthermore, hearing loss and physical stress responses can result from exposure to elevated levels of ambient noise, commonly referred to as noise pollution. To avoid air and noise pollution, individuals with pre-existing health conditions or pollution sensitivities often rely on local air quality reports when assessing their personal exposure risk at a given location. These reports are typically based on discrete measurements collected by fixed or aerial monitoring stations and attempt to quantify the levels of pollution or allergens at a given location, such as in or above a city, county, or other relatively large geographic area. Therefore, air quality and noise level data may not be readily accessible or relevant to a given individual.

[0003] Similarly, ambient noise levels tend to vary dramatically based on location and time of day, week, month, and year. Urban areas with high concentrations of vehicular traffic and industrial activity tend to be louder than rural areas. A given urban area may be significantly quieter at night or on weekends than the same urban area during weekday working hours. Likewise, noise levels tend to increase when people are near activity building areas, open-air concert venues or sports fields, airports, railways, racetracks, etc. Increased noise levels can range from merely annoying to causing temporary or long-term physical and mental health problems. Therefore, noise pollution is comparable to air pollution in terms of its potential adverse effects on health and overall quality of life. This teaching is beneficial for making personal decisions about the potential journey to a destination or the time spent there, informed by the expected noise and air pollution levels at the destination or along the route to it. Summary of the Invention

[0004] This paper discloses a vehicle network and related cloud-based computing methods for collecting air quality, ambient noise level data, or both, and for reporting this data to consumers or end users. The aim of this teaching is to disseminate more granular or location-specific data to individual users, thereby better informing them to make personal decisions based on ambient air quality and / or noise levels at their current location or intended destination. Due to a lack of relevant air and noise pollution information, particularly near a user's current location or intended destination, individuals may not be able to avoid exposure to polluted or noisy areas. This teaching addresses this problem by leveraging the collective sensing and communication capabilities of a distributed group of master vehicles. The master vehicles collaborate with one or more cloud-based computing resources, referred to herein as remote processing stations (RPS), to provide and receive up-to-date air quality and noise level data, wherein the collection and dissemination of relevant data remains unobtrusive to the individual operators of the master vehicles.

[0005] Specifically, each corresponding master vehicle within the envisioned vehicle network is individually equipped with a sensor suite, including one or more air quality sensors and / or one or more acoustic sensors. The vehicle-hosted sensor suite is activated periodically and temporarily, typically when the master vehicle is parked, stationary, or otherwise turned off, or in response to other predetermined conditions described below. Environmental data collected by the various sensor suites of multiple master vehicles within a given geographic area is offloaded to the cloud and analyzed by the aforementioned RPS, which then communicates remotely with each master vehicle.

[0006] In response to the environmental data collected by the RPS (referred to herein as pollution data samples to account for the presence of any one or both of the types of air and noise pollution), the RPS generates area- or location-specific map data indicating pollution levels and transmits it to a receiving device. In various hypothetical embodiments, the receiving device may include various host vehicles, smartphones, desktop computers, laptops or tablets, wearable devices, etc. Ultimately, the air quality and noise level map is displayed on the receiving device's screen; other advantageous options are possible, as described in detail below.

[0007] Specifically, aspects of this disclosure include a primary vehicle for use with a remote processing station (RPS), wherein the RPS is configured to generate pollution reports from a set of global pollution data. The primary vehicle, which may be implemented differently as a motor vehicle, rail vehicle / train, boat or ship, drone or aircraft, and / or another mobile system, includes a vehicle body, a vehicle telematics unit (VTU) wirelessly communicating with and connected to the RPS, a sensor suite, and an electronic control unit (ECU). The sensor suite includes acoustic sensors and / or air quality sensors, respectively configured to collect pollution data samples at the current location of the primary vehicle. The pollution data samples include ambient noise levels and / or ambient air quality levels. The set of global pollution data includes the pollution data samples and additional pollution data samples from one or more additional primary vehicles. The ECU, communicating with the VTU and sensor suite, selectively transmits pollution data samples to the RPS in response to a set of predetermined conditions via operation of the VTU.

[0008] In a possible implementation, the sensor suite includes acoustic sensors and air quality sensors, wherein the ECU receives pollution reports from the RPS. In this exemplary embodiment, the pollution report describes the noise level and air pollution level at the current location or destination of the main vehicle.

[0009] The predefined conditions may include the vehicle being parked, stationary, or closed.

[0010] The main vehicle may include a display screen. The pollution report may include map data indicating ambient noise levels and ambient air quality levels, wherein the ECU is configured to transmit the pollution report to the display screen to present the map data thereon.

[0011] The vehicle body defines the interior of the vehicle. In one possible embodiment, the acoustic sensor includes at least one microphone located inside the vehicle. In other embodiments, an external microphone may be used, with or without such an onboard microphone.

[0012] Exemplary configurations of air quality sensors include particle counters and / or gas sensors.

[0013] The ECU can optionally be configured to limit the activation of the sensor suite to, for example, less than five minutes per hour. In this or other implementations, the ECU can be configured to prompt the operator of the main vehicle with alternative driving route options based on pollution reports.

[0014] This document also describes a method for use with a master vehicle that communicates with the aforementioned RPS. An exemplary embodiment of the method includes: in response to a set of predetermined conditions, collecting pollution data samples at the current location of the master vehicle using a sensor suite of the master vehicle via an ECU. The method also includes transmitting the pollution data samples to the RPS via a VTU of the master vehicle, the VTU of the master vehicle then communicating with the ECU. The pollution data samples are part of the set of global pollution data. Furthermore, in this embodiment, the method includes receiving a pollution report from the RPS, the pollution report being based on previous data samples from multiple master vehicles. In response to the pollution report, the method also includes displaying ambient noise levels and / or ambient air quality levels on a display screen.

[0015] Another aspect of this disclosure includes a computer-readable storage medium on which instructions executable by a processor of the RPS are recorded. Execution of the instructions causes the processor to receive a set of global pollution data from multiple master vehicles communicating with the RPS, each corresponding master vehicle having a corresponding sensor suite operable to collect pollution data samples at the current location of the corresponding master vehicle. The sensor suite includes acoustic sensors and / or air quality sensors respectively configured to measure ambient noise levels and ambient air quality levels. The pollution data samples are a component of this set of global pollution data.

[0016] The execution of the instructions also causes the processor to calculate the level of uncertainty in the set of global pollution data for the current location, and to generate at least one color-coded map using the set of global pollution data. This color-coded map indicates the ambient noise level and ambient air quality level at the current location and / or destination of the primary vehicle. The at least one color-coded map is based in part on the level of uncertainty. The pollution report, including the at least one color-coded map, is ultimately transmitted to a receiving device for display.

[0017] Option 1. A master vehicle for use with a remote processing station (RPS) configured to generate pollution reports from a set of global pollution data, the master vehicle comprising:

[0018] Vehicle body;

[0019] Vehicle telematics unit (VTU) that communicates wirelessly with RPS and is connected to the vehicle body.

[0020] A sensor suite comprising acoustic sensors and / or air quality sensors respectively configured to collect pollution data samples at the current location of a primary vehicle, the pollution data samples including ambient noise levels and / or ambient air quality levels, wherein the global pollution data set includes the pollution data samples and additional pollution data samples from one or more additional primary vehicles; and

[0021] An electronic control unit (ECU) communicates with the VTU and sensor suite, wherein the ECU selectively transmits pollution data samples to the RPS in response to a set of predetermined conditions via the operation of the VTU.

[0022] Option 2. The main vehicle according to Option 1, wherein the sensor suite includes an acoustic sensor and an air quality sensor, and the ECU is configured to receive a pollution report from the RPS, wherein the pollution report describes the noise level and air pollution level at the current location or destination of the main vehicle.

[0023] Option 3. The main vehicle according to Option 1 further includes wheels connected to the vehicle body, wherein the main vehicle is a motor vehicle, and the set of predetermined conditions includes the motor vehicle being parked, stationary, or in a closed state.

[0024] Option 4. The main vehicle according to Option 1 further includes a display screen, wherein the pollution report includes map data indicating ambient noise level and ambient air quality level, and wherein the ECU is configured to transmit the pollution report to the display screen to present the map data thereon.

[0025] Option 5. The main vehicle according to Option 1, wherein the vehicle body defines the interior of the vehicle, and wherein the acoustic sensor includes at least one microphone located within the interior of the vehicle.

[0026] Option 6. The main vehicle according to Option 1, wherein the air quality sensor includes a particle counter.

[0027] Option 7. The main vehicle according to Option 1, wherein the air quality sensor includes a gas sensor.

[0028] Option 8. The main vehicle according to Option 1, wherein the ECU is configured to limit the activation of the sensor suite to less than five minutes per hour.

[0029] Option 9. The main vehicle according to Option 1, wherein the ECU is configured to prompt the operator of the main vehicle with alternative driving route options based on pollution reports.

[0030] Option 10. A method for use with a master vehicle, the master vehicle communicating with a remote processing station (RPS) configured to generate a pollution report from a set of global pollution data, the method comprising:

[0031] In response to a set of predetermined conditions, a pollution data sample is collected at the current location of the main vehicle using a sensor suite via the main vehicle's electronic control unit (ECU), wherein the sensor suite includes an acoustic sensor and / or an air quality sensor configured to measure ambient noise level and ambient air quality level, respectively.

[0032] Pollution data samples are transmitted to the RPS via the vehicle telematics unit (VTU) of the main vehicle. The VTU communicates with the ECU, and the pollution data samples are part of this set of global pollution data.

[0033] Pollution reports are received from the RPS, based on previous data samples from multiple master vehicles; and

[0034] In response to pollution reports, display the ambient noise level and / or ambient air quality level on the screen.

[0035] Option 11. The method according to Option 10, wherein the RPS is programmed to store the history of pollution reports for a given operating area as historical data on a computer-readable storage medium, and to generate a model of noise pollution and air pollution for the given area using the historical data, wherein receiving pollution reports from the RPS includes receiving historical data.

[0036] Option 12. The method according to Option 10, wherein the set of predetermined conditions includes the motor vehicle being parked, stationary, or in a closed state.

[0037] Option 13. The method according to Option 10, wherein the main vehicle includes a vehicle body defining the interior of the vehicle, and wherein using the sensor suite of the main vehicle includes using at least one microphone located inside the vehicle as a sound sensor.

[0038] Option 14. The method according to Option 10, wherein collecting pollution data samples using the sensor suite of the main vehicle includes using a particulate counter as an air quality sensor.

[0039] Option 15. The method according to Option 10, wherein collecting pollution data samples using the sensor suite of the main vehicle includes using a gas sensor as an air quality sensor.

[0040] Option 16. The method according to Option 10 further includes: limiting the activation of the sensor kit to less than five minutes per hour via the ECU.

[0041] Option 17. The method according to Option 10 further includes: prompting the operator of the main vehicle with alternative driving route options via the ECU based on a pollution report.

[0042] Option 18. A computer-readable storage medium having instructions recorded thereon, the instructions being executable by a processor of a remote processing station (RPS) to cause the processor to:

[0043] A set of global pollution data is received from multiple master vehicles communicating with RPS, each of which has a corresponding sensor suite operable to collect pollution data samples at the current location of the corresponding master vehicle via the electronic control unit (ECU) of the master vehicle, wherein the sensor suite includes an acoustic sensor and / or an air quality sensor respectively configured to measure ambient noise level and ambient air quality level, and wherein the pollution data samples are part of the set of global pollution data.

[0044] The processor calculates the level of uncertainty in this set of global pollution data for the current location;

[0045] At least one color-coded map is generated via a processor using this set of global pollution data. This color-coded map indicates ambient noise levels and ambient air quality levels at the current location and / or destination of the primary vehicle. The at least one color-coded map is based in part on a level of uncertainty.

[0046] The pollution report is transmitted to a receiving device for display thereon, and the pollution report includes at least one color-coded map.

[0047] Option 19. The computer-readable storage medium according to Option 18, wherein the processor has access to a history of pollution reports for a given operating area as historical data, and the instructions are executable by the processor to cause the processor to: generate a model of the ambient noise level and ambient air quality level of the area including the current location and / or destination using the historical data, and generate a pollution report using the historical data.

[0048] Option 20. The computer-readable storage medium according to Option 18, wherein the instructions are executable by a processor to cause the processor to: selectively request activation of one or more sensor suites in the master vehicle based on predetermined collection criteria.

[0049] The foregoing features and advantages, as well as other features and accompanying advantages, of this disclosure will become apparent when taken in conjunction with the accompanying drawings and the appended claims, based on the following detailed description of illustrative examples and models for carrying out this disclosure. Furthermore, this disclosure expressly includes combinations and sub-combinations of the elements and features set forth above and below. Attached Figure Description

[0050] The accompanying drawings are incorporated in and form a part of this specification, illustrating embodiments of the present disclosure and serving together with the description to explain the principles of the present disclosure.

[0051] Figure 1 This is a schematic diagram of a representative vehicle network, in which each corresponding master vehicle is equipped with a corresponding sensor suite that operates according to this application.

[0052] Figure 2 It is used in Figure 1 The diagram shows schematic circuit diagrams of the environmental systems used on various main vehicles.

[0053] Figure 3 The illustration is a representative air quality and noise level map generated by a remote processor and displayed via a screen as part of this strategy.

[0054] Figure 4 This is a flowchart describing an exemplary embodiment of the method.

[0055] The accompanying drawings are not necessarily to scale and present slightly simplified representations of the various features of this disclosure, including, for example, specific dimensions, orientations, positions, and shapes. Details associated with such features will be determined in part by the specific intended application and environment of use. Detailed Implementation

[0056] This disclosure may be implemented in many different forms. Representative examples are shown in the various figures and described in detail herein as non-limiting representations of the principles of the disclosure. Therefore, elements and limitations described, for example, in the abstract, background, summary, and detailed description sections but not expressly set forth in the claims, should not be incorporated into the claims individually or jointly by implication, inference, or otherwise. Furthermore, unless specifically stated otherwise, the use of the singular includes the plural, and vice versa; the terms “and” and “or” should be both conjunctions and adversative conjunctions; “any” and “all” should both mean “any and all”; and the words “including,” “containing,” “comprising,” “having,” etc., should mean “including but not limited to.”

[0057] Similar terms, such as “about,” “almost,” “basically,” “roughly,” “approximately,” etc., may be used herein to mean “within, close to, or almost within,” or “within 0-5% of,” or “within acceptable manufacturing tolerances,” or logical combinations thereof. Similarly, as used herein, a component “configured” to perform a specified function is capable of performing the specified function without alteration, and not merely has the potential to perform the specified function after further modification. In other words, the described hardware, when explicitly configured to perform the specified function, is specifically selected, created, implemented, utilized, programmed, and / or designed for the purpose of performing the specified function.

[0058] As used herein, a component “configured” to perform a specified function is capable of performing the specified function without alteration, rather than merely having the potential to perform the specified function after further modification. In other words, the described hardware, when explicitly configured to perform the specified function, is specifically selected, created, implemented, utilized, programmed, and / or designed for the purpose of performing the specified function.

[0059] Referring now to the accompanying drawings, in which the same reference numerals refer to the same features throughout several views. Figure 1 The diagram illustrates a vehicle network 10 with a remote processing station (RPS) 12, which communicates wirelessly with multiple master vehicles 14 via cellular and / or satellite and is operable for measuring and quantifying air quality and noise levels. Within the scope of this disclosure, the term "master" is used in the context of the vehicles 14, each serving as a corresponding local platform to which the sensors and other hardware systems described herein are attached. For simplicity and clarity, in the common context of air and noise pollution, air quality levels and ambient noise levels are sometimes collectively referred to herein as "pollution." The RPS 12 is implemented as a collection of cloud-based servers or other networked computer devices and configured to generate pollution reports 13 (arrow PR) from a set of global pollution data 15 (arrow PD). This set of global pollution data 15 is transmitted or offloaded to the RPS 12 by individual master vehicles 140 among the multiple master vehicles 14. Each corresponding master vehicle 140 then locally collects a sample of pollution data, referred to herein as 150 for clarity. Figure 1 In the simplified example shown, the total number (n) of such contamination data samples 150 is individually labeled as 150a, 150b, 150c, 150d, 150e, 150f, and 150g. The number (n) can be on the order of thousands, hundreds of thousands, or millions of master vehicles 140, depending on the geographic area covered. Each contamination data sample 150 forms a component or dataset portion of this set of global contamination data 15 provided to RPS 12 via cloud 11. The various non-vehicle functions of RPS 12, equipped with processor 12P and resident memory 12M, are specifically referenced below. Figure 3 and 4 To explain in more detail.

[0060] Each corresponding pollution data sample 150 from a given master vehicle 140 includes local ambient air quality levels and ambient noise levels, both collected at the current location of the corresponding master vehicle 140. Each master vehicle 140 is ideally parked, stationary, or otherwise off during data collection and propagation. That is, a given master vehicle 140 in a non-limiting exemplary form of a motor vehicle will typically detect powertrain, wind and road noise, as well as exhaust emissions from other vehicles traveling near the master vehicle 140 while in motion. When the same master vehicle 140 is parked / off, no such noise will be generated, which helps in detecting ambient noise levels that represent true ambient noise.

[0061] The primary objective of the automated solution described in detail herein is to reduce individual risk of exposure to air pollution, noise pollution, or both. This objective can be achieved by providing users of each master vehicle 140, as well as users of other appropriately equipped receiving devices (e.g., smartphones, portable or stationary computers, wearable devices, etc.), with detailed time-specific and location-specific pollution and noise level data in the form of a pollution report 13. The pollution report 13 envisioned herein is generated offline by RPS 12 using crowdsourced environmental data, featuring cloud-based computing capabilities and remote connectivity to the master vehicle 140. Figure 1 The diagram is provided in Figure 11. Therefore, the main vehicle 140 is effectively used in this paper as a distributed sensor platform to collaborate with RPS 12 when implementing this method, as shown below. Figure 4 Describe its embodiments.

[0062] This instruction utilizes Figure 1 The wide availability of the vehicle network 10 is specifically achieved by equipping and operating individual master vehicles 140 as environmental sensor platforms. While the master vehicles 140 are not necessarily limited to... Figure 1 and 2 The various types of motor vehicles shown, however, contribute to ensuring extensive data collection, leading to higher confidence levels in the relevance and accuracy of the collected data. This, in turn, facilitates the dissemination of forward-looking, location- and time-specific data. Equipped with this information, users can choose to avoid traveling to or spending extended periods in areas beyond their personal tolerance for exposure to air pollution and / or noise. Additional automation solution options, as described below, include prompting the operator of the master vehicle 140 with alternative routes, suggested alternative locations or accommodations, or other possible recommendations to enable a given user to avoid or reduce such exposure.

[0063] refer to Figure 2 The representative main vehicle 140 is configured for use as Figure 1This is part of a vehicle network 10. In the illustrated embodiment, the main vehicle 140 is a motor vehicle equipped with wheels 17, a vehicle body 142 connected to the wheels 17, and a vehicle interior 144 defined by the vehicle body 142, i.e., a passenger compartment or cabin. The main vehicle 140 may be implemented differently as a crossover vehicle as shown, or a sports utility vehicle, sedan, coupe, truck, agricultural equipment, or other mobility platform within the scope of this disclosure. Again, as mentioned above, other types of vehicles, including boats or other vessels, aircraft, rail vehicles, motorcycles, electric bicycles, etc., can be used within the scope of this disclosure. Figure 2 The representative cross-border vehicles are for illustrative purposes only and not as limitations of this teaching. Similarly, the data collection capabilities of vehicle network 10 can be enhanced by collecting data from similarly equipped fixed platforms, such as residential, commercial, academic or government buildings, bridges, cell towers, etc.

[0064] Figure 2 The example of the main vehicle 140 includes an environmental data system 16, which in turn connects with... Figure 1 The RPS 12 wireless / telecommunication is provided. In an exemplary embodiment, the environmental data system 16 includes a vehicle telematics unit (VTU) 18, an electronic control unit (ECU) 22, and a sensor suite 20. The ECU 22 communicates wirelessly with the VTU 18 and the sensor suite 20, for example, via a controller domain network (CAN) bus, Wi-Fi, or BLUETOOTH. ® The connection is as understood in the art. As envisioned herein, the VTU 18 is an in-vehicle telematics control unit operable via... Figure 1 The Cloud 11 connects to external devices, using relevant vehicle-to-everything (V2X) standards and protocols. In this way, the VTU 18 can interact with the RPS 12 (which, in itself, can act as something like ONSTAR). ® The ability to subscribe to host services and may wirelessly communicate with other host vehicles 140 or other external devices, for example, via cellular towers, base stations, mobile switching centers, satellite services, etc. Long-range vehicle communication capabilities with remote non-vehicle devices (e.g., RPS 12) may be provided via one or more of cellular chipsets / components, navigation and positioning chipsets / components, and / or wireless modems, as is generally well known in the art.

[0065] Figure 2The VTU 18, as part of its general programming capabilities, is able to collect vehicle telemetry data in real time using available in-vehicle wireless communication technologies (primarily BLUETOOTH®, Wi-Fi, NFC, etc.), including but not limited to speed, location, temperature, and a wide range of in-vehicle system diagnostic information. As part of its associated hardware configuration, the VTU 18 includes or connects to a Global Positioning System (GPS) receiver 180 and a cellular antenna 200. Telemetry data can be collected via an in-vehicle satellite navigation unit, such as a Global Navigation Satellite System (GNSS) module 19, which in turn connects to the GPS receiver 180 and thus to the GPS satellite orbital constellation (not shown).

[0066] The sensor suite 20, as envisioned herein, includes at least one acoustic sensor 20A and at least one air quality sensor 20B. The corresponding acoustic and air quality sensors 20A and 20B are configured for measuring… Figure 1 The data shown corresponds to the pollution data sample 150. That is, each acoustic sensor 20A is operable for measuring ambient noise levels, for example, using sensors arranged in... Figure 1 One or more unidirectional or array / directional microphones are located within the vehicle interior 144 and are used to output a signal corresponding to the measured ambient noise level (arrow 55), for example, in decibels. Since the main vehicle 140 may be stationary when the acoustic sensors 20A are activated, as described herein, positioning at least some of the acoustic sensors 20A within the vehicle interior 144 eliminates unintentional detection of engine noise, traction motor rotation, or other driveway or road noise that might otherwise be confused with ambient noise. However, in some embodiments, one or more acoustic sensors 20A may be located outside the vehicle interior 144 and may operate individually or in combination with onboard microphones. Automated methods can be used to minimize the detection of cabin noise, such as from the radio or passenger conversations, including the possible detection of the presence of passengers or pets within the vehicle interior 144, the open / closed state of windows of the main vehicle 140, etc. Data collection may be locally triggered by the ECU 22, for example, based on a predetermined sampling interval, or the sensor suite 20 may be activated in response to a request from the RPS 12. For example, RPS 12 can selectively request activation of sensor suites 20 for one or more of the main vehicles 140 based on predetermined collection criteria (e.g., relative lack of data in a given area or area of ​​interest).

[0067] Air quality sensor 20B measures and quantifies ambient air quality / pollution levels and outputs a corresponding measured air quality signal (arrow 65) indicating its level. Air quality sensor 20B can be externally connected to... Figure 1The air quality sensor 20B is positioned on the vehicle body 142 to measure the air quality outside the vehicle interior 144. The air quality sensor 20B can be implemented differently, such as a commercially available particulate matter (PM) sensor, a laser or optical particle counter, or a turbidimeter operable for detecting particulate matter based on light scattering. Furthermore, the air quality sensor 20B may include one or more gas sensors configured to detect the presence and level of specific gases, such as, but not limited to, ozone, sulfur dioxide, nitrogen oxides (NOx), or other gases, for example, via infrared light absorption or other operating principles.

[0068] VTU 18 and ECU 22 can be implemented as one or more digital computer devices equipped with corresponding memories (M1) 18M and (M) 24 and one or more corresponding processors (P1) 18P and (P) 26. ECU 22 is also equipped with a timer or clock 27 operable to timestamp each collected sample, enabling... Figure 1 RPS 12 knows the collection time and date of each transmitted contaminated data sample 150, as well as the collection location as described above. The algorithms, software, control logic, protocols, and / or methods disclosed below, including... Figure 4 The representative method 100 can be at least partially implemented as computer-executable software stored in memory 18M and / or 24M, such as tangible, non-transitory computer-readable storage media, such as flash memory, solid-state drive (SSD) memory, hard disk drive (HDD) memory, CD-ROM, digital versatile disk (DVD) or other suitable storage devices. Each main vehicle 140 may be equipped with an embedded voice processing unit that utilizes audio filtering, editing and analysis modules.

[0069] The operation of processors 18P and 26 may require the use of application-specific integrated circuits (ASICs), programmable logic devices (PLDs), field-programmable logic devices (FPLDs), discrete logic, etc. Therefore, the implementation described below... Figure 4 Instructions for method 100 or its alternative embodiments may be recorded on a non-transitory computer-readable storage medium, which, for simplicity, is... Figure 1 This is represented as memory 24. When executed by processor 26, this instruction causes ECU 22 to perform the environmental sensing and communication functions described herein, wherein processor 18P similarly performs the functions requested by VTU 18.

[0070] During operation of ECU 22, ECU 22 is configured to selectively transmit collected pollution data samples 150 to RPS 12 via cooperation with VTU 18 and operation of VTU 18. This action occurs in response to a set of predetermined conditions. Although other conditions may be contemplated within the scope of this disclosure, the set of predetermined conditions according to the exemplary embodiment includes the main vehicle 140 being parked or otherwise in a calibrated amount of time in a turned-off state, for example, at least approximately five seconds. The set of predetermined conditions may also, or alternatively, include other conditions, such as the main vehicle 140 being unoccupied, and / or method 100 being enabled by the owner / operator or other user of the main vehicle 140 in an "optional joining" usage scenario.

[0071] Figure 2 ECU 22 is configured to be from Figure 1 RPS 12 receives pollution report 13 and ultimately executes control actions in response to the pollution report. For example, ECU 22 can use display control signals (arrow CC) in response to pollution report 13. 25 The ECU 22 controls the display screen 25 to perform in-vehicle control actions, i.e., control actions on the main vehicle 140. Similarly, the ECU 22 can calculate and display alternative route options, suggested alternative destinations, etc., based on the content of the pollution report 13, as described below. The pollution report 13 may include a digital noise and pollution map or other descriptive information describing the ambient noise and air pollution levels at the current location or destination of the main vehicle 140.

[0072] RPS 12 itself ultimately combines pollution data sample 150 with pollution data sample 150 provided by other participating master vehicles 140 to model the environmental noise and air pollution levels at the current or destination location of the master vehicle 140, and outputs pollution reports 13 to various master vehicles 140 and / or other users or subscribers of RPS 12 in a customized / region-specific manner based on its current or expected location. Other control actions can be performed outside the master vehicle 140, and therefore, as non-vehicle control actions, such as displaying similar information on portable electronic devices, wearable devices, etc., this teaching does not necessarily end with vehicle control actions.

[0073] Because it is a pre-determined condition Figure 2The main vehicle 140 can be stationary / off when the acoustic sensor 20A is activated, so the acoustic sensor 20A is strategically positioned within the vehicle interior 144, for example, as an in-cabin microphone array. This arrangement helps eliminate the detection of engine, traction motor, wind, road, or other drivetrain sounds that might otherwise be confused with the ambient noise of concern herein. Furthermore, since modern vehicles are often equipped with such in-cabin microphones, embodiments of this teaching may include reusing existing microphones to function in the disclosed manner. Automated methods can also be used to minimize the detection of in-cabin noise from the radio or passenger conversations. For example, one possible solution involves using seat-based weight sensors, infrared sensors, motion sensors, door lock / seatbelt latch sensors, etc., to detect the presence of an occupant, and then activating the acoustic sensor 20A when the vehicle interior 144 is verified to be unoccupied in some way.

[0074] refer to Figure 3 The remote processing station (RPS) 12 receives the set of global pollution data 15 during its ongoing operation, as described above, which includes various pollution data samples 150, each pollution data sample 150 being generated by... Figure 1 The various master vehicles 140 transmit data over a period of time. RPS 12 can be configured to generate two intuitive graphical maps as part of the pollution report 13: (1) an air quality map (AQM) 29, and (2) a noise level map (NLM) 28. When the pollution report 13 is finally generated by, for example, Figure 2 When received by the receiving equipment of the main vehicle 140 or another suitable device equipped with the aforementioned display screen 25, the AQM 29 and / or NLM 28 are displayed via the display screen 25, for example as a color-coded overlay on the displayed road map, or as a plain text message announcing pollution and / or noise levels. As part of this capability, the RPS 12 is programmed to store the history of pollution reports 13 for a given operating area as historical data on a computer-readable storage medium and to use the historical data to generate a model of noise and pollution for the given area. Therefore, pollution reports 13 may include all or part of historical data, as described below.

[0075] In vehicle-mounted applications, the receiving device includes Figure 2The VTU 18 and ECU 22 of the main vehicle 140 are shown. In this case, the display screen 25 can be implemented as a touchscreen on the center console, such as a navigation or infotainment system. This implementation can facilitate route planning options, for example, by informing the operator of the main vehicle 140 of high noise and / or air pollution levels in or around one or more locations along the planned driving route or at their destination. Alternatively, the receiving device can be a smartphone, in which case the display screen 25 can be implemented as a smartphone touchscreen, for use on / inside or away from the main vehicle 140. Other fixed or portable electronic devices are conceivable as possible receiving devices within the scope of this disclosure, such as desktop computers, laptop computers, tablet computers, or smartwatches or other wearable devices, thus the configuration of the display screen 25 can be varied.

[0076] Now for reference Figure 4 An exemplary embodiment of this method 100 begins at box B101 ("(140) = Close") The term "frame" as used in this article refers to... Figure 1 The illustrated vehicle network 10 executes programming logic steps for one or more hardware components. Block B101 for a given master vehicle 140 within the vehicle network 10 may need to detect a set of predetermined conditions, which may be a single predetermined condition or multiple predetermined conditions in different embodiments. As described above, suitable predetermined conditions for performing method 100 may be the master vehicle 140 being parked, stationary, or in a "closed" or quiet state; other conditions may include the absence of passengers or pets inside the vehicle, the user's "select-to-join" state being active, and so on. When such predetermined conditions have been met, method 100 proceeds to block B102.

[0077] Box B102 (“Activation Sensor (20)” includes activation) Figure 2 The sensor suite 20. While embodiments envision the use of acoustic sensor 20A and air quality sensor 20B, those skilled in the art will understand that method 100 may use any one or both types of sensors 20A and / or 20B (or exclusively at different times or for a given master vehicle 140). That is, based on user preference or from Figure 1 Following instructions from the remote processing station (RPS) 12, the corresponding acoustic and / or air quality sensors 20A and / or 20B can be activated simultaneously or separately, for example, based on the availability or lack of sufficient data for a given area. Once the sensor suite 20 has been activated, method 100 proceeds to block B104.

[0078] Box B104 (“Upload (150) to RPS (12)”) includes sampling relevant information (in this case, ambient air quality and noise level) within a calibrated sampling interval, and then uploading pollution data sample 150 to RPS (12). Figure 1 Cloud 11 is used for final transmission to RPS 12. To limit power consumption on the battery or other power source operable to power sensor kit 20, ECU 22 can be configured to limit the activation of sensor kit 20 to less than, for example, five minutes per hour. That is, the sampling interval should be kept to a minimum, for example, 30 seconds to one minute per hour, or three to five minutes per hour in different implementations. Once contamination data sample 150 has been collected and transmitted via... Figure 2 The clock 27 plus a timestamp, VTU18 uses Figure 2 Cellular antenna 200 wirelessly transmits contamination data sample 150 to RPS 12. Then method 100 proceeds to block B106.

[0079] In the Figure 1 At box B106 (“Calculating the Uncertainty Level (UL)”) of RPS 12, RPS 12 can calculate the numerical uncertainty level or confidence level for a given area, for example, based on the number of samples collected or the number of master vehicles 140 that collect measurements for a specific area of ​​interest. As an illustrative example, a collection density of, for instance, 500 samples per day over several consecutive weeks within several square blocks of area might correspond to a high confidence level, while collecting 50 samples per day in the same area on non-consecutive days (potentially with a large data gap during the weekend) might correspond to a low confidence level. Therefore, a threshold collection density can be used by RPS 12 to help classify the set of global pollution data 15 and / or the pollution data samples 150 comprising a given area into low, medium, and high confidence levels. RPS 12 can perform the same uncertainty analysis on both noise and pollution levels.

[0080] As part of the envisioned approach, current and historical data can be selectively mixed or combined based on the level of uncertainty. When the uncertainty of the current data is high, for example... Figure 1RPS 12 may rely more heavily or even exclusively on historical data of the region of interest. Alternatively, RPS 12 may choose to mix current data with historical data, for example, using data weighting or a method based on a predetermined formula to fill gaps in the data sample 150, i.e., relying more heavily on historical data at low confidence levels and more heavily on current data at high confidence levels. Therefore, according to this alternative implementation of the teachings, data weighting is performed based on confidence in a fixed manner or with a sliding or variable scale. Once the confidence level of the data sample 150 for a given region of interest has been determined, method 100 proceeds to block B107.

[0081] In box B107 ("UL < CAL") At point B107, RPS 12 next compares the calculated uncertainty level with a calibrated threshold, and proceeds to box B108 if the uncertainty level is less than the threshold. Alternatively, if the uncertainty level is greater than the threshold, box B107 proceeds to box B110.

[0082] Box B108 (“Using Historical Data”) may require retrieving all or part of historical data, i.e., previously determined noise and pollution levels for a given area of ​​interest. This historical data is recorded over time during the continuous operation of RPS 12. That is, RPS 12 maintains an operational history of noise and pollution levels for multiple areas of interest on a digital map (i.e., a geospatial map database). When the latest data is unavailable or available data is uncertain due to a low number of reporting sensors, RPS 12 may retrieve historical data from its resident memory and feed it to box B112 in method 100. While the use of historical data (which may be collected at different times of the day, week, or year of interest to the user) is not ideal, it is better than reporting low-confidence data or not reporting noise or pollution data at all.

[0083] Box B110 (“Using Current Data”) may require using the current data noise and contamination levels for a given region of interest, primarily or exclusively replacing historical data. RPS 12 therefore relays the current data to box B112, after which method 100 proceeds to box B112.

[0084] At box B112 (“Generate Map”), Figure 1 RPS 12 generation as follows Figure 3The AQM 29 and NLM 28 are shown. Box B112 may include using spatially distinct data samples 150 from various master vehicles 140 processed via RPS 12, and then building or updating models from the data samples 150, including reported locations, times of day, days of week, etc. Data modeling or model fitting may be used to generate AQM 29 and NLM 28. The generated maps may be used to update the aforementioned historical data, which may then optionally be sold or made available to interested third parties, for example, based on an app-based subscription or as an add-on service. Method 100 then proceeds to box B114.

[0085] Box B114 (“Transmission (13) to User”) requires the transmission of contamination report 13 to the receiving device via RPS 12. In a non-limiting embodiment, the receiving device includes Figure 1 One of the various main vehicles 140, as described above. In possible implementations, pollution report 13 includes AQM 29 or NLM 28 or both, or pollution report 13 may convey relevant information in another way, for example, as an SMS text message. Once... Figure 1 The VTU 18 or equivalent receiving hardware of the receiving device with alternative constructions can be received via AQM 29 and NLM 28. Figure 3 The display screen 25 shows.

[0086] As part of box B114 or another logical box, the user of the main vehicle 140 can input the route destination into available route planning software, which can then be operated on or in collaboration with ECU 22, possibly in conjunction with the user's smartphone and applications accessible thereon. ECU 22 can overlay AQM 29 and NLM 28 onto the route map displayed via display screen 25. In this way, the user can view a visual representation of noise and pollution levels on or along the displayed driving route, for example, as color-coded shading, possibly using typical green, orange / yellow, and red scales to gradually increase noise or pollution levels.

[0087] Optionally, the route planning system can suggest alternative driving route options that bypass locations along the route with higher levels of pollution or noise. Similar methods can also be used outside the context of route planning. For example, someone planning an outdoor event or booking a hotel can access a software application (“app”) on their smartphone to view the AQM 29 and / or NLM28 for a given location. The user might input a desired threshold for pollution or noise, and the app would then display alternative locations or hotels that meet the user's specific noise / pollution requirements.

[0088] As those skilled in the art will understand, some aspects of this disclosure may... Figure 1 This is implemented at the level of RPS 12. For example, RPS 12 may include a computer-readable storage medium, such as a processor 12P, on which instructions executable by the processor 12P from resident memory 12M are recorded. Execution of such instructions enables the processor 12P to receive the set of global pollution data 15 from multiple master vehicles 14, each respective master vehicle 140 having a corresponding sensor suite 20 operable for collecting pollution data samples 150 at the current location of the respective master vehicle 140. Execution of the instructions also enables the processor 12P to calculate the aforementioned level of uncertainty in the set of global pollution data 15 for the current location, and to generate, via the processor 12P, a [database name missing] using the set of global pollution data 15. Figure 3 At least one color-coded map is illustrated at locations 28 and 29. These maps 28 and 29, representing the ambient noise level and ambient air quality level, are respectively based in part on the uncertainty level. The execution of the instruction ultimately results in the transmission of pollution report 13 to a receiving device, such as the host vehicle 140 or another user device, wherein pollution report 13 includes at least one color-coded map.

[0089] In this scenario, processor 12P may have access to the history of pollution reports for a given operating area, as described above as historical data. Instructions can therefore be executed by processor 12P to generate a model of the ambient noise level and ambient air quality level of the area, including the current location and / or destination, using the historical data, and to generate a pollution report 13 using the historical data. Among other possible actions, instruction execution may also cause processor 12P to selectively request activation of sensor suites 20 for one or more of the main vehicles 140 based on predetermined collection criteria, including but not limited to areas of particular interest with blank or insufficient data coverage.

[0090] Therefore, the aforementioned teachings make Figure 1 The primary vehicle 140, as represented herein, can be used as a sensor platform for detecting air pollution and noise levels, thereby improving the existing technology regarding the collection, dissemination, and potential end-use of vehicle-mounted data. Pollution data samples 150 provided by a large number of such primary vehicles 140 are distributed over a wide range of areas, essentially global in the modern world. Models of air quality and noise levels, dependent on time and location, can be generated based on current and historical measurements at a given location or destination. The output of such maps can be visually displayed to consumers of pollution reports 13, for example, as color-coded digital maps, road map overlays, or simple SMS text messages or other suitable alerts. This teaching similarly envisions the possible fusion of data with other air quality monitoring systems or networks to achieve even higher spatial resolution. Therefore, this disclosure is not necessarily limited to the vehicle use context detailed herein.

[0091] The detailed description and accompanying drawings are supporting and descriptive of this teaching, but the scope of this teaching is defined only by the claims. While the best mode and some other embodiments for carrying out this teaching have been described in detail, various alternative designs and embodiments exist for practicing the teaching as defined in the appended claims. Furthermore, this disclosure expressly includes combinations and sub-combinations of the elements and features set forth above and below.

Claims

1. A master vehicle for use with a remote processing station configured to generate pollution reports from a set of global pollution data, the master vehicle comprising: Vehicle body; A vehicle telematics unit that wirelessly communicates with a remote processing station and is connected to the vehicle body; A sensor suite comprising acoustic sensors and / or air quality sensors respectively configured to collect pollution data samples at the current location of a primary vehicle, the pollution data samples including ambient noise levels and / or ambient air quality levels, wherein the global pollution data set includes the pollution data samples and additional pollution data samples from one or more additional primary vehicles; and An electronic control unit that communicates with a vehicle telematics unit and a sensor suite, wherein the electronic control unit selectively transmits pollution data samples to a remote processing station in response to a set of predetermined conditions via operation of the vehicle telematics unit. The set of predetermined conditions includes pollution data samples collected when the main vehicle is not occupied; The set of predetermined conditions includes, according to predetermined collection criteria, a lack of data from the area where the main vehicle is currently located; and The remote processing station is programmed to store historical pollution reports for a given operating area as historical data on a computer-readable storage medium, and to generate a model of noise and air pollution for the given operating area using the historical data instead of the current data when the uncertainty level calculated about the current data is greater than a predetermined threshold uncertainty level. The sensor suite includes acoustic sensors and air quality sensors, and the electronic control unit is configured to receive the pollution reports from the remote processing station, including receiving the historical data.

2. The main vehicle according to claim 1, wherein, The pollution report describes the noise and air pollution levels at the current location or destination of the main vehicle.

3. The main vehicle according to claim 1, further comprising wheels connected to the vehicle body, wherein, The main vehicle is a motor vehicle, and the predefined conditions for this group include the motor vehicle being parked, stationary, or in a closed state.

4. The main vehicle according to claim 1, further comprising a display screen, wherein, The pollution report includes map data indicating ambient noise levels and ambient air quality levels, and the electronic control unit is configured to transmit the pollution report to a display screen to present the map data thereon.

5. The main vehicle according to claim 1, wherein, The vehicle body defines the interior of the vehicle, and the acoustic sensor includes at least one microphone located inside the vehicle.

6. The main vehicle according to claim 1, wherein, Air quality sensors include particle counters.

7. The main vehicle according to claim 1, wherein, Air quality sensors include gas sensors.

8. The main vehicle according to claim 1, wherein, The electronic control unit is configured to limit the activation of the sensor suite to less than five minutes per hour.

9. The main vehicle according to claim 1, wherein, The electronic control unit is configured to provide the operator of the main vehicle with alternative driving route options based on pollution reports.

10. A method for use with a master vehicle, the master vehicle communicating with a remote processing station configured to generate a pollution report from a set of global pollution data, the method comprising: In response to a set of predetermined conditions, a pollution data sample is collected at the current location of the main vehicle using a sensor suite of the main vehicle via the electronic control unit of the main vehicle, wherein the sensor suite includes an acoustic sensor and / or an air quality sensor respectively configured to measure ambient noise level and ambient air quality level. Pollution data samples are transmitted to a remote processing station via the vehicle telematics unit of the main vehicle. The vehicle telematics unit communicates with the electronic control unit. The pollution data samples are part of this set of global pollution data. Pollution reports are received from a remote processing station, based on previous data samples from multiple master vehicles; In response to pollution reports, the system displays ambient noise levels and / or ambient air quality levels on the screen. The set of predetermined conditions includes, according to predetermined collection criteria, a lack of data from the area where the main vehicle is currently located; and The remote processing station is programmed to store historical pollution reports for a given operating area as historical data on a computer-readable storage medium, and to use the historical data instead of the current data to generate a model of noise and air pollution in the given operating area when the uncertainty level calculated about the current data is greater than a predetermined threshold uncertainty level, wherein receiving pollution reports from the remote processing station includes receiving historical data.

11. The method according to claim 10, wherein, The predefined conditions include the vehicle being parked, stationary, or closed.

12. The method according to claim 10, wherein, The main vehicle includes a vehicle body within a defined vehicle interior, wherein the sensor suite using the main vehicle includes using at least one microphone located within the vehicle interior as a sound sensor.

13. The method according to claim 10, wherein, Pollution data samples are collected using the sensor suite of the main vehicle, including the use of a particulate counter as an air quality sensor.

14. The method of claim 10, wherein, Pollution data samples are collected using the sensor suite of the main vehicle, including the use of gas sensors as air quality sensors.

15. The method of claim 10, further comprising: The activation of the sensor kit is limited to less than five minutes per hour via the electronic control unit.

16. The method of claim 10, further comprising: The electronic control unit provides the operator of the main vehicle with alternative driving route options based on the pollution report.

17. A non-transitory computer-readable storage medium having instructions recorded thereon, the instructions being executable by a processor of a remote processing station to cause the processor to: A set of global pollution data is received from multiple corresponding master vehicles communicating with a remote processing station. Each corresponding master vehicle has a corresponding sensor suite operable to collect pollution data samples at its current location in response to a set of predetermined operating conditions via an electronic control unit of each master vehicle. The corresponding sensor suite includes acoustic sensors and / or air quality sensors configured to measure ambient noise levels and ambient air quality levels, respectively, wherein the pollution data sample is part of the set of global pollution data; The processor calculates the level of uncertainty in this set of global pollution data for the current location; The uncertainty level is based on the number of samples collected in a given operating area, or on the number of the plurality of corresponding master vehicles that collect measurements in a given operating area; The processor at the remote processing station uses this set of global pollution data to generate at least one color-coded map, the at least one color-coded map indicating the ambient noise level and ambient air quality level at the current location and / or destination of each respective master vehicle, the at least one color-coded map being based in part on the level of uncertainty; and The pollution report is transmitted to a receiving device for display thereon; the pollution report includes at least one color-coded map. The set of predetermined conditions includes, according to predetermined collection criteria, a lack of data from the area where each corresponding master vehicle is currently located; and The remote processing station is programmed to store historical pollution reports for the given operating area as historical data on a computer-readable storage medium, and to generate a model of noise and air pollution for the given operating area using the historical data instead of the current data when the uncertainty level calculated about the current data is greater than a predetermined threshold uncertainty level, wherein transmitting the pollution reports includes transmitting the historical data.

18. The non-transitory computer-readable storage medium according to claim 17, wherein, The processor has access to the history of pollution reports for the given operating area as historical data. The instructions can be executed by the processor to cause the processor to: generate a model of the ambient noise level and ambient air quality level of a first area including the current location and / or destination using the historical data, and generate a pollution report using the historical data.

19. The non-transitory computer-readable storage medium according to claim 17, wherein, The instructions can be executed by a processor to cause the processor to selectively request activation of one or more sensor suites in the master vehicle based on the predetermined collection criteria that include the lack of data coverage of the given operating area.

20. The non-transitory computer-readable storage medium according to claim 17, wherein, The electronic control unit is configured to limit the activation of the sensor suite to less than five minutes per hour.

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