Method and apparatus for road noise cancellation

Abstract

Methods and systems are described herein for a vehicle system that provides built-in road noise cancellation in a vehicle. In one or more embodiments, a method for road noise cancellation includes monitoring an occupant ear position using a head tracking device; capturing airborne noise by using a feed-forward microphone and a headrest microphone in the area where the ears of the passenger are located; updating acoustic path information as a function of the occupant ear position and the speaker position within the region; generating a noise cancellation signal using a sampling rate greater than 2 kHz; and outputting the noise cancellation signal via a headrest speaker located near a zone where the occupant's ears are located to at least partially reduce the road noise level in the zone.

Description

[0001] Cross - Reference to Related Applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 607,967, filed on Dec. 8, 2023, titled “METHOD AND APPARATUS FOR ROADNOISE CANCELLATION”. The entire content of the application listed above is hereby incorporated by reference for all purposes. Technical Field

[0003] The present disclosure relates to methods and devices for an audio environment of a vehicle. Background Art

[0004] An active road noise cancellation (RNC) system is a noise, vibration, and harshness (NVH) mitigation system that effectively reduces continuous vehicle rumble and roar noise in a vehicle's cabin. Conventional RNC systems cancel low - frequency, structure - borne noise (typically below 400 Hz). Conventional RNC systems and other NVH mitigation systems may face challenges when attempting to reduce high - frequency noise (e.g., 400 Hz or above). These challenges may be due to the lack of airborne noise source detection, long delays, and small quiet zones. Although these systems can provide significant noise attenuation, it is still desirable to mitigate the remaining high - frequency noise for a quiet and comfortable cabin experience. Automotive - grade digital signal processing (DSP) and digital sensors can be implemented in the RNC system to assist in mitigating NVH at frequencies of 400 Hz and above. Summary of the Invention

[0005] This document describes methods and systems for a vehicle system that provides built-in road noise cancellation. In one or more embodiments, a method for road noise cancellation includes monitoring the position of an occupant's ears using a head tracking system; capturing airborne noise using a feedforward microphone and a headrest microphone in the area where the occupant's ears are located; updating acoustic path information based on the position of the occupant's ears and the position of speakers in the area; achieving fast system latency using a sampling rate of at least 2 kHz and a low-latency anti-aliasing (AA) filter; and outputting sound via a headrest speaker located near the area where the occupant's ears are located to at least partially reduce the road noise level in the area. The method can be implemented by a high-frequency road noise cancellation (HF-RNC) system, which includes: a feedforward sensor that includes an accelerometer and a microphone; a vehicle speaker system that includes headrest speakers, door speakers, a center speaker, and a subwoofer; cabin microphones that include headrest microphones and roof lining microphones; a head tracking system configured to detect the position of the occupant's ears and the seat position, an embedded system including a digital signal processing system, a low-latency signal processing system, a low-latency filter, a power management integrated circuit; and a controller having computer-readable instructions stored on a non-volatile memory, the computer-readable instructions when executed causing the controller to perform the above method.

[0006] It should be understood that the above summary is provided to introduce in a simplified form a series of concepts that are further described in the detailed description. This does not mean determining the key or essential features of the claimed subject matter, the scope of which is uniquely defined by the claims that follow the detailed description. Furthermore, the claimed subject matter is not limited to embodiments that solve any disadvantages noted above or in any part of this disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The present disclosure can be better understood by reading the following description of non-limiting embodiments with reference to the accompanying drawings, in which:

[0008] Figure 1 A block diagram of an in-vehicle computing system and one or more external devices is shown;

[0009] Figure 2 A block diagram of a high-frequency road noise cancellation (HF-RNC) system is shown;

[0010] Figure 3 A graph showing the coherence between a headrest microphone and a feedforward accelerometer signal is shown;

[0011] Figure 4A graph showing a comparison of the impulse responses from a door speaker and, in comparison, from a headrest speaker;

[0012] Figure 5 A graph showing a comparison of the frequency response of a headrest speaker and the frequency response of a door speaker;

[0013] Figure 6 An example of a headrest of an HF - RNC system is shown;

[0014] Figure 7 A graph showing a comparison of the noise measured directly at the occupant's ear and the noise at the occupant's ear estimated by virtual sensing technology;

[0015] Figure 8 An illustration showing the interior of a vehicle configured with an HF - RNC system and the path of an AI - based head - tracking system;

[0016] Figure 9 A block diagram showing the algorithm of the HF - RNC system;

[0017] Figure 10 A graph showing the noise cancellation performance of the driver's seat of the HF - RNC system; and

[0018] Figure 11 A flowchart showing the active road noise cancellation method implemented by the HF - RNC system. Detailed Description

[0019] The following description relates to systems and methods for built - in road noise cancellation in vehicle systems. In one or more examples, a method for road noise cancellation includes monitoring an occupant's ear position using a head - tracking device; capturing airborne noise sources using a feed - forward microphone and a headrest microphone in the area of the occupant's ear position; updating acoustic path information based on the occupant's ear position and the speaker position in the area; generating a noise cancellation signal using a sampling rate greater than 2 kHz; and outputting the noise cancellation signal via a headrest speaker located near the area of the occupant's ear position to at least partially reduce the road noise level in the area.

[0020] The vehicle HF-RNC system described herein extends the noise cancellation frequency range to 1 kHz and beyond 1 kHz. The vehicle HF-RNC system includes a plurality of enablers, the plurality of enablers including a feedforward microphone, a headrest microphone, headrest speakers, low-latency signal processing, a head tracking system, and an extended multi-input / multi-output system. The air-borne noise sources are captured using the feedforward microphone. The low system latency is achieved by a fast sampling rate and a low-latency anti-aliasing filter. The headrest speakers are used together with the door speakers and the subwoofer to reduce the audio latency in the acoustic domain. The cabin microphone can be mounted in the same housing as the headrest speaker and can be positioned in the headrest and / or the seat shoulder. The head tracking system monitors the movement of the occupant's ear position. The head tracking system also uses a face recognition artificial intelligence (AI) algorithm to detect the positions of the occupant's ears and the headrest speakers and cooperates with a stereo camera to identify their three-dimensional positions.

[0021] Figure 1 An example of an in-vehicle computing system of a vehicle is shown, where the in-vehicle computing system can include and / or be communicatively coupled to elements of a road noise cancellation (HF-RNC) system. The RNC system can be a high-frequency RNC (HF-RNC) system. Figure 2 A block diagram of the HF-RNC system is shown. Figure 3 A graph showing the coherence between the headrest microphone and the feedforward accelerometer signals of the HF-RNC system is shown. Figure 4 A graph comparing the impulse responses from the door speakers with those from the headrest speakers is shown. Figure 5 A graph comparing the frequency responses of the headrest speakers with those of the door speakers is shown. Figure 6 An implementation of a headrest noise cancellation system is shown, which can be included in the HF-RNC system. Figure 7 A graph comparing the noise directly measured at the ears of an occupant (e.g., a user) with the noise estimated at the occupant's ears through virtual microphone technology is shown. Figure 8 An illustration of the interior of a vehicle configured with the HF-RNC system and the path of the AI-based head tracking system is shown. Figure 9 A block diagram of the algorithm of the HF-RNC system is shown. Figure 10 A graph showing the noise cancellation performance of the driver's seat of the HF-RNC system is shown. Figure 11 A flowchart showing the active road noise cancellation method implemented by the HF-RNC system is shown.

[0022] Figure 1A block diagram of the in-vehicle computing system 109 of the vehicle 102 is shown. The in-vehicle computing system 109 may execute one or more of the methods described herein in some embodiments. In some examples, the in-vehicle computing system 109 may be an in-vehicle infotainment system configured to provide information-based media content (audio and / or visual media content, including entertainment content, navigation services, etc.) to vehicle users to enhance the operator's in-vehicle experience. The in-vehicle computing system 109 may include or be coupled to various vehicle systems, subsystems, hardware components, and software applications and systems located or integrated in the vehicle 102 to enhance the in-vehicle experience of the driver and / or passengers. The in-vehicle computing system 109 may also be coupled to elements of the RNC system, such as the HF-RNC system further described with respect to Figure 2 as described further.

[0023] The in-vehicle computing system 109 may include one or more processors, the one or more processors including an operating system processor 114 and an interface processor 120. The operating system processor 114 may execute an operating system on the in-vehicle computing system 109 and control the input / output, display, playback, and other operations of the in-vehicle computing system 109. The interface processor 120 may interface with the vehicle control system 130 via the vehicle-to-vehicle system communication module 122.

[0024] The vehicle-to-vehicle system communication module 122 may output data to one or more other vehicle systems 131 and one or more other vehicle control elements 161, while also receiving data inputs from the other vehicle systems 131 and other vehicle control elements 161 via the vehicle control system 130, for example. When outputting data, the vehicle-to-vehicle system communication module 122 may provide a signal corresponding to the output of any state of the vehicle, the vehicle's surrounding environment, or any other information source connected to the vehicle via a bus. Vehicle data output may include, for example, analog signals (such as current speed), digital signals provided by separate information sources (such as a clock, a thermometer, a position sensor such as a Global Positioning System (GPS) sensor, etc.), and / or digital signals propagated through a vehicle data network (such as an Engine Controller Area Network (CAN) bus through which engine-related information may be transmitted). For example, the in-vehicle computing system 109 may retrieve the current speed of the vehicle estimated by a wheel sensor from the engine CAN bus, the power state of the vehicle obtained via the vehicle's battery and / or power distribution system, the ignition state of the vehicle, etc. Additionally, other interfacing means such as Ethernet may also be used without departing from the scope of the present disclosure.

[0025] A storage device 108 may be included in the vehicle computing system 109 to store data, such as instructions, in a non-volatile form that can be executed by the operating system processor 114 and the interface processor 120. The storage device 108 may store application data, including pre-recorded sounds, to enable the vehicle computing system 109 to run applications to connect to a cloud-based server and / or collect information for transmission to the cloud-based server. The application may retrieve information collected by vehicle systems / sensors, input devices (e.g., user interface 118), data stored in one or more storage devices (such as volatile memory 119A or non-volatile memory 119B), data in devices communicating with the vehicle computing system (e.g., mobile devices connected via a link), etc. ([[]] is a registered trademark of the Bluetooth Technology Alliance Corporation of Kirkland, Washington.) The vehicle computing system 109 may also include volatile memory 119A. The volatile memory 119A may be random access memory (RAM). Non-transitory storage devices, such as non-volatile storage device 108 and / or non-volatile memory 119B, may store instructions and / or code that, when executed by a processor (e.g., operating system processor 114 and / or interface processor 120), control the vehicle computing system 109 to perform one or more of the actions described in this disclosure.

[0026] A microphone 103 may be included in the vehicle computing system 109 to: receive voice commands from a user; measure ambient noise in the vehicle; determine whether the audio from the vehicle's speakers is tuned according to the vehicle's acoustic environment, etc. The passenger compartment of the vehicle may include more than one microphone 103. In short, the passenger compartment may be divided into multiple zones, and each of the multiple zones may have a microphone located therein to measure the ambient noise in the corresponding zone. The voice processing unit 104 may process voice commands, such as voice commands received from the microphone 103. In some embodiments, the vehicle computing system 109 may also be able to use a microphone included in the vehicle's audio system 132 to receive voice commands and sample ambient vehicle noise.

[0027] One or more additional sensors may be included in the in-vehicle computing system or the sensor subsystem 110 of 109. For example, the sensor subsystem 110 may include cameras, such as a rearview camera for assisting a user in parking a vehicle and / or a cabin camera for identifying a user (e.g., using face recognition and / or user gestures). As further described herein, the cabin camera may be used to detect the position of a user's head. The sensor subsystem 110 may also include, for example, one or more pressure sensors and / or attachment sensors in one or more zones of the cabin to detect the presence of a user in the corresponding zone. The sensor subsystem 110 of the in-vehicle computing system 109 may communicate with and receive inputs from various vehicle sensors and may further receive user inputs. For example, the inputs received by the sensor subsystem 110 may include transmission gear position, transmission clutch position, throttle pedal input, brake input, transmission selector position, vehicle speed, engine speed, mass air flow through the engine, ambient temperature, intake temperature, etc., as well as inputs from climate control system sensors, an audio sensor for detecting voice commands issued by a user, a key fob sensor for receiving commands from and optionally tracking the geographical location / proximity of the key fob of the vehicle, etc.

[0028] While some vehicle system sensors may communicate with the sensor subsystem 110 individually, other sensors may communicate with both the sensor subsystem 110 and the vehicle control system 130, or may communicate with the sensor subsystem 110 indirectly via the vehicle control system 130. The navigation subsystem 111 of the in-vehicle computing system 109 may generate and / or receive navigation information, such as location information (e.g., via a GPS sensor and / or other sensors from the sensor subsystem 110), route guidance, traffic information, point of interest (POI) identification, and / or provide other navigation services for a driver.

[0029] The external device interface 112 of the in-vehicle computing system 109 may be coupled to and / or communicate with one or more external devices 150 located outside the vehicle 102. Although the external devices are shown as being located outside the vehicle 102, it should be understood that they may be temporarily accommodated within the vehicle 102, such as when a user is operating an external device while operating the vehicle 102. In other words, the external devices 150 are not integrated with the vehicle 102. The external devices 150 may include a mobile device 142 (e.g., connected via NFC, or other wireless connections) or alternative supported devices 152. (Wi- is a registered trademark of the Wi-Fi Alliance in Austin, Texas.)

[0030] The mobile device 142 can be a mobile phone, a smart phone, a wearable device / sensor, or other portable electronic device that can communicate with the in-vehicle computing system via wired and / or wireless communication. Other external devices include one or more external services 146. For example, the external device can include an out-of-vehicle device that is separate from and located outside of the vehicle. Still other external devices include one or more external storage devices 154, such as solid state drives, pen drives, universal serial bus (USB) drives, etc. Without departing from the scope of the present disclosure, the external device 150 can communicate with the in-vehicle computing system wirelessly or via a connector. For example, the external device 150 can communicate with the in-vehicle computing system 109 through the external device interface 112 via a network 160, a USB connection, a direct wired connection, a direct wireless connection, and / or other communication links.

[0031] The external device interface 112 can provide a communication interface to enable the in-vehicle computing system to communicate with a mobile device associated with the driver's contacts. For example, the external device interface 112 can enable a phone call to be established with a mobile device associated with the driver's contacts and / or a text message (e.g., short message service (SMS), multimedia message service (MMS), etc.) to be sent to the mobile device (e.g., via a cellular communication network). The external device interface 112 can additionally or alternatively provide a wireless communication interface to enable the in-vehicle computing system to synchronize data with one or more devices in the vehicle (e.g., the driver's mobile device), as described in more detail below.

[0032] One or more applications 144 may operate on the mobile device 142. As an example, the mobile device application 144 may be operated to aggregate user data regarding the user's interaction with the mobile device. For example, the mobile device application 144 may aggregate data regarding: music playlists listened to by the user on the mobile device, phone call records (including the frequency and duration of phone calls answered by the user), location information (including locations the user frequents and the amount of time spent at each location), and the like. The data collected may be transmitted by the application 144 over the network 160 to the external device interface 112. Additionally, a specific user data request may be received at the mobile device 142 via the external device interface 112 from the in-vehicle computing system 109. The specific data request may include a request for determining the user's geographical location, the ambient noise level and / or music genre at the user's location, the ambient weather conditions (temperature, humidity, etc.) at the user's location, and the like. The mobile device application 144 may send control instructions to components of the mobile device 142 (e.g., microphone, amplifier, etc.) or other applications (e.g., navigation application) to enable collection of the requested data on the mobile device or to effect the requested adjustments to the components. The mobile device application 144 may then relay the information collected back to the in-vehicle computing system 109.

[0033] Similarly, one or more applications 148 may operate on the external service 146. As an example, the external service application 148 may be operated to aggregate and / or analyze data from multiple data sources. For example, the external service application 148 may aggregate data from one or more social media accounts of the user, data from the in-vehicle computing system (e.g., sensor data, log files, user input, etc.), data from Internet queries (e.g., weather data, POI data), and the like. The data collected may be transmitted to another device and / or analyzed by the application to determine the context of the driver, vehicle, and environment and perform actions based on the context (e.g., request / send data to other devices).

[0034] The vehicle control system 130 may include controls for controlling aspects of the various vehicle systems 131 involved in different in-vehicle functions. These may include, for example, aspects of the vehicle audio system 132 for reducing road noise in the passenger compartment of the vehicle 102, aspects of the climate control system 134 for meeting the heating or cooling needs of the vehicle occupants in the passenger compartment, and aspects of the telecommunication system 136 for enabling the vehicle occupants to establish a telecommunication connection with others.

[0035] The audio system 132 may include one or more sound reproduction devices, including electromagnetic transducers such as one or more speakers 135. The vehicle audio system 132 may be passive or active, such as by including a power amplifier. In some examples, the in-vehicle computing system 109 may be the sole audio source for the sound reproduction devices, or there may be other audio sources connected to the audio reproduction system (e.g., an external device such as a mobile phone). Any such connection of an external device to the audio reproduction device may be analog, digital, or any combination of analog and digital technologies. As further described with respect to Figure 8 the passenger compartment of a vehicle (e.g., vehicle 102) may be divided into different zones. Each zone may have a dedicated set of one or more speakers 135 located therein to produce an audio output for the corresponding zone. Additionally or alternatively, one or more speakers 135 of the audio system 132 may be shared by two or more zones, e.g., by being placed between zones and producing an audio output for the two zones.

[0036] The vehicle control system 130 may also include controls for adjusting the settings of various vehicle control elements 161 (or vehicle controls, or vehicle system control elements) related to the engine and / or auxiliary elements within the passenger compartment of the vehicle, such as one or more steering wheel controls 162 (e.g., steering wheel-mounted audio system controls, cruise controls, windshield wiper controls, headlight controls, turn signal controls, etc.), dashboard controls, microphones, accelerator / brake / clutch pedals, shifter levers, door / window controls located in the driver's door or passenger's door, seat controls, passenger compartment light controls, audio system controls, passenger compartment temperature controls, etc. The vehicle control elements 161 may also include internal engine and vehicle operation controls (e.g., engine controller modules, actuators, valves, etc.) that are configured to receive instructions via the vehicle's CAN bus to change the operation of one or more of the engine, exhaust system, transmission, and / or other vehicle systems. The control signals may also control the audio output at one or more speakers 135 of the vehicle audio system 132. For example, the control signals may adjust audio output characteristics such as volume, equalization, audio image (e.g., an audio signal configuration that produces an audio output that appears to the user to originate from one or more defined locations), audio distribution among multiple speakers, etc. For example, as further described herein with respect to Figures 2 to 10 the audio output characteristics of the zones of the vehicle may be adjusted to reduce road noise in the one or more zones in response to determining that a user is located in the one or more zones of the vehicle. Similarly, the control signals may control the vents, air conditioners, and / or heaters of the climate control system 134. For example, the control signals may increase the delivery of cooled air to a particular section of the passenger compartment.

[0037] Control elements located outside the vehicle (e.g., controllers for safety systems) can also be connected to the in-vehicle computing system 109, such as via the vehicle-to-vehicle system communication module 122. Control elements of the vehicle control system 130 can be physically and permanently located on and / or in the vehicle for receiving user input. In addition to receiving control instructions from the in-vehicle computing system 109, the vehicle control system 130 can also receive input from one or more external devices 150 operated by the user (such as from the mobile device 142). This allows aspects of the vehicle system 131 and the vehicle control element 161 to be controlled based on user input received from the external device 150.

[0038] The in-vehicle computing system 109 can also include one or more antennas 106. The in-vehicle computing system can obtain broadband wireless Internet access via the antenna 106 and can further receive broadcast signals, such as radio, television, weather, traffic, etc. The in-vehicle computing system 109 can receive positioning signals, such as GPS signals, via the antenna 106. The in-vehicle computing system can also receive wireless commands via radio frequency (RF) (such as via the antenna 106) or via infrared or by other means through a suitable receiving device. In some embodiments, the antenna 106 can be included as part of the audio system 132 or the telecommunications system 136. Additionally, the antenna 106 can provide AM / FM radio signals to the external device 150 (such as to the mobile device 142) via the external device interface 112.

[0039] The user can control one or more elements of the in-vehicle computing system 109 via the user interface 118. The user interface 118 can include a graphical user interface presented on a touch screen and / or a display screen, and / or user-actuated buttons, switches, knobs, dials, sliders, etc. For example, user-actuated elements can include steering wheel controls, door and / or window controls, dashboard controls, audio system settings, climate control system settings, etc. The user can also interact with one or more applications of the in-vehicle computing system 109 and the mobile device 142 via the user interface 118. In addition to receiving the user's vehicle setting preferences on the user interface 118, the vehicle settings selected by the vehicle control system 130 can also be displayed to the user on the user interface 118. Notifications and other messages (such as received messages) as well as navigation aids can be displayed to the user on the display screen of the user interface. Responses to user preferences / information and / or to the presented messages can be executed via user input to the user interface.

[0040] Conventional RNC systems can use microphones and speakers (e.g., microphone 103, the microphone of the audio system 132, speaker 135) to detect and reduce road noise present in the passenger compartment of a vehicle. Conventional RNC systems can additionally or alternatively use accelerometers to measure vibrations associated with road noise. However, conventional RNC systems face challenges when attempting to reduce high-frequency noise (e.g., 400 Hz or above) in the passenger compartment. Road noise above 400 Hz is mostly generated by the interaction of the drive wheel tire tread with the road surface. Some noise is generated by the radiation of tire tread and sidewall vibrations (e.g., the rim of the drive wheel), while other road noise is generated by aerodynamic interactions near the tire footprint. Compared with conventional RNC systems, one or more microphones of the HF-RNC system can be feedforward microphones, which can be placed outside the vehicle (e.g., on and / or near the drive wheels of the vehicle), and can be configured to detect road noise outside the vehicle, and thus detect road noise outside the vehicle before the road noise reaches the passenger compartment. Similar to feedforward accelerometers, the accuracy of road noise measurement can depend on the positioning of the feedforward microphone at a location where it can capture the most airborne noise sources. The feedforward microphone can also capture other aerodynamic noise generated in the vehicle body bottom.

[0041] Due to strict environmental factors and microphone self-noise, it may be difficult to install conventional feedforward microphones outside the vehicle to measure external vehicle noise. Additionally, when the microphone is positioned near a rotating drive wheel, due to direct exposure to high-speed airflows, the microphone may deteriorate due to dust and chemicals, and the noise caused by wind turbulence may contaminate the microphone signal. Installing a microphone windscreen can partially mitigate this problem; however, this may not be a long-term solution as the windscreen itself may deteriorate. Feedforward microphone sensors configured for high-frequency HF-RNC can meet the strict automotive environmental requirements while minimizing wind noise interference. Such microphones may be more suitable for RNC over a wide frequency range, and more specifically for HF-RNC (e.g., up to, equal to, or greater than 400 Hz).

[0042] Figure 2 An exemplary block diagram of a high-frequency road noise cancellation (HF-RNC) system 200 is shown. The HF-RNC system 200 can be implemented in different types of vehicles, such as vehicles powered by one or more electric motors and / or vehicles using an internal combustion engine as a power source. For example, the HF-RNC system 200 can be implemented as Figure 1 a part of the on-vehicle computing system 109 of the vehicle 102. The HF-RNC system 200 can include a plurality of elements communicatively coupled. The elements can be coupled by wired and / or wireless connections. As Figure 2As shown, the arrows between components indicate that information can be sent from a first component to a second component in the direction of the arrow, as further described herein.

[0043] The HF-RNC system 200 may include a feedforward sensor 202 configured to measure vibration and noise sources related to road noise. In some examples, a feedforward microphone 206 may be combined with an accelerometer 204 to form a hybrid feedforward sensor unit (collectively referred to as the feedforward sensor 202). The feedforward sensor 202 may consist of one or more of each of the accelerometer 204 and the microphone 206. Additionally or alternatively, the HF-RNC system 200 may include more than one feedforward sensor 202. The microphone 206 may be positioned close to the vehicle's tires (e.g., drive wheels), where most airborne noise sources are generated. For example, each microphone 206 may be positioned outside the vehicle, such as at the vehicle's suspension knuckle, wheel well, subframe, and / or body bottom. The microphone 206 and the accelerometer 204 may continuously capture road noise during vehicle operation (whether the vehicle is moving or stationary). For example, the feedforward sensor 202 may capture the sound profile of road noise, including the frequency of the road noise.

[0044] The feedforward sensor 202 may send information (e.g., road noise measurements, sound profiles) to the embedded system 208 of the HF-RNC system 200. The embedded system 208 includes a digital signal processing (DSP) module 210, a low-latency signal processing module 212, a low-latency filter (e.g., AA filter) 214, and a power management integrated circuit (power IC) 216. In some examples, the embedded system 208 may be included in the processor of an in-vehicle computing system (such as Figure 1 the in-vehicle computing system 109). As further described herein with respect to Figure 11 the embedded system 208 may be configured with instructions stored in non-volatile memory that, when executed, provide high-frequency road noise cancellation for at least a portion of the vehicle's cabin. The feedforward sensor 202 may send information to the embedded system 208 in real time, that is, while the feedforward sensor 202 captures road noise measurements.

[0045] The embedded system 208 may also receive information from the cabin microphone 228 and the head tracking device 234. The cabin microphone 228 may include a headrest microphone 230 and / or a headliner microphone 232. For example, the cabin microphone 228 may be located within or on the seat headrest, as described herein with respect to Figure 6As an example, the headrest microphone 230 can be the error microphone of the HF-RNC system. The cabin microphone 228 can be configured to capture the ambient noise within the vehicle cabin. One or more cabin microphones 228 can be configured for each seat within the cabin. Thus, the cabin microphone 228 can be configured to capture the ambient noise in the area where the cabin microphone 228 is located. For example, the cabin microphone 228 can be configured to capture the ambient noise that an occupant sitting on a chair in the area where the cabin microphone 228 is located may experience.

[0046] The head tracking device 234 includes an occupant head position tracker 236 and a seat locator 238. The occupant head position tracker 236 can include one or more of a camera (such as a stereo camera) and an artificial intelligence (AI) algorithm, the AI algorithm being configured to track the position of the occupant's head, and more specifically, the position of the occupant's ears. The seat locator 238 can be a position sensor integrated into each seat of the cabin. In some examples, the seat locator 238 can be included in the AI algorithm and can be configured to track the position of the headrest speaker 220. In some examples, one or more seats of the cabin can be modular (e.g., can be located at different positions within the cabin), and the seat locator 238 can track and report the current position of the corresponding seat to the embedded system 208. In some embodiments, the occupant head position tracker 236 and the seat locator 238 can be integrated into a single device (e.g., the head tracking device 234), the single device being configured to track the occupant ear position and the seat position. For example, and as further described herein, a stereo camera located within the vehicle cabin can be used to capture a three-dimensional image of the cabin and identify the occupant ear position and the seat position of the seat on which the occupant is sitting. Additionally or alternatively, the head tracking device 234 can track the position of the headrest microphone 230.

[0047] The embedded system 208 can be configured with instructions stored in non-volatile memory that, when executed, generate a road noise cancellation signal for at least a portion of the vehicle's passenger compartment. The embedded system 208 uses the information received from the feedforward sensor 202 to identify road noise outside the vehicle's passenger compartment, uses the information received from the head tracking device 234 to identify the location of the user (e.g., the zone where the user is located and the location of the occupant's ears within the zone), and uses the information from the cabin microphone 228 to identify the ambient road noise within the zone where the occupant is located and, additionally or alternatively, serves as an error microphone. The embedded system 208 executes instructions to process the digital signals of the road noise from the feedforward sensor 202 and the cabin microphone 228 (e.g., using the digital signal processing module 210) and applies one or more low-latency filters 214 thereto. The low-latency signal processing module 212 and the power management integrated circuit 216 can be used to reduce the amount of data to be processed and generate a digital output signal to reduce the ambient road noise within the zone in real time and / or near real time. For example, the sampling rate for generating the noise cancellation signal can be greater than or equal to 2 kHz.

[0048] The embedded system 208 can send information (e.g., the noise cancellation signal) to the vehicle speaker system 218. The vehicle speaker system 218 can include multiple types of speakers to control the ambient road noise within a broadband frequency range, including headrest speakers 220, door speakers 222, center speakers 224, and subwoofers 226. In some embodiments, the vehicle speaker system 218 can include multiple speakers of each type. The vehicle speaker system 218 also provides information to the cabin microphone 228. For example, one or more of the microphones in the cabin microphone 228 can detect the sound output by one or more of the speakers of the vehicle speaker system 218. In this way, a feedback loop is established between the embedded system 208 and the vehicle speaker system 218 to determine whether the digital signal output by the embedded system 208 sufficiently reduces and / or cancels the ambient road noise within the zone.

[0049] Figure 3FIG. 300 is shown, which shows the coherence between the driver's outer ear microphone and the feedforward signal measured at a single location as a function of frequency. The vibration and acoustic signals are measured at a common location using each of the accelerometer 204 and the microphone 206. The accelerometer signal 302 corresponds to the coherence with the accelerometer 204 of the feedforward sensor. The microphone signal 304 corresponds to the coherence with the microphone of the feedforward sensor. As shown in FIG. 300, the coherence of the accelerometer signal 302 decreases above 500 Hz, while the coherence of the microphone signal 304 increases above 500 Hz. In this way, the feedforward microphone can help capture the noise in the high frequency range (e.g., above 500 Hz and up to 1 kHz) that is not fully captured by the feedforward accelerometer, in order to effectively actively cancel the high frequency noise. In addition, a feedforward sensor (e.g., feedforward sensor 202) that combines both the feedforward microphone and the feedforward accelerometer can provide the unexpected benefit of capturing vehicle noise in a wideband frequency range.

[0050] Conventional RNC systems can use a low sampling rate (e.g., 1.5 kHz or 2 kHz) to create a digital signal configured to reduce road noise signals (e.g., noise cancellation signals). The low sampling rate can generally reduce, but may not fully eliminate, the ambient road noise inside the vehicle's cabin. Increasing the sampling rate of the road noise measurement (e.g., obtaining more samples from the continuous signal) can increase the similarity between the measured signal (e.g., road noise) and the digital signal.

[0051] The HF-RNC system 200 uses a higher sampling rate compared to conventional RNC systems, where the HF-RNC system 200 described herein can generate a noise cancellation signal at a sampling rate greater than 2 kHz. In another example, the sampling rate of the HF-RNC system 200 can be greater than or equal to 3 kHz. Increasing the sampling rate can reduce the delay by reducing the gap between samples. The increased sampling rate can also use low-delay AA filters and buffering techniques (which further reduce the delay). The sampling rate of the HF-RNC system 200 can be increased to the maximum sampling rate achievable by the available memory of the computing system (e.g., embedded system 208) and the microprocessor without interlocked pipelined stages (MIPS). In terms of processing requirements, low delay can be prioritized over digital signal processing time.

[0052] In addition, conventional RNC systems may use only door speakers and subwoofers for noise cancellation. The HF-RNC system described herein can use headrest speakers in addition to door speakers and subwoofers.

[0053] The latency of an entire vehicle active noise cancellation (ANC) system (e.g., such as the HF-RNC system 200) can depend on the digital signal processing time and the propagation time of the secondary sound pressure wave in air. The embedded system of the HF-RNC system described herein can use a conventional DSP. For example, the HF-RNC system can use a high-bandwidth digital A2B bus to achieve extremely low-latency data transmission. Within the allowable memory and MIPs of the system, the algorithm sampling rate can be increased. Increasing the sampling rate in this way may help reduce the latency of the generated noise cancellation signal.

[0054] Additional latency reduction can be achieved by positioning the speaker close to the occupant's ear. Thus, headrest speakers can be used in the HF-RNC system described herein to reduce the air time latency. For example, the air time latency of a conventional door speaker may be greater than 3 milliseconds (ms). Figure 4 A graph 400 comparing the impulse responses over time from a door speaker versus a headrest speaker is shown. Curve 402 corresponds to the impulse response of the headrest speaker (e.g., headrest speaker 220), and curve 404 corresponds to the impulse response of the door speaker (e.g., door speaker 222). As indicated by arrow 406, the headrest speaker output reaches the occupant's ear more than 3 milliseconds earlier than the door speaker output. In this way, using the headrest speaker to at least partially generate the noise cancellation signal can help reduce the latency of the HF-RNC system and more effectively cancel high-frequency noise.

[0055] Another benefit of the headrest speaker can be that the headrest speaker provides a flat response over a broadband frequency range. Figure 5 A graph 500 comparing the frequency response of a headrest speaker (e.g., headrest speaker 220) with the frequency response of a door speaker (e.g., door speaker 222) is shown. The first curve 502 corresponds to the frequency response of the headrest speaker, and the second curve 504 corresponds to the frequency response of the door speaker. The door speaker response shows many peaks and valleys, which means it is subject to cavity modes and limits the range of HF-RNC system performance robustness. When the frequency response changes drastically, the desired and / or sufficient noise cancellation may not occur, as shown in the case of the door speaker. In particular, above 400 Hz, graph 500 shows multiple valleys and low noise cancellation efficiency for the door speaker. Meanwhile, the headrest speaker shows a relatively flat response over a broadband frequency range, which can help the HF-RNC algorithm achieve the desired noise cancellation performance.

[0056] Typical vehicle headrest speakers generate noise above 150 Hz. It is unrealistic to expect headrest speakers to cover the entire RNC frequency range. Therefore, the HF-RNC system also uses conventional door speakers and subwoofers to extend the bandwidth of the RNC speaker output. For example, when headrest speakers (e.g., from the right side of the headrest and the left side of the headrest), door speakers, and subwoofers are all included in the HF-RNC system and used to generate noise cancellation signals, it may be desirable (e.g., maximum noise cancellation can be performed).

[0057] Figure 6 An example of a headrest noise cancellation system 600 is shown, which can be Figure 2 part of the HF-RNC system 200 as briefly described above. The headrest noise cancellation system 600 includes a headrest microphone 602 and a headrest speaker 604. The headrest microphone 602 can be an example of the headrest microphone 230, and the headrest speaker 604 can be an example of the headrest speaker 220. The headrest noise cancellation system 600 can be physically coupled to a seat 606 of a vehicle (e.g., Figure 1 vehicle 102). The seat 606 can include a backrest 612 positioned to contact the back of an occupant 610 and a headrest 608 positioned to contact the head of the occupant 610. The headrest noise cancellation system 600 can be physically coupled to the headrest 608. In some examples, the headrest noise cancellation system 600 can protrude from the side of the headrest 608, as Figure 6 shown. In alternative examples, the headrest noise cancellation system 600 can be partially or fully embedded within the headrest 608 or the backrest 612. In some examples, the headrest microphone 602 and the headrest speaker 604 can be included in a shared housing.

[0058] Conventional RNC systems may use virtual microphone technology in combination with headliner microphones. Headliner microphones can include microphones located in front of the occupant (e.g., relative to the direction of travel of the vehicle). For example, headliner microphones can be located in the instrument panel of the vehicle and / or near the steering wheel of the vehicle. Headliner microphones can be separate and physically distinct from headrest microphones such as the headrest microphone 602.

[0059] For example, virtual microphone techniques can be used to overcome small dead zones. Conventional RNC systems may use headliner microphones to estimate the noise at the occupant's ear. This can significantly mitigate physical microphone packaging limitations in production vehicles and improve noise cancellation above 150 Hz. However, coherent signals from physical cabin microphones are still used to virtually sense the noise at the occupant's ear. Due to complex cabin acoustic characteristics, it can be challenging to obtain coherent noise signals above 350 Hz from the headliner microphone to estimate the noise at the occupant's ear. The HF-RNC system described herein (e.g., which includes the headrest noise cancellation system 600) can use both the headliner microphone and the headrest microphone 602. Physical cabin microphones near the automotive seat headrest, such as the headrest microphone 602, can provide acceptable coherence for the noise at the occupant's ear over a wide frequency range.

[0060] The desired location of the cabin microphone (e.g., cabin microphone 228), also referred to herein as the "headrest microphone," can be determined based on a detailed location survey and subsequent virtual microphone algorithm simulations. The headrest physical microphone in the HF-RNC system described herein can contribute the majority of the noise detection to the virtual microphone algorithm. For example, the headrest microphone can contribute 50% or more of the noise detection to the virtual microphone algorithm. However, for certain noise content, the headliner physical microphone can provide additional coherence. Thus, when both the roof microphone and the headrest microphone are used in virtual microphone techniques, the desired (e.g., most accurate) noise level can be detected. In some embodiments, the headrest microphone can be a digital microphone.

[0061] Figure 7 A graph 700 is shown that compares the noise measured directly at the occupant's ear with the noise at the occupant's ear estimated by virtual microphone techniques using both the headrest microphone (e.g., headrest microphone 602) and the headliner microphone. The first curve 702 corresponds to the measured noise at the ear, and the second curve 704 corresponds to the estimated noise at the ear. As shown in graph 700, the estimated noise approximately matches the measured noise up to 1 kHz, and the deviation (e.g., separation) between the noise detection capabilities starts to increase from approximately 575 Hz.

[0062] As regarding Figure 6Briefly described, a vehicle with an HF-RNC system can have one or more desired quiet zones where road noise can be actively cancelled using the HF-RNC system. When the ears of an occupant are within a quiet zone, the occupant can experience a quieter ride. The size of the quiet zone can be determined by a variety of factors, including the frequency range of the noise source, the sound field, and the number of secondary sources. As the frequency increases, the wavelength decreases, which results in a smaller quiet zone size. In this paper, the quiet zone (ZoQ) is defined as the zone where the sound attenuation is at least 10 dB. Generally, the spatial range of a local active control system (e.g., a headrest noise cancellation system 600 mounted on a single vehicle seat) is about one-tenth of the wavelength.

[0063] The ZoQ of the high-frequency ANC system is relatively small. Therefore, in order to maintain sufficient noise cancellation performance regardless of the occupant's body size and movement, the second path information can be updated based on the positions of the occupant's ears and the speakers. The HF-RNC system described in this paper includes an AI-based head tracking system configured to track the positions of the occupant's ears and the headrest speakers. The AI-based head tracking system uses a stereo depth camera and a face detection AI algorithm to detect the occupant's ears and speakers, and uses parallax to calculate the relative distance between the ears and the speakers. The three-dimensional coordinates of the inner ears and the headrest speakers of the driver and the passenger (e.g., collectively referred to as the occupant) can be measured using a single head tracking system.

[0064] Figure 8 An illustration 800 shows the interior of a vehicle 810 configured with an HF-RNC system (e.g., HF-RNC system 200) and the path of an AI-based head tracking system (e.g., head tracking device 234). The AI-based head tracking system can include a stereo depth camera 802 to continuously track the positions of the occupant's ears and the speakers and adjust the predicted second path information to maintain the cancellation performance regardless of the occupant's position. The AI head tracking system can track facial features and can also be configured to identify the three-dimensional position of the occupant's ears based on the facial features. The stereo depth camera 802 can be located on or within the dashboard 808 of the vehicle 810. Other positions of the stereo depth camera 802 are also considered. In some examples, the head tracking system can include more than one stereo depth camera 802. In additional examples, a stereo depth camera can be provided for each potential occupant of the vehicle. The AI-based head tracking system can detect the positions of the occupant's ears 804 and the headrest speakers 806, and the system can change the second path, including: the path P from the speakers to the cabin microphones (e.g., the roof lining microphone and the headrest microphone), the path V from all the speakers to the virtual microphone, and the path PV from the cabin microphones to the virtual microphone corresponding to the detected positions of the occupant's ears and the headrest speakers.

[0065] Figure 9 FIG. 900 is a block diagram showing an exemplary algorithm of an HF-RNC system. The HF-RNC algorithm may include a first path 904 having a transfer function P(z), where the transfer function P(z) represents the transfer characteristics of a first signal path between a noise source 902 and the position of an occupant. The noise source 902 may also be measured at a reference signal 906. The reference signal 906 may come from a feedforward sensor (e.g., feedforward sensor 202). The HF-RNC may also include a filter 908 having a transfer function W(z). In addition, the HF-RNC may include a least mean square (LMS) filter 910. Further, the HF-RNC may include an actual second path 912 having a transfer function Se(z). The transfer function Se(z) may represent the signal path between one or more speakers 914 (e.g., vehicle speaker system 218) that play the filtered signal from the transfer function W(z) and the positions of a physical error microphone 916 and a virtual error microphone 918.

[0066] The reference signal 906 may represent the noise source 902 for the filter 908. The filter 908 may apply an amplitude and a phase shift to the reference signal 906 to output a filtered signal that will be played via one or more speakers 914. For example, the amplitude and / or phase shift (e.g., 180°) may be adjusted such that the reference signal 906 is convolved with the filter 908 and output as a filtered signal through the speakers, thereby achieving cancellation at the microphone position. The speaker output may be transmitted via the actual second path 912 and supplied to a physical second path 936 having a transfer function Sp(z) and a virtual second path 924 having a transfer function Sv(z).

[0067] The HF-RNC algorithm may combine the filtered signal via the second path 912 with the noise source 902 via the first path 904 to produce an input signal to the physical error microphone 916 (e.g., headrest microphone 602), which is represented by a first summing node 920 that performs a summing operation in the HF-RNC algorithm to produce an input signal that is transformed into a first error signal 922. The error signal 922 may be combined with the filtered signal output by the filter 908 via the physical second path 936 to form an input to a path H(z) 926, which is represented by a second summing node 928. The path H(z) 926 may correspond to the ear position of the occupant and the speaker position determined by a head tracking system such as a head tracking device 234. For example, the path H(z) may be adjusted using the monitored ear position of the occupant from the head tracking device 234. The adjustment may be monitored at a high sampling rate (e.g., greater than 2 kHz) and adjusted with low latency.

[0068] The output signal of path H(z) 926 can be combined with the filtered signal output by W(z) via the virtual second path Sv(z) to form the input to one or more virtual error microphones 918, which is represented by the third summing node 930. One or more virtual error microphones can convert the input into a second error signal 932. The LMS filter 910 and the filtered signal 908 can be modified based on the second error signal 932 through an algorithm. In addition, the HF-RNC algorithm can update the LMS filter 910 and the filtered signal 908 based on the stored second path 934 via the transfer function Se'(z) generated from the reference signal 906.

[0069] Figure 10 Chart 1000 is shown, which shows the electric vehicle driver seat noise cancellation performance at a vehicle speed of 50 miles per hour (mph) in decibels per hertz (dB / Hz) when the HF-RNC system is on (as shown in graph 1004) and when the HF-RNC system is off (as shown in graph 1002). The data collected shows the driver seat noise cancellation performance (driver outer ear HR-RNC noise cancellation performance) at 50 mph on a public rough road. As shown in chart 1000, noise cancellation up to 1 kHz is achieved. Peak noise cancellation is observed to exceed 10 dB at low frequencies, and up to 6 dB at peaks above 500 Hz.

[0070] Figure 11 is a flowchart of a method 1100 for active road noise cancellation. The method 1100 described herein can be implemented in a vehicle system including a high-frequency road noise cancellation (HF-RNC) system, such as Figure 2 the HF-RNC system 200 and Figure 1 the vehicle 102. Thus, the method 1100 can be stored as executable instructions in a non-transitory memory (e.g., non-volatile storage device 108 and / or non-volatile memory 119B) and executed by a processor of an embedded system (e.g., operating system processor 114 and / or interface processor 120). The method 1100 can be an example of an algorithm implementing the HF-RNC system, such as Figure 9 the algorithm shown in block diagram 900.

[0071] At 1102, the method 1100 includes monitoring the position of the occupant's ears using a head tracking device (e.g., head tracking device 234). As described herein, the head tracking device can use a stereo depth camera and a face detection AI algorithm to detect the occupant's ears and the headrest speakers corresponding to the occupant, and use parallax to calculate the relative distance between the ears and the speakers. The three-dimensional coordinates of the inner ears and the headrest speakers of the driver and passengers (e.g., collectively referred to as occupants) can be measured using a single head tracking device.

[0072] At 1104, method 1100 includes capturing airborne noise sources using a feedforward sensor (e.g., feedforward sensor 202) and a cabin microphone in the area where the occupant's ear is located. The feedforward sensor may include a feedforward accelerometer and a feedforward microphone. The feedforward microphone may be positioned on the outer surface of the vehicle, as described above. Capturing airborne noise via the feedforward sensor may provide a reference signal for the HF-RNC algorithm. The cabin microphone may include a headrest microphone, such as headrest microphone 602. In additional examples, the cabin microphone may also include a headliner microphone. The cabin microphone may include one or more physical error microphones for the HF-RNC algorithm.

[0073] At 1106, method 1100 includes updating acoustic path information based on the occupant ear position and the speaker position in the area. The updated acoustic path information may include applying a path function to the signal output by the physical error microphone. The path function may be used to generate an error signal for updating the physical and virtual acoustic second paths.

[0074] At 1108, method 1100 includes generating a noise cancellation signal using a sampling rate greater than 2 kHz. In some examples, the sampling rate may be greater than or equal to 3 kHz. A low-latency anti-aliasing (AA) filter may be used to generate the noise cancellation signal.

[0075] At 1110, method 1100 includes outputting the noise cancellation signal via a vehicle speaker system in the area where the occupant's ear is located to at least partially reduce the road noise level in the area. The vehicle speaker may be Figure 2 an example of vehicle speaker system 218. Outputting the noise cancellation signal to the vehicle speaker system may include outputting the noise cancellation signal to a headrest speaker (e.g., headrest speaker 604) at 1112. Optionally, outputting the noise cancellation signal to the vehicle speaker system may include outputting the noise cancellation signal to one or more additional speakers (including one or more of door speakers, subwoofers, and center speakers) at 1114. The one or more additional speakers may be located inside or outside the area of the occupant ear position. The noise cancellation signal output at 1114 may be an additional noise cancellation signal output simultaneously with the noise cancellation signal output by the headrest speaker. Method 1100 returns.

[0076] In this way, a road noise cancellation function can be provided based on the position of the vehicle occupant, and the road noise cancellation function can cancel road noise with frequencies up to 1 kHz and above 1 kHz. By using, in addition to the feedforward microphones and speakers (such as door speakers, center speakers, etc.) located in the passenger compartment of the vehicle, also the microphones and speakers in the area where the occupant is located (such as headrest microphones and speakers), the HF-RNC system can cancel high-frequency road noise more effectively and specifically compared to traditional RNC systems.

[0077] The present disclosure provides support for a method for high-frequency road noise cancellation in a vehicle system, the method including using a head tracking device to monitor the position of the occupant's ears; using a feedforward microphone and a headrest microphone in the area of the occupant's ears to capture an airborne noise source; updating acoustic path information based on the position of the occupant's ears and the position of the speakers in the area; generating a noise cancellation signal at a sampling rate greater than 2 kHz; and outputting the noise cancellation signal via a headrest speaker near the area of the occupant's ears to at least partially reduce the road noise level in the area. In a first example of the method, the method further includes: outputting an additional noise cancellation signal via one or more additional speakers inside or outside the area of the occupant's ears. In a second example (optionally including the first example) of the method, the headrest microphone is coupled to the seat headrest and / or the backrest of the seat of the vehicle system. In a third example (optionally including one or both of the first and second examples) of the method, the head tracking device includes a stereo camera configured to capture three-dimensional images of the occupant's ears and the headrest speaker. In a fourth example (optionally including one or more or each of the first to third examples) of the method, the headrest speaker and the headrest microphone are mounted in a shared housing. In a fifth example (optionally including one or more or each of the first to fourth examples) of the method, the head tracking device uses artificial intelligence to identify and track facial features including the ears. In a sixth example (optionally including one or more or each of the first to fifth examples) of the method, generating the noise cancellation signal includes using a low-latency anti-aliasing filter.

[0078] The present disclosure also provides support for a vehicle system, the vehicle system including: a feedforward sensor, the feedforward sensor including an accelerometer and a microphone; a vehicle speaker system, the vehicle speaker system including headrest speakers, door speakers, a center speaker, and a subwoofer; a cabin microphone, the cabin microphone including a headrest microphone and a headliner microphone; a head tracking device configured to detect the position of an occupant's ears and the seat position; an embedded system, the embedded system including a digital signal processing system, a low-latency signal processing system, a low-latency filter, and a power management integrated circuit; and instructions stored on a non-volatile memory of the embedded system, wherein the computer-readable instructions, when executed, cause the embedded system to: monitor the position of the occupant's ears using the head tracking device; capture airborne noise using the feedforward sensor and the headrest microphone located near the area of the occupant's ear position; update acoustic path information based on the occupant's ear position and the speaker position in the area; generate a noise cancellation signal using a sampling rate greater than 2 kHz; and output the noise cancellation signal via the headrest speaker located near the area of the occupant's ear position to at least partially reduce the road noise level in the area. In a first example of the system, the headrest microphone is coupled to the headrest and / or the backrest of the seat of the vehicle system. In a second example of the system (optionally including the first example), the head tracking device includes a stereo camera configured to capture three-dimensional images of the occupant's ears and the headrest speakers. In a third example of the system (optionally including one or both of the first and second examples), the headrest speaker and the headrest microphone are mounted in a shared housing. In a fourth example of the system (optionally including one or more or each of the first to third examples), the noise cancellation signal reduces noise up to 1 kHz. In a fifth example of the system (optionally including one or more or each of the first to fourth examples), the instructions include capturing airborne noise using the headliner microphone and the headrest microphone. In a sixth example of the system (optionally including one or more or each of the first to fifth examples), the instructions include outputting the noise cancellation signal via the door speakers, the center speaker, and the subwoofer in addition to the headrest speakers.

[0079] The present disclosure also provides support for a high-frequency road noise cancellation system for a vehicle, the high-frequency road noise cancellation system comprising: a feedforward sensor, the feedforward sensor including a feedforward microphone; a vehicle speaker system, the vehicle speaker system including headrest speakers; a head tracking device configured to track the position of an occupant's ear and the position of a headrest microphone; a cabin microphone, the cabin microphone including a headrest microphone; an embedded system including a digital signal processing module and instructions stored on a non-volatile memory, the instructions when executed causing the embedded system to: monitor the position of the occupant's ear using the head tracking device; capture airborne noise sources using the feedforward sensor and the cabin microphone; update acoustic path information based on the position of the occupant's ear; generate a noise cancellation signal using the updated acoustic path information; and output the noise cancellation signal using the vehicle speaker system. In a first example of the system, the cabin microphone is an error microphone, and the airborne noise captured by the cabin microphone adjusts a filter used to generate the noise cancellation signal. In a second example of the system (optionally including the first example), the instructions include adjusting the filter based on the output of the error microphone modified by the monitored position of the occupant's ear. In a third example of the system (optionally including one or both of the first and second examples), the instructions for updating the acoustic path information include updating a physical second path and a virtual second path. In a fourth example of the system (optionally including one or more or each of the first to third examples), the vehicle speakers further include one or more of door speakers, subwoofers, and center speakers. In a fifth example of the system (optionally including one or more or each of the first to fourth examples), the output of the vehicle speakers reaches the occupant's ear before the output of the door speakers.

[0080] The description of the embodiments has been presented for purposes of illustration and description. Appropriate modifications and variations can be effected in light of the above description or can be obtained by practicing the methods described. For example, unless otherwise stated, one or more of the methods described can be performed by suitable apparatus and / or combinations of apparatus. These methods can be performed by using one or more logic devices (e.g., processors) in conjunction with one or more additional hardware elements such as storage devices, memories, hardware network interfaces / antennas, switches, actuators, clock circuits, etc. to execute stored instructions. The methods described can be performed in various orders in addition to the order described herein, in parallel, and / or simultaneously. The systems described are exemplary in nature and can include additional elements and / or omit elements. The subject matter of the present disclosure includes all novel and non-obvious combinations and sub-combinations of the various systems and configurations and other features, functions, and / or properties disclosed.

[0081] As used in this application, an element or step recited in the singular and preceded by the word "a" or "an" should be understood as not excluding a plurality of the recited elements or steps, unless such exclusion is stated. Furthermore, a reference to "one embodiment" or "one example" of the present disclosure is not to be construed as excluding the existence of additional embodiments that also incorporate the recited features. The terms "first," "second," and "third," etc. are used merely as labels and are not intended to impose numerical requirements or a particular positional order on their objects. The appended claims particularly point out the subject matter regarded as novel and non-obvious from the foregoing disclosure.

Claims

1. A method for high frequency road noise cancellation in a vehicle system, comprising: Use head tracking devices to monitor occupant ear position; capturing airborne noise sources using a feedforward microphone and a headrest microphone in the area of ​​the occupant's ear location; updating acoustic path information based on the occupant's ear locations and speaker locations within the zone; generating a noise cancellation signal at a sampling rate greater than 2 kHz; as well as The noise cancellation signal is output via headrest speakers located near the zone where the occupant's ears are located to at least partially reduce a road noise sound level in the zone. 2 . The method of claim 1 , further comprising outputting additional noise cancellation signals via one or more additional speakers located inside or outside of the zone where the occupant's ears are located. 3 . The method of claim 1 , wherein the headrest microphone is coupled to a seat headrest and / or backrest of a seat of the vehicle system. 4 . The method of claim 1 , wherein the head tracking device comprises a stereo camera configured to capture three-dimensional images of the occupant's ears and headrest speakers.

5. The method of claim 1, wherein the headrest speaker and the headrest microphone are mounted in a shared housing.

6. The method of claim 1, wherein the head tracking device uses artificial intelligence to identify and track facial features including ears. The method of claim 1 , wherein generating the noise cancellation signal comprises using a low-delay anti-aliasing filter.

8. A vehicle system comprising: a feedforward sensor comprising an accelerometer and a microphone; A vehicle speaker system, the vehicle speaker system comprising a headrest speaker, a door speaker, a center speaker and a subwoofer; A compartment microphone, the compartment microphone comprising a headrest microphone and a roof lining microphone; a head tracking device configured to detect occupant ear position and seat position; An embedded system comprising a digital signal processing system, a low-latency signal processing system, a low-latency filter, and a power management integrated circuit; as well as Instructions stored on a non-volatile memory of the embedded system, wherein the computer readable instructions, when executed, cause the embedded system to: monitoring the position of the occupant's ears using the head tracking device; capturing airborne noise using the feed-forward sensor and the headrest microphone located near the area where the occupant's ears are located; updating acoustic path information based on the occupant's ear positions and the speaker positions within the zone; Generate a noise cancellation signal using a sampling rate greater than 2kHz; as well as The noise cancellation signal is output via the headrest speakers located proximate the zone of the occupant's ear locations to at least partially reduce a road noise sound level in the zone.

9. The vehicle system of claim 8, wherein the headrest microphone is coupled to a headrest and / or a backrest of a seat of the vehicle system. 10 . The vehicle system of claim 8 , wherein the head tracking device comprises a stereo camera configured to capture three-dimensional images of the occupant's ears and headrest speakers.

11. The vehicle system of claim 8, wherein the headrest speaker and the headrest microphone are mounted in a shared housing.

12. The vehicle system of claim 8, wherein the noise cancellation signal reduces noise up to 1 kHz.

13. The vehicle system of claim 8, wherein the instructions include capturing airborne noise using the headliner microphone and the headrest microphone.

14. The vehicle system of claim 8, wherein the instructions include outputting the noise cancellation signal via the door speakers, the center speaker, and the subwoofer in addition to the headrest speakers.

15. A high frequency road noise cancellation system for a vehicle, comprising: a feedforward sensor, the feedforward sensor comprising a feedforward microphone; a vehicle speaker system, the vehicle speaker system comprising a headrest speaker; a head tracking device configured to track the position of the occupant's ears and the position of the headrest microphones; A compartment microphone, wherein the compartment microphone comprises a headrest microphone; An embedded system, the embedded system comprising a digital signal processing module and instructions stored in a non-volatile memory, the instructions, when executed, causing the embedded system to: Using the head tracking device to monitor the position of the occupant's ears; capturing airborne noise sources using the feedforward sensor and the cabin microphone; updating acoustic path information based on the occupant ear position; generating a noise cancellation signal using the updated acoustic path information; as well as The noise cancellation signal is output using the vehicle speaker system.

16. The high frequency road noise cancellation system of claim 15, wherein the cabin microphone is an error microphone and airborne noise captured by the cabin microphone adjusts a filter used to generate the noise cancellation signal.

17. The high frequency road noise cancellation system of claim 16, wherein the instructions include adjusting the filter based on the output of the error sensor modified by the monitored occupant ear position.

18. The high frequency road noise cancellation system of claim 15, wherein the instructions to update the acoustic path information include updating a physical second path and a virtual second path.

19. The high frequency road noise cancellation system of claim 15, wherein the vehicle speaker system additionally includes one or more of door speakers, a subwoofer, and a center speaker.

20. The high frequency road noise cancellation system of claim 19, wherein the output of the vehicle speaker system reaches the occupant's ears before the output of the door speakers.

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