73 results about "Roadway noise" patented technology

A road noise cancellation (RNC) system is provided with at least one loudspeaker to project anti-noise sound within a passenger cabin of a vehicle in response to an anti-noise signal; and a controller. The controller is programmed to: determine a coherence value between a noise signal indicative of road induced noise and an error signal indicative of noise and the anti-noise sound within the passenger cabin; estimate a noise reduction value based on the coherence value; filter the noise signal and the error signal based on the estimated noise reduction value; and generate the anti-noise signal based on the filtered noise signal and the filtered error signal.

Techniques for automatic parameter tuning of active road noise cancellation systems are described herein. The system can automatically search for an optimal set of algorithm parameters based on recorded data. An active road noise cancellation algorithm and simulation can be embedded in an auto-differentiation framework, which allows gradients of the algorithm parameters to guide the automatic search and calculations of the algorithm parameters.

A method, an apparatus, a storage medium and a computer program product for noise prediction of a vehicle model. There is provided a method for noise prediction of a vehicle model, which includes: training a noise prediction model based on historical test data of the vehicle and corresponding historical road noise data; obtaining predictive road noise data by inputting test data of the vehicle model into a trained noise prediction model; and obtaining contributions of various parameters in the test data to the predictive road noise data by analyzing the predictive road noise data with a SHAP explaining module.

Described herein are methods and systems for a vehicle system which provide inbuilt road noise cancellation in the vehicle. In one or more embodiments, a method for road noise cancellation comprises using a head-tracking device to monitor an occupant ear position, capturing airborne noise using a feedforward microphone and a headrest microphone of a zone in which the occupant ear is positioned, updating acoustic path information according to the occupant ear position(s) and speaker position(s) within the zone, generating a noise cancellation signal using sampling rate greater than 2 kHz, and outputting the noise cancellation signal via a headrest speaker located near the zone in which the occupant ear is positioned to at least partially reduce a road noise sound level in the zone.

The invention discloses an automobile road noise processing method and device and a filter training method, and relates to the technical field of noise reduction, and the method comprises the steps: employing a preset multiphase analysis filter group to carry out the sub-band decomposition of an input time domain reference signal and a time domain error signal, and obtaining a sub-band reference signal and a sub-band error signal; updating a sub-band adaptive filter coefficient based on the sub-band reference signal and the sub-band error signal; performing sub-band synthesis on the updated sub-band adaptive filter coefficient by adopting a preset multi-phase synthesis filter bank to obtain an updated time domain adaptive filter coefficient; and processing a newly input time domain reference signal based on the updated time domain adaptive filter coefficient to obtain an anti-noise signal, and controlling road noise based on the anti-noise signal. According to the invention, the calculated amount of the automobile road noise control system is reduced, so that the requirement on the hardware computing power of the system is reduced.

Various implementations include audio systems and related approaches for providing road noise cancelation (RNC). Certain implementations include a method of training a machine learning (ML) based road noise cancelation (RNC) system for a vehicle, the method including: providing inputs to the ML based RNC system, the inputs obtained from: a set of ear-mounted microphones on a user of the vehicle, at least one transducer, an accelerometer, a set of cabin microphones in the vehicle, and a controller area network (CAN) bus, wherein the inputs from the set of ear-mounted microphones on the user approximate detected road noise by the user; adapting a set of parameters defining noise cancelation signals in the ML based RNC system based on the inputs; and generating noise cancelation signals for output by the at least one transducer based on the adapted set of parameters.

Various implementations include a method of training a road noise cancelation (RNC) system for a vehicle, including: providing inputs to RNC system, the inputs obtained from: a set of ear-mounted microphones on a user, at least one transducer, an accelerometer, a set of cabin microphones in the vehicle, and a controller area network (CAN) bus, the inputs from the set of ear-mounted microphones on the user approximating a signal detected by the ears of the user; adapting a set of parameters in the RNC system defining an estimated signal detected at respective ears of the user based on the inputs; and generating at least one of the following for input during an operating mode of the RNC system: estimated ear microphone signals based on the adapted set of parameters, or a set of projection filters for use in determining an estimated ear signal at the respective ears of the user.

The invention discloses an automobile road noise processing method and device, and relates to the technical field of noise reduction, and the method comprises the steps: dynamically determining a target filter group according to the obtained environment state information; respectively performing sub-band decomposition on the time domain reference signal and the time domain error signal according to the target multiphase analysis filter bank; and updating a sub-band adaptive filter coefficient based on the sub-band reference signal and the sub-band error signal, and performing sub-band synthesis on the updated sub-band adaptive filter coefficient by using a target multi-phase synthesis filter bank to obtain an updated time domain adaptive filter coefficient, and processing a newly input time domain reference signal based on the updated time domain adaptive filter coefficient to obtain an anti-noise signal, and controlling the road noise based on the anti-noise signal. The method and the device can adapt to environment change, avoid influence of the environment change on the noise reduction effect, and improve the stability of the noise reduction effect.

This invention discloses a method for predicting traffic conditions in large-scale urban road networks based on graph neural networks. The method first acquires road network topology and traffic time-series data, extracts road hierarchy information, and constructs graph data. The core lies in building a spatiotemporal graph neural network model that integrates dedicated road hierarchy components: a road hierarchy embedding layer maps discrete levels to continuous vectors to enhance feature semantics; a hierarchical global context module aggregates the global states of similar roads with linear complexity; and a dynamic cross-level attention module models the dynamic interaction dependencies between roads of different levels. This method suppresses noise interference from low-level roads through a hierarchical differentiation strategy and uses a separate weighted loss function for training. This invention effectively solves the problems of insufficient global perception, missing interaction modeling, and significant noise interference caused by neglecting road hierarchy semantics in existing technologies, significantly improving the accuracy and robustness of traffic condition prediction for large-scale urban road networks.

A hydrophone may be deployed in a wellbore to collect sounds that may be used to identify whether a wellbore is safe to operate. This hydrophone may include acoustic sensors that sense noise generated by motion of the hydrophone and may sense noise indicative of a defect that could lead to catastrophic failure of a wellbore. Noise generated by movement of the hydrophone may be classified as "road noise" and noise associated with wellbore defects may be classified being "signals of interest." The presence of "road noise" may interfere with the collection of "signals of interest" and because of this, evaluations performed on data that includes "road noise" may result in inaccurate determinations and a decrease in safety. As such, systems and methods of the present disclosure are directed to improving safety of a wellbore by removing "road noise" more effectively while increasing quality of "signals of interest."

This application discloses a road noise cancellation method, apparatus, device, and readable storage medium. The method includes the steps of: acquiring a first vibration signal of real-time noise from a single-axis accelerometer; generating a first anti-vibration signal based on the first vibration signal; and using the first anti-vibration signal to control a loudspeaker to play the first anti-noise signal to eliminate road noise. This application reduces the path for acquiring vibration signals, thereby lowering the bandwidth requirements of multi-axis accelerometers during data transmission and improving signal transmission efficiency.

The invention discloses an automobile road noise processing method and device, and relates to the technical field of noise reduction, and the method comprises the steps: dynamically determining a target amplitude limiting parameter value according to obtained influence factor information, the influence factor information comprising environment state information and / or sensor state information, the environment state information is information representing the environment state inside and / or outside the automobile, and the sensor state information is information representing the working state of a sensor used for collecting a reference signal and / or an error signal; generating an anti-noise signal based on the input first time domain reference signal and the first time domain error signal by adopting a pre-adaptive algorithm; and performing amplitude limiting on the anti-noise signal according to the target amplitude limiting parameter value, and outputting the anti-noise signal subjected to the amplitude limiting so as to control the road noise. According to the invention, the system stability and safety are ensured while a good noise reduction effect is ensured.

The utility model provides a kind of road noise barrier based on sound-absorbing material, including barrier support assembly and barrier body, barrier support assembly includes the barrier support post of pair arrangement, and the sliding slot upper end of barrier support post is connected with buffer sliding block, and one barrier hanging pole is connected between buffer sliding block, barrier hanging pole is connected with barrier assembly support by hinged link, and barrier assembly support is connected with barrier body by bolt.The utility model in barrier body is converted into heat energy dissipation by the sound hole hole of sound hole board body, and the sound-absorbing micropore on microporous attraction cloth layer is based on micro-perforated plate theory, and the sound-absorbing coefficient is excellent in full frequency band, especially in low frequency part, further improve sound-absorbing effect, significantly improve the sound-absorbing performance of low frequency band by sound-absorbing cotton layer, and the porous structure of sound-absorbing cotton layer effectively insulates internal air convection and heat radiation, significantly reduce heat loss, while large aperture area absorbs and reflects sound wave, effectively reduce noise.

The invention discloses an automobile road noise processing method and device, equipment, a storage medium and a product, and relates to the technical field of noise reduction, and the method comprises the steps: carrying out the sub-band decomposition of an input time domain reference signal and an input time domain error signal; dynamically determining a target updating step length according to the obtained influence factor information, wherein the influence factor information comprises environment state information and / or sensor state information; updating a sub-band adaptive filter coefficient according to the target updating step length based on the sub-band reference signal and the sub-band error signal; performing sub-band synthesis on the updated sub-band adaptive filter coefficient to obtain an updated time domain adaptive filter coefficient; and processing a newly input time domain reference signal based on the updated time domain adaptive filter coefficient to obtain an anti-noise signal, and controlling the road noise based on the anti-noise signal. The robustness and safety of the automobile road noise control system are guaranteed, and delayed response or unstable output is avoided.

A road noise cancellation (RNC) system may include a signal analysis controller for detecting non-stationary transient events based on sensor signals having spectral or temporal characteristics that are significantly different from steady-state road or cabin noise. Upon detecting such non-stationary events, the RNC system may modify the sensor signals to mask the non-stationary events, thereby preventing the RNC system's adaptive filters from erroneously adapting due to the transient non-stationary events. Alternatively, the RNC system may pause or slow down or suspend adaptation of its controllable filters for the duration of a frame that includes the non-stationary events.

Disclosed are a vehicle road noise control method and system based on active noise cancellation, electronic equipment, and a storage medium. The vehicle road noise control method comprises: collecting a multi-channel reference signal of vehicle road noise; generating a control signal according to a filter coefficient at current moment and the multi-channel reference signal, and feeding the control signal to a sound reproduction device of a vehicle; collecting sound signals at a plurality of sampling positions in a vehicle compartment to obtain a vector of an error signal; filtering the reference signal to obtain a filtered reference signal; writing the filtered reference signal into a matrix form; and updating the filter coefficient according to the matrix form of the filtered reference signal and the vector of the error signal. Active noise cancellation can be carried out on road noise caused by friction between vehicle tires and the road surface, noise pollution in the vehicle is reduced, and a relatively high convergence speed and a relatively excellent accuracy are achieved.

Described herein are methods and systems for a vehicle system which provide inbuilt road noise cancellation in the vehicle. In one or more embodiments, a method for road noise cancellation comprises using a head-tracking device to monitor an occupant ear position, capturing airborne noise using a feedforward microphone and a headrest microphone of a zone in which the occupant ear is positioned, updating acoustic path information according to the occupant ear position(s) and speaker position(s) within the zone, generating a noise cancellation signal using sampling rate greater than 2kHz, and outputting the noise cancellation signal via a headrest speaker located near the zone in which the occupant ear is positioned to at least partially reduce a road noise sound level in the zone.

The present application relates to a kind of computing method for realizing wide range dynamic noise map system fast update, comprising the following steps: using the data information of system database, based on existing day and night period and city road grade, simplify the structure of traditional road sound level mechanism model;Using big data technology, using hybrid modeling method, regression each grade road sound source (day and night) sound level contribution amount prediction model;Road noise fast calculation method based on sound level contribution amount prediction model is constructed, the fast update of dynamic noise map is realized.Compared with prior art, while ensuring the calculation precision, the operation and update efficiency of noise map system is greatly improved, and the technical constraints of foreign core computing software are broken, the localization of noise map core computing technology is realized, which provides technical support for wide range deep development of noise map.

The present disclosure relates to an information processing device, an information processing method, and a program with which it is possible to realize superior noise cancellation. A tracking information acquisition unit acquires tracking information pertaining to the head of an occupant inside the compartment of a vehicle. A filter selection unit selects, from among noise cancellation filters generated on the basis of position information pertaining to the head, a noise cancellation filter corresponding to the tracking information. A noise cancellation unit outputs, from a speaker provided within the compartment, a noise cancellation signal generated on the basis of the selected noise cancellation filter and a sensor value obtained from an acceleration sensor mounted on the vehicle. The technology according to the present disclosure can be applied to, for example, a road noise cancellation system.

Various implementations include noise cancelation (NC) systems and related approaches for NC. Certain implementations include a system including: a vehicle audio system including at least one transducer for providing an audio output to an occupant in a vehicle; a position sensor for indicating a position of the occupant in the vehicle; a set of additional sensors including an accelerometer; and a machine learning (ML) based road noise cancelation (RNC) system connected with the vehicle audio system and the position sensor, the ML based RNC system configured to: receive inputs from the vehicle audio system, the position sensor, and the accelerometer; apply a set of parameters defining noise cancelation signals based on the inputs; and generate noise cancelation signals for output by the at least one transducer based on the applied set of parameters.

The utility model discloses an urban road noise reduction device, which belongs to the technical field of traffic noise treatment and comprises a road body, sound insulation and noise reduction components are arranged on two sides of the road body, two sound insulation barrier arc-shaped covers are centripetally arranged, and arc centers face the road body. An air bag noise reduction bag used for absorbing noise and reducing sound wave propagation vibration is bonded to the inner wall of each sound insulation barrier arc-shaped cover, a top noise reduction cover is further arranged between the top ends of the two sound insulation barrier arc-shaped covers, and a noise reduction and energy absorption assembly is arranged in the middle of the opposite side face of each sound insulation barrier plate. The two noise reduction and energy absorption assemblies each comprise a first noise reduction and sound absorption filter screen, and the two first noise reduction and sound absorption filter screens are located on the two sides of the road body correspondingly, so that vehicle noise in the road body is subjected to sound absorption and noise reduction through the first noise reduction and sound absorption filter screens, the air bag noise reduction bag and the top noise reduction cover. Noise can be effectively reflected and blocked, and the noise can be guided to enter the internal sound absorption assembly to be processed.

The invention provides a road noise reduction control method and system based on traffic state statistics, and relates to the field of road noise reduction control, and the method comprises the steps: collecting a real-time traffic state and a real-time associated traffic state of a target road, and predicting and obtaining a predicted traffic state of the target road in a future time period through a traffic state predictor; through a noise feature simulation channel, a simulated noise feature sequence is obtained through analysis according to the predicted traffic state; and setting a reverse sound wave control scheme of the active noise reduction equipment by taking elimination of the analog noise feature sequence as a target, and executing noise reduction control. The objective of the invention is to solve the technical problem that the timeliness and precision of road noise suppression are insufficient due to the fact that a traditional noise reduction control method is difficult to cope with the dynamic change of road traffic noise, and can significantly improve the timeliness and precision of noise reduction scheme setting through real-time traffic prediction and dynamic reverse sound wave control. The problems of time-varying characteristics and complexity of road traffic noise are effectively solved, and accurate road noise reduction control is realized.

The present invention more effectively reduces discomfort of occupants, which is caused by a noise when the road surface condition switches.　An information processing device 10 comprises a control unit 11 for: acquiring audio information of a noise which is generated during traveling of a vehicle 50 and is sensed by a microphone 15; generating, on the basis of the acquired audio information, a cancellation sound for canceling a road noise caused by unevenness of a road surface G on which the vehicle 50 travels; and causing a speaker 16 to output the generated cancellation sound. The control unit 11: acquires road surface information indicating the condition of the road surface G in a direction in which the vehicle 50 advances; detects, on the basis of the acquired road surface information, a switching point at which the condition regarding the unevenness of the road surface G switches; and, in response to the detection of the switching point, causes the speaker 16 to output a noise sound obtained by imitating the road noise in a fixed transition section which is before or after the switching point passed along due to traveling by the vehicle 50 and in which the degree of unevenness of the road surface is smaller.

An assist band is set to a standard band when there is no large road noise, and is set to a treble band not including a low frequency band but including a high frequency band as compared with the standard band when there is a large road noise. In audio data of a front seat microphone, components outside the assist band are cut by an IIR filter, downsampled by a downsampling unit to a sampling frequency that is twice the upper limit of the assist band, processed by an echo canceller and a howling canceller, upsampled by an upsampling unit, and output to a rear seat speaker. When there is a large road noise, the operation of the howling canceller is invalidated, and the input is output as it is.

It is advantageous for a vehicle to detect road wetness or related environmental conditions. This is particularly true for self-driving vehicles, which can then adjust the manner of automated operation of the vehicle to increase safety by reducing speed, braking earlier, adjusting internal estimates of road traction parameters, or adjusting autonomous operation in some other manner. It is difficult to directly measure road wetness (e.g., using spectroscopy or other methods directed at the road surface), however, it is possible to indirectly estimate road wetness based on road noise audio signals detected via one or more microphones disposed on the vehicle. The location of the microphones, the type of post-processing applied to the audio signals, or other factors can be adapted to increase the useful road wetness-related content of such audio signals while reducing the presence of engine noise, road noise, or other confounding signals.

The invention discloses a road sound environment emotion influence evaluation method and device, and relates to the technical field of environment evaluation, and the method comprises the steps: carrying out the sampling of various urban road sound environment functional regions, determining the effective dominant audio and dominant sound pressure levels which a plurality of road dominant sound source types belong to, and classifying the effective dominant audio and dominant sound pressure levels into a plurality of road noise types; building a questionnaire platform in combination with the effective dominant audio and collecting subjective scores of a plurality of subjective indexes; acquiring electroencephalogram signals according to the effective dominant audio triggering of each road noise type; correspondingly determining subjective key principal components based on the subjective score of each road noise type; extracting a plurality of spectrum features of each electroencephalogram signal, and correspondingly determining objective key principal components according to the spectrum features of each road noise type; and correspondingly and comprehensively determining the emotion comprehensive index of each road noise type by adopting the subjective key principal component, the objective key principal component, the effective dominant audio and the dominant sound pressure level. And the actual influence of the urban road sound environment on human emotion and cognition can be revealed more comprehensively and accurately.

Disclosed are a method and system for controlling vehicle road noise based on active noise reduction. The method includes: acquiring a multi-channel reference signal of vehicle road noise; generating a control signal based on a coefficient of a filter at a current time and the multi-channel reference signal, and feeding to a sound reproduction device of the vehicle; acquiring acoustical signals at a plurality of sampling positions inside a compartment of the vehicle to obtain a vector of an error signal; filtering the reference signal to obtain a filtered reference signal; writing the filtered reference signal in a matrix form; and updating the coefficient of the filter. The method actively reduces the road noise caused by friction between vehicle tires and road surface, reduces interior noise pollution, and has a relatively fast convergence speed and relatively high accuracy.

Various implementations include a method of training a road noise cancelation (RNC) system for a vehicle, including: providing inputs to RNC system, the inputs obtained from: a set of ear-mounted microphones on a user, at least one transducer, an accelerometer, a set of cabin microphones in the vehicle, and a controller area network (CAN) bus, the inputs from the set of ear-mounted microphones on the user approximating a signal detected by the ears of the user; adapting a set of parameters in the RNC system defining an estimated signal detected at respective ears of the user based on the inputs; and generating at least one of the following for input during an operating mode of the RNC system: estimated ear microphone signals based on the adapted set of parameters, or a set of projection filters for use in determining an estimated ear signal at the respective ears of the user.

Techniques for automatic parameter tuning of an active road noise cancellation system are described herein. The system can automatically search a group of optimal algorithm parameters according to recorded data. Active road noise cancellation algorithms and simulations may be embedded in an automatic differential framework that allows gradients of algorithm parameters to guide automatic search and calculation of algorithm parameters.

This invention discloses an in-vehicle selective noise reduction method based on sound field reconstruction, relating to the field of in-vehicle safety warning technology. The method includes: collaboratively collecting in-vehicle acoustic and vibration data through sensors; separating the acoustic and vibration data using a blind source separation algorithm to obtain a voiceprint feature tensor; inputting the voiceprint feature tensor into a convolutional neural network for voiceprint recognition, outputting a safety sound category and a safety sound hazard level; generating adaptive noise reduction parameters based on vehicle speed and safety sound category; assigning the final adaptive noise reduction parameters to seats in different regions; and issuing a physical vibration warning based on the safety sound hazard level to complete the in-vehicle selective noise reduction. This invention significantly improves the detection and recognition accuracy of critical safety sounds in road noise environments; it balances noise suppression and active safety assurance, effectively enhancing the vehicle's perception and response capabilities to emergency sound sources while improving passenger comfort.