CN114067612A - Vehicle perception and danger early warning method and system based on environmental sound analysis - Google Patents
Vehicle perception and danger early warning method and system based on environmental sound analysis Download PDFInfo
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- CN114067612A CN114067612A CN202111419113.1A CN202111419113A CN114067612A CN 114067612 A CN114067612 A CN 114067612A CN 202111419113 A CN202111419113 A CN 202111419113A CN 114067612 A CN114067612 A CN 114067612A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
- G01S5/22—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
- G08B7/066—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources guiding along a path, e.g. evacuation path lighting strip
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
- G10L15/063—Training
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
- G10L25/24—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being the cepstrum
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
- G10L15/063—Training
- G10L2015/0631—Creating reference templates; Clustering
Abstract
The invention discloses a vehicle perception and danger early warning method and system based on environmental sound analysis. Collecting sound information around the vehicle through sound sensors arranged around the vehicle body, transmitting the sound information to a sound analysis module, extracting short-time energy characteristics of the sound information and MFCC (Mel frequency cepstrum coefficient) characteristics, comparing and analyzing, and judging target object attributes (motor vehicles, non-motor vehicles, pedestrians and animals); the position and relative motion relation of the sound source relative to the vehicle is judged by analyzing the Time Difference (TDOA) of sound reaching different position sensors, and the attribute of the surrounding traffic constituent and the relative position information of the vehicle and the surrounding traffic constituent are displayed by the vehicle-mounted display. According to the perceived relative motion relation between the information such as the attribute, the position, the motion and the like of the surrounding traffic composers and the vehicle, whether danger occurs or not is judged, and danger early warning is carried out on the vehicle driver and other traffic composers under the dangerous condition, and the information can be fused with other types of sensor perception information, so that the environment perception precision is improved.
Description
Technical Field
The invention relates to the technical field of sound detection, in particular to a vehicle perception and danger early warning method and system based on environmental sound analysis.
Background
With the increasing of the automobile holding capacity, traffic scenes become more and more complex, and it is difficult to observe and identify all targets (including motor vehicles, non-motor vehicles, pedestrians and the like) around the vehicles, no matter the vehicles are driven by people or unmanned vehicles, and particularly, in the scenes such as blind areas of vision, foggy days, rainy days, nights and the like of the vehicles, it is more difficult to observe surrounding traffic components carefully. According to the vehicle perception and danger early warning method and system based on environmental sound analysis, traffic composition information is visually represented as images through a vehicle-mounted display to inform a driver, and sound and light reminding is carried out on the driver and other traffic compositions under dangerous conditions.
For illegal whistle phenomenon in a whistle-forbidden area, research for positioning and capturing by using voice recognition is currently available. In the vehicle-assisted driving technology, there is also a study of recognizing and locating a whistling around a vehicle and determining whether the vehicle is in danger.
However, the above studies have the following drawbacks: only the whistle is used for identifying the vehicle, the sounds emitted by the non-motor vehicles, pedestrians and the like are taken as noise for filtering, and the factors such as the non-motor vehicles, the pedestrians and the like are not considered; only the whistling sound is identified, and the problem that the surrounding vehicles cannot timely whistling due to fault and over-speed running is difficult to solve.
The invention provides a vehicle perception and danger early warning method and system based on environmental sound analysis to ensure reasonable analysis of surrounding traffic composition, the system makes full use of surrounding sound information, and carries out analysis through a sound sensor array and a sound analysis module to transmit the surrounding traffic composition information of a vehicle, including motor vehicles, non-motor vehicles, pedestrians and the like, to a driver, and meanwhile, when a target object is too close to a self vehicle, danger early warning is carried out on the driver, and driving safety is ensured. With the increasing automobile holding amount, traffic scenes become more and more complex, and it is difficult to observe and identify all targets (including motor vehicles, non-motor vehicles, pedestrians and the like) around the vehicle no matter the current vehicles driven by people or the vehicles driven by no people, and particularly, in the scenes such as the blind area of the field of vision, the foggy day, the rainy day, the night and the like of the vehicle, it is more difficult to observe the surrounding traffic composition carefully. According to the vehicle perception and danger early warning method and system based on environmental sound analysis, traffic composition information is visually represented as images through a vehicle-mounted display to inform a driver, and sound and light reminding is carried out on the driver and other traffic compositions under dangerous conditions.
Disclosure of Invention
Based on the above, the present invention is directed to analyzing the surrounding traffic composition through the environmental sound, determining the location and attribute of an object according to the short-time energy characteristics, the MFCC characteristics, and the time difference of arrival (TDOA), and reminding a driver of a vehicle, other drivers, and pedestrians when the distance between the vehicle and the object is less than the safety distance, thereby ensuring the driving safety. The environment recognition precision in the conditions of foggy days, at night, in visual field blind areas and the like is effectively improved.
In order to achieve the purpose, the invention provides a vehicle sensing and danger early warning method and system based on environmental sound analysis.
The sound acquisition module consists of 12 sound sensors and a single chip microcomputer which are arranged around the vehicle body and is used for acquiring sound information, preprocessing the sound information and preparing for the sound analysis module;
the sound analysis module is supported by a vehicle-mounted high-performance server, receives sound information preprocessed by the sound acquisition module, inputs the sound information into a trained sound recognition model for comparison and recognition, and obtains the attribute and the position information of the target by combining the analysis of Time Difference (TDOA) of the same sound source reaching different position sensors. Meanwhile, whether danger occurs or not is judged according to the relative distance between the self vehicle and the target object and the motion state of the target object;
the danger early warning module comprises a vehicle-mounted display, a vehicle inside and outside loudspeaker, a vehicle outside indicator light and the like, and the attributes of surrounding traffic composers and the relative position information of the vehicle and the surrounding traffic composers can be visually represented as images through the vehicle-mounted display to inform a driver, and sound and light reminding is carried out on the vehicle driver and other traffic composers under dangerous conditions.
Further, 12 sound sensors are distributed around the vehicle body in the form of 2 sound sensors at the vehicle head, 2 sound sensors at the vehicle tail, 2 sound sensors at the left side and the right side of the vehicle body and 1 sound sensor at each of four vertexes of the vehicle body. The vehicle-mounted display is located the main driver's cabin, and outer speaker and the outer pilot lamp of car all are located the vehicle top, and the speaker is taken from leaving the factory in the car, is connected with sound analysis module for leaving the factory, receives the signal of telecommunication of sound analysis module transmission and output warning sound.
Furthermore, in the sound collection process, noise such as wind noise is filtered through a filter, and targeted collection is performed on the frequencies of the following sounds: engine sound and exhaust sound of a fuel vehicle, motor sound of a new energy vehicle, tire sound of a non-motor vehicle, breath sound and footstep sound of a person and an animal, and the like.
Further, sound in the traffic environment is collected and analyzed to establish a data set, the data set is continuously collected in the running process of the vehicle, the data set is perfectly supplemented, then the short-time energy characteristic and the MFCC characteristic of the data set are extracted, training is carried out after cluster analysis, and a sound recognition model is obtained.
Further, the collected sound information is subjected to feature extraction, and then the collected sound information is input into a sound recognition model to compare short-time energy features with MFCC features, so that object attributes (motor vehicles, non-motor vehicles, pedestrians and the like) are identified; and analyzing and calculating the time difference of the sound reaching different position sensors to obtain target position information and the relative motion relation between the target object and the self vehicle.
Further, safety distances are set, including a longitudinal safety distance d1 and a transverse safety distance d 2. When the relative distance between the longitudinal target object and the vehicle is less than the safe distance d1, the driver and other traffic components are reminded through the loudspeaker and the indicator light; when the relative distance between the transverse object and the self-vehicle is less than the safe distance d2, the driver and other traffic components are reminded through the loudspeaker and the indicating lamp.
Further, the prompts for drivers and other traffic composers include:
when the relative distance between the self-vehicle and the target is judged to be smaller than the safe distance, the roof loudspeaker prompts danger and please notice.
Further, the indication of the indicator lights to other traffic composers includes:
when the relative distance between the self vehicle and the target object is judged to be less than or equal to the safe distance, the indicator lamp outside the vehicle displays red;
when the relative distance between the self vehicle and the target object is judged to be larger than the safe distance, the indicating lamp outside the vehicle displays green.
Based on the technical scheme, the vehicle perception and prompting system utilizing environmental noise analysis has the following advantages: the invention judges the attribute and the position of the surrounding traffic composer by the short-time energy characteristic, the MFCC characteristic and the time difference of arrival (TDOA), and has wider identification frequency range, more identification sounds and higher identification precision.
According to the invention, the surrounding traffic composition information is transmitted to the driver of the own vehicle through the display, and the danger information is transmitted to the driver of the own vehicle and the surrounding traffic composition person through the loudspeaker and the indicating lamp, so that the system is better suitable for environments with low visibility such as night, foggy days and rainy days, more application scenes and wider application range.
The invention can send out sound and light to warn surrounding traffic, aiming at the condition that the relative distance between the vehicle and the target object is less than the safe distance and danger is about to occur, and the safety is higher.
Drawings
FIG. 1 is a flow chart of the operation of the present invention.
FIG. 2 is a schematic diagram of one embodiment of the present invention.
Fig. 3 shows the layout of the entire vehicle system.
Wherein, 1 is the motor vehicle, 2 is the non-motor vehicle, 3 is the sound sensor, 4 is on-vehicle display, 5 is on-vehicle high performance server, 6 is the speaker outside the car, 7 is the pilot lamp.
Detailed Description
In order that the objects, technical solutions and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the accompanying drawings in conjunction with the following specific embodiments.
As shown in fig. 1 and 2, the system mainly includes a sound sensor 3, an in-vehicle display 4, an in-vehicle high-performance server 5, an external speaker 6, an indicator light 7, and an internal speaker.
The training process of the voice recognition model is described with reference to fig. 1 and 2: firstly, a sound sample library is established by utilizing public data and actual collection, and the sound sample is manually calibrated. The Python is used to perform processing such as pre-filtering and end point detection on the voice data of each sample, thereby reducing the influence of the voice signal.
And performing characteristic parameter analysis and cluster analysis on the processed voice signals to obtain a representative training sample set, and then introducing the training sample set into a CNN (convolutional neural network) for training to obtain a trained voice recognition model.
The feature recognition process is explained with reference to fig. 1 and 2:
identification of target attributes: when the auxiliary perception system works, sound signals around are collected through the sound sensor, the characteristics of the sound signals are preprocessed to realize separation of different sound signals, short-time energy characteristics and MFCC characteristics of the sound signals are extracted and converted into a characteristic diagram, and classification and identification (motor vehicles, non-motor vehicles, pedestrians and animals) are carried out on the attributes of the sound through the CNN of the sound analysis module.
Identification of the target position: the sound sensor array receives the sound source signal and then transmits the sound source signal to the sound analysis module, and the position information and the relative motion relation of the target are obtained through analyzing the Time Difference (TDOA) of the same sound source reaching different position sensors. Meanwhile, whether danger occurs or not is judged according to the relative distance between the self vehicle and the target object and the motion state of the target object.
Sound sensor distributes around the automobile body, and vehicle-mounted display is located main driver's cabin, and outer speaker of car and the outer pilot lamp of car all are located the vehicle top, and the speaker is for dispatching from the factory from taking the speaker in the car.
The specific work flow of the invention comprises.
Step S1: when the vehicle starts, the system is automatically started, and the indicator light outside the vehicle is displayed as green at the moment.
Step S2: the sound sensor 3 collects sound information around the vehicle and performs preprocessing, including: engine sound and exhaust sound of a fuel vehicle, motor sound of a new energy vehicle, tire sound of a non-motor vehicle, breath sound and footstep sound of a person and an animal, and the like.
Step S3: the sound sensor 3 transmits the preprocessed sound information to a sound analysis module, and after the sound analysis module extracts the features, the extracted short-time energy features and the MFCC features are input into a trained sound recognition model for comparison and recognition to obtain the attributes of the sound target; the method comprises the steps of analyzing Time Difference (TDOA) of the same sound source reaching different position sensors to obtain position information of a sound target, and then transmitting the position and attribute information of a target object to a danger early warning module.
The sound analysis module continuously analyzes the relative distance between the self-vehicle and the target object and the relative motion relation between the target object and the self-vehicle according to the target position information to judge whether danger occurs or not and sends a corresponding signal to the danger early warning module.
Step S4: the danger early warning module receives the electric signal transmitted by the sound analysis module, and visually represents the attribute of the surrounding traffic composer and the relative position information of the vehicle and the surrounding traffic composer as images through the vehicle-mounted display so as to inform a driver.
When the sound analysis module judges that danger exists, the danger early warning module carries out sound and light reminding on a driver and other traffic constituent persons.
The specific judgment process is as follows: the longitudinal safety distance d1 and the transverse safety distance d2 are set.
After the position of vertical target is calculated to sound analysis module, reach vertical target and the relative distance of car certainly, when vertical target is less than safe distance d1 with the relative distance of car certainly, sound analysis module judges that there is danger, send corresponding early warning signal to dangerous early warning module, dangerous early warning module receives the early warning signal after, carry out dangerous early warning to the driver through speaker and display in the car, carry out dangerous early warning to other traffic composition people outside the car through outer speaker of car and pilot lamp.
After the position of horizontal target is calculated to sound analysis module, reach horizontal target and the relative distance of car certainly, when horizontal target is less than safe distance d2 with the relative distance of car certainly, sound analysis module judges that there is danger, send corresponding early warning signal to dangerous early warning module, dangerous early warning module receives the early warning signal after, carry out dangerous early warning to the driver through speaker and display in the car, carry out dangerous early warning to other traffic composition people outside the car through outer speaker of car and pilot lamp.
Wherein, the prompting words for the driver and other traffic composers comprise:
when the relative distance between the self-vehicle and the target is judged to be smaller than the safe distance, the roof loudspeaker prompts danger and please notice.
Wherein, the indicator light prompt to other traffic composers includes:
when the relative distance between the self vehicle and the target object is judged to be less than or equal to the safe distance, the indicating lamp outside the vehicle displays red.
When the relative distance between the self vehicle and the target object is judged to be larger than the safe distance, the indicating lamp outside the vehicle displays green.
Claims (8)
1. A vehicle perception and danger early warning method and system based on environmental sound analysis are characterized in that the system mainly comprises a sound collection module, a sound analysis module and a danger early warning module, wherein the sound collection module is connected with the sound analysis module, and the sound analysis module is connected with the danger early warning module;
the sound acquisition module consists of 12 sound sensors and a single chip microcomputer which are arranged around the vehicle body and is used for acquiring sound information, preprocessing the sound information and preparing for the sound analysis module;
the sound analysis module is supported by a vehicle-mounted high-performance server to provide calculation power, receives sound information preprocessed by the sound acquisition module, inputs the sound information into a trained sound recognition model for comparison and recognition, obtains the attribute and the position information of a target by combining the analysis of Time Difference (TDOA) of the same sound source reaching different position sensors, and judges whether danger occurs or not according to the relative distance between the vehicle and the target and the relative motion relation between the target and the vehicle;
the danger early warning module comprises a vehicle-mounted display, a vehicle inside and outside loudspeaker, a vehicle outside indicator light and the like, and the attributes of surrounding traffic composers and the relative position information of the vehicle and the surrounding traffic composers can be visually represented as images through the vehicle-mounted display to inform a driver, and sound and light reminding is carried out on the vehicle driver and other traffic composers under dangerous conditions.
2. The vehicle sensing and danger early warning method and system based on environmental sound analysis as claimed in claim 1, wherein the sound sensors are distributed around the vehicle body, the vehicle-mounted display is located in the main cab, the external speaker and the external indicator light are both located at the top of the vehicle, and the internal speaker is located in the cab.
3. The vehicle perception and danger early warning method and system based on environmental sound analysis as claimed in claim 1, wherein in the sound collection process, noise such as wind noise is filtered out through a filter, and the following frequencies of sound are collected in a targeted manner: engine sound and exhaust sound of a fuel vehicle, motor sound of a new energy vehicle, tire sound of a non-motor vehicle, breath sound of a person and an animal, footstep sound, and the like.
4. The method and system for vehicle perception and danger early warning based on environmental sound analysis as claimed in claim 1, wherein sound in traffic environment is collected and analyzed to build a data set, and the data set is collected continuously in the vehicle running process, the data set is completed and supplemented, then the short-time energy feature and MFCC feature of the data set are extracted, and training is performed after cluster analysis to obtain a sound recognition model.
5. The method and system for vehicle sensing and danger early warning based on environmental sound analysis as claimed in claim 1, wherein the collected sound information is feature extracted and input into a sound recognition model to compare short-time energy features with MFCC features, so as to identify object attributes (motor vehicle, non-motor vehicle, pedestrian, etc.); and analyzing and calculating the time difference of the sound reaching different position sensors to obtain the relative motion relation between the target position information and the self-vehicle.
6. The method and system for vehicle sensing and danger early warning based on environmental sound analysis as claimed in claim 1, wherein safe distances are set, including a longitudinal safe distance d1, a transverse safe distance d 2;
when the relative distance between the longitudinal target object and the self-vehicle is less than the safe distance d1, the driver and other traffic components are reminded through the loudspeaker and the indicating lamp; when the relative distance between the transverse object and the self-vehicle is less than the safe distance d2, the driver and other traffic components are reminded through the loudspeaker and the indicating lamp.
7. The method and system for vehicle perception and danger early warning based on ambient sound analysis of claim 1, wherein the prompts for drivers and other traffic composers include:
when the relative distance between the self-vehicle and the target is judged to be smaller than the safe distance, the roof loudspeaker prompts danger and please notice.
8. The method and system for vehicle perception and danger early warning based on ambient sound analysis of claim 1, wherein the indication of the indicator lights to other traffic components comprises:
when the relative distance between the self vehicle and the target object is judged to be less than or equal to the safe distance, the indicator lamp outside the vehicle displays red;
when the relative distance between the self vehicle and the target object is judged to be larger than the safe distance, the indicating lamp outside the vehicle displays green.
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