CN119357906B

CN119357906B - A method, system, medium and device for accurately detecting right turn of vehicle

Info

Publication number: CN119357906B
Application number: CN202411932744.7A
Authority: CN
Inventors: 姜登科; 谢东航; 段睿祺
Original assignee: Zhuhai Magic Cube Core Intelligent Connection Technology Co ltd
Current assignee: Zhuhai Magic Cube Core Intelligent Connection Technology Co ltd
Priority date: 2024-12-26
Filing date: 2024-12-26
Publication date: 2025-03-25
Anticipated expiration: 2044-12-26
Also published as: CN119357906A

Abstract

The present invention relates to the field of vehicle control technology, and more specifically, to a method, system, medium and device for accurately detecting a vehicle turning right. The scheme includes using an inertial measurement unit to collect information and obtain online collected information; transmitting the online collected information to a single-chip microcomputer through an SPI interface; preprocessing the data in the single-chip microcomputer to form a multi-dimensional data fusion data group; performing posture analysis online and combining GIS and bump height to make a comprehensive data validity judgment; performing average value analysis after obtaining six-axis data; and performing state judgment online based on the average value analysis result. The scheme uses fast data preprocessing combined with high-precision and data-fused three-axis Euler calculation to make accurate average value and change value judgments, thereby completing intelligent perception and control of the vehicle.

Description

Implementation method, system, medium and equipment for accurately detecting right turn of vehicle

Technical Field

The invention relates to the technical field of vehicle control, in particular to a realization method, a system, a medium and equipment for accurately detecting right turning of a vehicle.

Background

In the field of vehicle control, implementations for accurately detecting right turns of a vehicle typically involve the use of advanced sensor technologies (e.g., IMU), complex data processing algorithms (e.g., kalman filtering and machine learning), and multi-sensor fusion techniques. The technologies can monitor the motion state of the vehicle in real time, including acceleration, angular velocity and attitude changes, so as to accurately judge whether the vehicle is executing right-turning actions. The accurate detection has the significance of improving the safety and driving experience of the vehicle, and the auxiliary driving system can be more intelligently intervened by responding to the steering intention of the vehicle in time, so that necessary support or warning is provided, and the occurrence of traffic accidents is reduced. In addition, accurate detection of right turns of a vehicle is critical to the development of automated driving technology, which provides reliable data support for advanced driving assistance systems and automated driving vehicles, helping to achieve a smoother and safer driving transition.

Prior to the present technology, existing implementations of accurately detecting right turns of a vehicle have relied primarily on single sensor data, such as gyroscopes or accelerometers, by analyzing changes in the sensor output to infer the state of motion of the vehicle. However, the method has obvious limitations that firstly, a single sensor is easily affected by external interference and noise, so that the accuracy of data is reduced, secondly, the performance difference of the sensors with different brands and models is large, so that the algorithm needs to be frequently adjusted to adapt to different hardware conditions, and finally, the difficulty of accurate judgment is increased due to complex road environment and variable driving behaviors. Therefore, improving the data fusion capability and enhancing the robustness and adaptability of the system become key technical difficulties and research emphasis in the field.

Disclosure of Invention

In view of the above problems, the invention provides a realization method, a system, a medium and a device for accurately detecting the right turn of a vehicle, which are used for carrying out accurate average value and variation value judgment by combining high-precision and data fusion three-axis Euler calculation through rapid data preprocessing so as to finish intelligent perception and control of the vehicle.

According to a first aspect of the embodiment of the invention, an implementation method for accurately detecting right turning of a vehicle is provided.

In one or more embodiments, preferably, the implementation method for accurately detecting the right turn of the vehicle includes:

Acquiring information by using an inertial measurement unit to acquire online acquisition information;

Transmitting the online acquisition information to a singlechip through an SPI interface;

preprocessing data in a singlechip to form a multi-dimensional data fusion data set;

Carrying out on-line attitude analysis and carrying out comprehensive data validity judgment by combining GIS and bump height;

After six-axis data are obtained, average value analysis is carried out;

and carrying out on-line state judgment according to the average value analysis result.

In one or more embodiments, preferably, the acquiring information using the inertial measurement unit, to obtain on-line acquired information specifically includes:

Acquiring information of an inertial measurement unit on line, and acquiring acceleration and angular velocity;

acquiring GPS information through a vehicle-mounted GPS;

the bump height information is obtained through a vehicle-mounted sensor;

And combining the acceleration, the angular velocity, the six-axis sensor acquired data, the GPS information and the bump height information to serve as online acquired information.

In one or more embodiments, preferably, the transmitting the online acquisition information to the singlechip through the SPI interface specifically includes:

Setting an SPI interface channel;

and transmitting all online acquisition information to the singlechip at preset intervals through serial communication.

In one or more embodiments, preferably, the preprocessing of data in the single chip microcomputer to form a multi-dimensional data fusion data set specifically includes:

acquiring on-line acquisition information acquired in real time in a storage area of a singlechip;

Performing online analysis on the online acquired information, and calculating integral deviation by using a first calculation formula;

Judging whether the integral deviation meets a second calculation formula, if so, considering that the data meets the requirement, further filtering the multidimensional data in the same time period, and stamping a time stamp;

If the integral deviation does not meet the second calculation formula, the data is considered to be unsatisfied with the requirement, and the data is directly deleted;

Taking the data with the time stamp as original data, and performing low-pass filtering and Kalman filtering processing on the original data to remove noise;

The first calculation formula is as follows:

PC=

wherein PC is integral deviation, P (t) is the absolute value of deviation of the historical average value corresponding to each data at the moment t, and n is the total duration;

The second calculation formula is as follows:

{Max(PC)-Min(PC)}÷Max(PC)<Y

Where Y is a preset contrast margin, max () and Min () are maximum and minimum extraction functions in data within 10 minutes.

In one or more embodiments, preferably, the performing gesture analysis online and performing comprehensive data validity judgment in combination with GIS and bump height specifically includes:

Calculating three-axis Euler angles by using a six-axis fusion algorithm, wherein the three-axis Euler angles comprise pitch angles, roll angles and yaw angles;

Judging whether jump meeting a third calculation formula exists in the pitch angle, the roll angle and the yaw angle;

if yes, starting a historical map analysis module, wherein the historical map analysis module analyzes whether the bump height of a road section passing by the latest 1 minute meets a fourth calculation formula on line, if not, the current data is considered to be abnormal rotation, and if yes, the current data is considered to be normal;

further judging whether GIS auxiliary judging data exist for the abnormal rotation, and if not, eliminating current data;

If yes, judging whether the triaxial Euler angle meets a fifth calculation formula or not through GIS data, and if yes, considering the data to be effective and deleting the data in an irregular manner;

the third calculation formula is as follows:

YD>Y2

HD>Y3

PD>Y4

Wherein YD is the last 1 minute average change rate of pitch angle, HD is the last 1 minute average change rate of roll angle, PD is the last 1 minute average change rate of yaw angle, Y2 is the second contrast margin, Y3 is the third contrast margin, and Y4 is the fourth contrast margin;

the fourth calculation formula is as follows:

YF>ST

wherein YF is the maximum value of the bump height of a road section through which 1 minute passes, and ST is the preset maximum bump;

The fifth calculation formula is:

YD-GP>Y5

HD-GP>Y6

PD-GP>Y7

Wherein GP is a GIS judgment value, Y5 is a fifth comparison margin, Y6 is a sixth comparison margin, and Y7 is a seventh comparison margin.

In one or more embodiments, preferably, the average analysis is performed after obtaining six-axis data, which specifically includes:

after six-axis data are processed, carrying out data storage after delay for 20ms, and storing the data in a preset data linked list;

And calculating average change values of the first N data of the data linked list.

In one or more embodiments, preferably, the determining the state online according to the average value analysis result specifically includes:

according to the comparison of the calculated average change value and a preset turning threshold value, when judging that the sixth calculation formula is met, turning right or turning right;

if the turning state is not satisfied, the turning state is considered to be ended;

the sixth calculation formula is:

PB>Y8

PB is an average change value, and Y8 is a preset turning threshold value.

According to a second aspect of the embodiment of the invention, an implementation system for accurately detecting a right turn of a vehicle is provided.

In one or more embodiments, preferably, the implementation system for accurately detecting a right turn of a vehicle includes:

The data acquisition module is used for acquiring information by using the inertial measurement unit to acquire online acquisition information;

The data transmission module is used for transmitting the online acquisition information to the singlechip through an SPI interface;

The data preprocessing module is used for preprocessing data in the singlechip to form a multi-dimensional data fusion data set;

The attitude calculation module is used for carrying out attitude analysis on line and carrying out comprehensive data validity judgment by combining GIS and bump height;

The data processing module is used for carrying out average value analysis after six-axis data are obtained;

and the state judging module is used for carrying out state judgment on line according to the average value analysis result.

According to a third aspect of embodiments of the present invention, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method according to any of the first aspect of embodiments of the present invention.

According to a fourth aspect of embodiments of the present invention there is provided an electronic device comprising a memory and a processor, the memory being for storing one or more computer program instructions, wherein the one or more computer program instructions are executable by the processor to implement the method of any of the first aspects of embodiments of the present invention.

The technical scheme provided by the embodiment of the invention can comprise the following beneficial effects:

in the scheme of the invention, a comprehensive judging method for multi-dimensional data fusion is provided, and after data are acquired, multi-dimensional checking and analysis of the data are carried out before filtering.

In the scheme of the invention, the right turn judgment of multi-dimensional data fusion is realized by judging the three-axis Euler angles in the six-axis fusion algorithm and combining the road bump condition and the road turning position analysis on the basis.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.

The technical scheme of the invention is further described in detail through the drawings and the embodiments.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for implementing accurate detection of a right turn of a vehicle in accordance with one embodiment of the present invention.

Fig. 2 is a flowchart of information acquisition using an inertial measurement unit to obtain online acquisition information in an implementation method for accurately detecting a right turn of a vehicle according to an embodiment of the present invention.

Fig. 3 is a flowchart of transmitting the online acquisition information to the singlechip through the SPI interface in an implementation method for accurately detecting the right turn of the vehicle according to an embodiment of the present invention.

Fig. 4 is a flowchart of preprocessing data in a single chip microcomputer to form a multi-dimensional data fusion data set in an implementation method for accurately detecting a right turn of a vehicle according to an embodiment of the present invention.

FIG. 5 is a flow chart of an implementation method for accurately detecting right turns of a vehicle for on-line gesture analysis and comprehensive data validity determination in combination with GIS and bump height according to an embodiment of the present invention.

Fig. 6 is a flowchart of an implementation method for accurately detecting a right turn of a vehicle according to an embodiment of the present invention, after six axes of data are obtained, performing an average analysis.

Fig. 7 is a flowchart of an implementation method for accurately detecting a right turn of a vehicle according to an embodiment of the present invention, in which a state determination is performed on line according to an average analysis result.

FIG. 8 is a block diagram of an implementation system for accurately detecting a right turn of a vehicle in accordance with one embodiment of the present invention.

Fig. 9 is a block diagram of an electronic device in one embodiment of the invention.

Detailed Description

In some of the flows described in the specification and claims of the present invention and in the foregoing figures, a plurality of operations occurring in a particular order are included, but it should be understood that the operations may be performed out of order or performed in parallel, with the order of operations such as 101, 102, etc., being merely used to distinguish between the various operations, the order of the operations themselves not representing any order of execution. In addition, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first" and "second" herein are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, and are not limited to the "first" and the "second" being different types.

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.

The embodiment of the invention provides a realization method for accurately detecting right turning of a vehicle. According to the scheme, through rapid data preprocessing, high-precision and data fusion triaxial Euler calculation is combined, accurate average value and change value judgment are carried out, and intelligent sensing and control of a vehicle are completed.

The method comprises the steps of acquiring information by using an inertial measurement unit to obtain online acquisition information, transmitting the online acquisition information to a singlechip through an SPI interface, preprocessing data in the singlechip to form a multi-dimensional data fusion data set, carrying out on-line attitude analysis and comprehensive data validity judgment by combining GIS and bump height, carrying out average value analysis after six-axis data are obtained, and carrying out on-line state judgment according to an average value analysis result. In the embodiment of the invention, firstly, the IMU sensor is utilized to collect vehicle motion data and the vehicle motion data is transmitted to the singlechip in real time through the SPI interface. Subsequently, the original data is subjected to low-pass filtering and kalman filtering processing to remove noise and improve the data quality. And then, calculating a three-axis Euler angle by applying a six-axis fusion algorithm, and obtaining accurate posture information of the vehicle. After six axes of data are processed, the system delays for 20ms, then performs doubly linked list calculation, and calculates the average change value of the first N data. And finally, judging whether the vehicle is in a right turning state or whether the right turning is finished according to the comparison of the average change value and a preset threshold value. The system not only improves the safety and driving experience of the vehicle, but also provides reliable data support for the development of automatic driving technology.

As shown in fig. 2, in one or more embodiments, preferably, the acquiring information using the inertial measurement unit, to obtain on-line acquired information specifically includes:

The method comprises the steps of collecting information of an inertial measurement unit on line, collecting acceleration and angular velocity, obtaining GPS information through a vehicle-mounted GPS, obtaining bump height information through a vehicle-mounted sensor, and combining the acceleration and angular velocity with the collected data of a six-axis sensor, the GPS information and the bump height information to obtain the on-line collected information. In an embodiment of the invention, first, we continuously monitor and record acceleration and angular velocity information of the vehicle through an Inertial Measurement Unit (IMU) mounted on the vehicle. An IMU is a self-contained measurement device capable of detecting and reporting the state of motion, including acceleration and rotation rate, of a system relative to an inertial frame of reference. In this embodiment, the IMU is fixed to the vehicle interior with a three-axis accelerometer for measuring linear acceleration of the vehicle in three dimensions and a three-axis gyroscope for measuring rotational angular velocity of the vehicle about three mutually perpendicular axes. And secondly, acquiring accurate position information by using a vehicle-mounted GPS module. GPS is a satellite-based navigation system that can provide real-time geographic location, speed, and time information of a vehicle worldwide. In the present system, a GPS receiver continuously tracks a plurality of satellite signals to determine longitude and latitude coordinates and movement speed of a vehicle. Next, the vertical displacement amount of the vehicle caused by the road surface unevenness is detected by a bump height sensor mounted on the vehicle chassis or other critical position. Such sensors typically operate on the principle of piezoelectric effect or capacitance change, and are capable of converting mechanical vibrations into electrical signals for output, reflecting the degree of jolt experienced by the vehicle. And finally, integrating the acceleration and angular velocity data obtained from the IMU, the geographic position and velocity information provided by the GPS and the bump strength data recorded by the bump height sensor together to form a comprehensive online acquisition information packet. The data packet not only contains basic kinematic parameters of the vehicle, but also covers the influence of environmental factors on the running state of the vehicle, and provides rich original data for subsequent gesture analysis, data processing and state judgment. For example, when the vehicle is traveling over a rough road, the IMU may detect frequently varying accelerations and angular velocities, the GPS may indicate that the vehicle is slowly changing but that the velocity is fluctuating, and the bump height sensor may report a high bump value. The information is recorded in real time and transmitted to the central processing unit for analysis and processing in a wireless or wired mode.

As shown in fig. 3, in one or more embodiments, preferably, the transmitting the online collected information to the single chip microcomputer through the SPI interface specifically includes:

And transmitting all online acquisition information to the singlechip at preset intervals through serial communication. In the embodiment of the invention, firstly, an SPI interface channel needs to be set. SPI is a synchronous serial communication protocol commonly used for short-range, high-speed data transmission. In this embodiment, the SPI interface is configured for four-wire mode, including a clock line (SCLK), a master input/slave input line (MOSI), a master input/slave output line (MISO), and a slave select line (SS). These lines establish a connection between the microcontroller and the sensor module, ensuring that the data can be properly transferred. Next, an initialization setting of the SPI interface is performed. This includes configuring the SPI control registers to set the appropriate communication rate, data bit order (e.g., MSB first or LSB first), and whether certain functions are enabled (e.g., whether CS chip select signals are required). In addition, relevant parameters need to be adjusted according to the specific hardware used, such as selecting an appropriate clock source and division factor to meet the timing requirements of the system. And then, all the online acquisition information is sent to the singlechip through serial communication according to a preset time interval. In this step, each sensor node will package the data collected by it into a data frame and send it out through the SPI bus. The singlechip is used as a host end and can periodically initiate SPI transaction requests to read data from each sensor. Each transaction may involve the transmission of a single byte or multiple bytes, depending on the data format of the sensor and the required accuracy. For example, assuming that an accelerometer generates a new set of three-dimensional acceleration data every 10 milliseconds, the single chip microcomputer may trigger an SPI read operation every 10 milliseconds, and obtain the latest data from the accelerometer. Likewise, similar methods may be employed to periodically collect data for angular velocity meters and other types of sensors. Finally, all data received by the singlechip are stored in an internal memory thereof for subsequent processing. Such data may include information on real-time position, speed, acceleration, angular velocity, and jerk of the vehicle, which are critical to implementing Advanced Driving Assistance System (ADAS) functions, etc. In a word, through the steps, the SPI interface can be effectively utilized to transmit the data collected by various sensors to the singlechip in real time, so that support is provided for further data analysis and decision making.

As shown in fig. 4, in one or more embodiments, preferably, the preprocessing of data in the single chip microcomputer is performed to form a multi-dimensional data fusion data set, which specifically includes:

Acquiring real-time acquired online acquisition information in a storage area of a singlechip, carrying out online analysis on the online acquisition information, calculating integral deviation by using a first calculation formula, judging whether the integral deviation meets a second calculation formula, if so, considering that the data meets the requirement, further carrying out multi-dimensional data filtering in the same time period, stamping a time stamp, if not, considering that the data does not meet the requirement, directly deleting the data, taking the time stamped data as original data, and carrying out low-pass filtering and Kalman filtering processing on the original data to remove noise, wherein the first calculation formula is as follows:

PC=

The second calculation formula is as follows:

{Max(PC)-Min(PC)}÷Max(PC)<Y

First, acceleration and angular velocity information of the vehicle is acquired in real time by an Inertial Measurement Unit (IMU). Meanwhile, the vehicle-mounted GPS module is utilized to acquire geographic position information of the vehicle, including longitude, latitude, altitude and the like. In addition, the vertical displacement amount caused by the road surface unevenness during the running of the vehicle is detected by a bump height sensor mounted on the vehicle chassis or other critical position. Together, these data form the basis for online information collection. And transmitting the acquired data to the singlechip through the SPI interface. In this process, it is necessary to set an SPI interface channel and configure related communication parameters such as baud rate, data bit sequence, etc. to ensure accurate transmission of data. After receiving the data, the singlechip firstly obtains the online information acquired in real time in the storage area. Then, on-line analysis is performed on the on-line acquired information, and an integral deviation (PC) is calculated using a first calculation formula. Specifically, PC is the integral deviation, P (t) is the absolute value of the deviation of each data corresponding to the historical average at time t, and n is the total duration. Next, it is determined whether the integral deviation satisfies a second calculation formula. If the data is satisfied, the data is considered to satisfy the requirement, the multi-dimensional data is further subjected to filtering processing in the same time period, and a time stamp is marked, and if the data is not satisfied, the data is considered to be unsatisfied, and the data is directly deleted. And carrying out multidimensional data fusion on the screened data. This includes combining acceleration, angular velocity, GPS information, and bump height information, etc. to form a comprehensive data set. Meanwhile, in order to remove noise and improve data quality, the time-stamped data is subjected to low-pass filtering and kalman filtering processing as original data. After the pretreatment step, a clean and accurate multidimensional data fusion data set is finally obtained. This data set may be used for advanced applications such as subsequent gesture analysis, data processing and status determination.

As shown in fig. 5, in one or more embodiments, preferably, the performing gesture analysis online and performing comprehensive data validity determination in combination with GIS and bump height specifically includes:

The method comprises the steps of calculating three-axis Euler angles by using a six-axis fusion algorithm, judging whether jump meeting a third calculation formula exists among the pitch angle, the roll angle and the yaw angle, starting a historical map analysis module if the jump meeting the third calculation formula exists, analyzing whether the bump height of a road section passing by the last 1 minute meets the fourth calculation formula on line by the historical map analysis module, judging that the road section currently belongs to abnormal rotation if the road section is not met, judging whether GIS auxiliary judgment data exists for the abnormal rotation, eliminating the current data if the data does not exist, judging whether the three-axis Euler angles meet the fifth calculation formula through GIS data if the data exists, and determining that the data is valid and the data is deleted in a regular way if the data is met, wherein the third calculation formula is as follows:

YD>Y2

HD>Y3

PD>Y4

the fourth calculation formula is as follows:

YF>ST

The fifth calculation formula is:

YD-GP>Y5

HD-GP>Y6

PD-GP>Y7

Three-axis euler angles of the vehicle, including Pitch angle (Pitch), roll angle (Roll) and Yaw angle (Yaw), are calculated from accelerometer and gyroscope data using a six-axis fusion algorithm. These angles describe the rotational attitude of the vehicle in three dimensions. And judging whether abnormal jump exists in the pitch angle, the roll angle and the yaw angle or not by using a third calculation formula. The formula judges whether jump exists or not by comparing the average change rate of each angle in the last minute with a preset comparison margin. If the rate of change of either angle exceeds the corresponding contrast margin (Y2, Y3, Y4), then a jump is deemed to be present. And if the angle jump is detected, starting a historical map analysis module. The module analyzes the bump height data of the road section passed by the last minute and judges whether the fourth calculation formula is satisfied. If not, the data is considered to be abnormal rotation, and if so, the data is considered to be normal. And further judging whether GIS auxiliary judging data exist under the abnormal rotation condition. If the GIS data is not supported, the current data is rejected, and if the GIS data is supported, the fifth calculation formula is used for further verification. The formula judges the validity of the data by comparing the change rate of each angle with the difference of the GIS judging value. If the difference is within an acceptable range (defined by Y5, Y6, Y7), the data is considered valid. And a third calculation formula is used for judging angle jump, wherein YD, HD and PD are average change rates of pitch angle, roll angle and yaw angle in the last minute respectively, and Y2, Y3 and Y4 are preset comparison margins. And a fourth calculation formula for judging whether the bump height exceeds a preset maximum bump value ST, wherein YF is the maximum bump height within 1 minute. And a fifth calculation formula is used for carrying out final data validity judgment by combining GIS data, wherein GP is a GIS judgment value, and Y5, Y6 and Y7 are preset comparison margins.

In one or more embodiments, as shown in fig. 6, the average analysis is preferably performed after obtaining six-axis data, which specifically includes:

after six-axis data are processed, the data are stored after delay for 20ms and stored in a preset data linked list, and the average change value of the first N data of the data linked list is calculated. In an embodiment of the invention, six-axis data of the vehicle, including three-axis acceleration and three-axis angular velocity, are acquired by an Inertial Measurement Unit (IMU). These data reflect the motion state of the vehicle in three dimensions in real time. The collected six-axis data is processed, which may include filtering, denoising, etc., to ensure accuracy and reliability of the data. After processing the six-axis data, a 20 millisecond delay is set. This delay may be to wait for synchronization of other related data or to ensure data integrity and consistency. After the delay is finished, the processed data are stored in a preset data link list. A data linked list is a data structure that allows elements to be dynamically added and deleted, well suited for storage and management of real-time data. An average change value is calculated for the first N data in the linked list of data. The "first N pieces of data" herein may be set according to actual demands, and may be set as data within the last minute or the last second, for example. When calculating the average change value, the first N pieces of data in the data chain table need to be traversed, the change amount of each piece of data is summed, and then divided by N to obtain the average change value. This average change value may reflect the movement trend and stability of the vehicle over a period of time. The calculated average change value is output and can be used for advanced applications such as subsequent gesture analysis, data processing and state judgment.

As shown in fig. 7, in one or more embodiments, preferably, the on-line status determination according to the average analysis result specifically includes:

According to the comparison of the calculated average change value and a preset turning threshold value, when judging that a sixth calculation formula is met, right turning state or right turning is carried out, and when not met, the turning state is considered to be ended, wherein the sixth calculation formula is as follows:

PB>Y8

PB is an average change value, and Y8 is a preset turning threshold value.

In an embodiment of the present invention, first, six-axis data of a vehicle, including three-axis acceleration and three-axis angular velocity, are acquired by an Inertial Measurement Unit (IMU). The collected six-axis data is then processed, possibly including filtering, denoising, etc. Next, after the six-axis data is processed, a delay of 20ms is set, and the processed data is stored in a preset data link table. Finally, an average change value is calculated for the first N data in the linked list of data. And according to the comparison of the calculated average change value and a preset turning threshold value, when judging that the sixth calculation formula is met, considering that the vehicle is in a right turning state or is about to turn right, and if the vehicle is not met, considering that the turning state is ended. The sixth calculation formula is PB > Y8, wherein PB is an average change value, and Y8 is a preset turning threshold. This formula is used to determine whether the turning condition is satisfied. And outputting the result of the state judgment, and being applicable to advanced applications such as subsequent gesture analysis, data processing, state judgment and the like.

the data acquisition module 801 is configured to acquire information by using an inertial measurement unit, so as to obtain online acquisition information;

the data transmission module 802 is configured to transmit the online acquisition information to the singlechip through an SPI interface;

The data preprocessing module 803 is used for preprocessing data in the singlechip to form a multi-dimensional data fusion data set;

The gesture calculation module 804 is configured to perform gesture analysis online and perform comprehensive data validity judgment by combining GIS and bump height;

The data processing module 805 is configured to perform average analysis after obtaining six-axis data;

the state judging module 806 is configured to perform state judgment online according to the average value analysis result.

In the embodiment of the invention, a system suitable for different structures is realized through a series of modularized designs, and the system can realize closed-loop, reliable and efficient execution through acquisition, analysis and control.

According to a fourth aspect of an embodiment of the present invention, there is provided an electronic device. Fig. 9 is a block diagram of an electronic device in one embodiment of the invention. The electronic device shown in fig. 9 is a general implementation device for accurately detecting a right turn of a vehicle. The electronic device can be a smart phone, a tablet computer and the like. As shown, the electronic device 900 includes a processor 901 and a memory 902. The processor 901 is electrically connected to the memory 902. Processor 901 is a control center of terminal 900 that connects the various parts of the overall terminal using various interfaces and lines, and performs various functions of the terminal and processes data by running or calling computer programs stored in memory 902, and calling data stored in memory 902, thereby performing overall monitoring of the terminal.

In this embodiment, a processor 901 in an electronic device 900 loads instructions corresponding to the processes of one or more computer programs into a memory 902 according to the following steps, and the processor 901 runs the computer programs stored in the memory 902, so as to realize various functions, namely, information acquisition is performed by using an inertial measurement unit to obtain on-line acquisition information, the on-line acquisition information is transmitted to a singlechip through an SPI interface, preprocessing of data is performed on the singlechip to form a multi-dimensional data fusion data set, on-line gesture analysis is performed and comprehensive data validity judgment is performed by combining GIS and bump height, average value analysis is performed after six-axis data is obtained, and on-line state judgment is performed according to the average value analysis result.

Memory 902 may be used to store computer programs and data. The memory 902 stores a computer program having instructions executable in a processor. The computer program may constitute various functional modules. The processor 901 executes various functional applications and data processing by calling a computer program stored in the memory 902.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims

1. The implementation method for accurately detecting the right turn of the vehicle is characterized by comprising the following steps of:

After six-axis data are obtained, average value analysis is carried out;

carrying out on-line state judgment according to the average value analysis result;

The method comprises the steps of carrying out attitude analysis on line and carrying out comprehensive data validity judgment by combining GIS and bump height, and specifically comprises the following steps:

the third calculation formula is as follows:

YD>Y2

HD>Y3

PD>Y4

the fourth calculation formula is as follows:

YF>ST

The fifth calculation formula is:

YD-GP>Y5

HD-GP>Y6

PD-GP>Y7

2. The method for accurately detecting right turn of vehicle according to claim 1, wherein the information acquisition is performed by using an inertial measurement unit to obtain on-line acquisition information, specifically comprising:

acquiring GPS information through a vehicle-mounted GPS;

the bump height information is obtained through a vehicle-mounted sensor;

3. The method for accurately detecting the right turn of the vehicle according to claim 1, wherein the on-line acquisition information is transmitted to the singlechip through the SPI interface, specifically comprising:

Setting an SPI interface channel;

4. The method for accurately detecting right turn of vehicle according to claim 1, wherein the preprocessing of data is performed in a single chip microcomputer to form a multi-dimensional data fusion data set, specifically comprising:

The first calculation formula is as follows:

PC=

The second calculation formula is as follows:

{Max(PC)-Min(PC)}÷Max(PC)<Y

5. The method for accurately detecting right turn of a vehicle according to claim 1, wherein the average analysis is performed after six-axis data are obtained, specifically comprising:

6. The method for accurately detecting right turn of vehicle according to claim 1, wherein the on-line state determination according to the average analysis result comprises:

the sixth calculation formula is:

PB>Y8

PB is an average change value, and Y8 is a preset turning threshold value.

7. A system for implementing accurate detection of right turns of a vehicle, characterized in that the system is adapted to implement a method according to any one of claims 1-6, the system comprising:

8. A computer readable storage medium, on which computer program instructions are stored, which computer program instructions, when executed by a processor, implement the method of any of claims 1-6.

9. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method of any of claims 1-6.