CN114737455A

CN114737455A - Pavement detection method, device and equipment

Info

Publication number: CN114737455A
Application number: CN202210421702.1A
Authority: CN
Inventors: 陈野; 张骞; 杨明; 周欣如; 章婉霞; 赵红宇; 承楠
Original assignee: Neusoft Corp
Current assignee: Neusoft Corp
Priority date: 2022-04-21
Filing date: 2022-04-21
Publication date: 2022-07-12
Anticipated expiration: 2042-04-21
Also published as: CN114737455B

Abstract

The application discloses a road surface detection method, a road surface detection device and road surface detection equipment, which are used for collecting the acceleration of a vehicle in the vertical direction and the position of the vehicle in real time. When the vertical direction acceleration of the vehicle meets a first preset condition, the vibration moment of the front wheels, the first vertical direction acceleration, the position of the target vehicle and a first acceleration sequence comprising the first vertical direction acceleration at the moment are obtained. And determining the estimated rear wheel vibration time interval according to the front wheel vibration time. And in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets a first preset condition, acquiring a second vertical direction acceleration and a second acceleration sequence comprising the second vertical direction acceleration. And calculating the correlation degree of the first acceleration sequence and the second acceleration sequence. And when the degree of correlation satisfies a preset range, determining that the road surface at the target vehicle position is an uneven road surface. The method is suitable for different vehicle parameters, so that the detection accuracy of the uneven road surface is high.

Description

Pavement detection method, device and equipment

Technical Field

The present disclosure relates to the field of detection technologies, and in particular, to a method, an apparatus, and a device for detecting a road surface.

Background

In general, uneven road surfaces, such as depressed road surfaces and raised road surfaces, are present on roads. When the vehicle runs on an uneven road surface, the abrasion of the vehicle is accelerated and even accidents are caused. Therefore, it is important to determine the position of the rough road surface and to perform maintenance and repair on the rough road surface.

In order to solve the problem, some vehicles have an uneven road surface detection function, and can acquire position information of the uneven road surface and send the position information to relevant departments in the driving process so as to improve the road surface repairing efficiency.

Currently, some vehicles detect rough surfaces by collecting data with an acceleration sensor and comparing the collected data with a fixed threshold. However, since the vehicle parameters of different vehicles are different, the threshold is fixed in such a way that the accuracy of the detection result is low.

Disclosure of Invention

In order to solve the technical problem, the application provides a road surface detection method, a road surface detection device and road surface detection equipment, which can improve the accuracy of uneven road surface detection.

In order to achieve the above purpose, the technical solutions provided in the embodiments of the present application are as follows:

the embodiment of the application provides a road surface detection method, which comprises the following steps:

acquiring the acceleration of the vehicle in the vertical direction and the position of the vehicle in real time;

acquiring the vibration moment of a front wheel, the first vertical acceleration and the position of a target vehicle when the vertical acceleration of the vehicle meets a first preset condition;

acquiring a first acceleration sequence comprising the first vertical direction acceleration;

determining an estimated rear wheel vibration time interval according to the front wheel vibration moment;

within the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets the first preset condition, acquiring a second vertical direction acceleration meeting the first preset condition;

acquiring a second acceleration sequence comprising the second vertical direction acceleration;

and calculating the correlation degree of the first acceleration sequence and the second acceleration sequence, and determining that the road surface at the position of the target vehicle is in an uneven state if the correlation degree meets a preset range.

In one possible implementation, the uneven state includes a dimpled state or a raised state, and the method further includes:

acquiring a plurality of pre-selected acceleration sequences; the preselected acceleration sequence corresponds to a label; the label comprises a dimpled state or a raised state;

if the acceleration of the vehicle in the vertical direction meets the first preset condition within the estimated rear wheel vibration time interval, forming a target acceleration sequence by the first acceleration sequence and the second acceleration sequence;

respectively calculating a normalized path distance between the target acceleration sequence and each preselected acceleration sequence based on a dynamic time normalization algorithm;

and determining the label corresponding to the preselected acceleration sequence with the regular path distance meeting a third preset condition as the label of the road surface at the position of the target vehicle.

In one possible implementation, the method further includes:

collecting steering wheel angle data of a vehicle in real time;

and in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle does not meet the first preset condition and the steering wheel angle data of the vehicle meets the second preset condition, determining that the road surface at the position of the target vehicle is in an uneven state.

if the acceleration of the vehicle in the vertical direction does not meet the first preset condition and the steering wheel angle data of the vehicle meets the second preset condition within the estimated rear wheel vibration time interval, taking the first acceleration sequence as a target acceleration sequence;

In one possible implementation, the method further includes:

and in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle does not meet the first preset condition and the steering wheel angle data of the vehicle does not meet the second preset condition, determining that the road surface at the position of the target vehicle is in a flat state.

In one possible implementation, the obtaining a first acceleration sequence including the first vertical direction acceleration includes:

acquiring an adjacent first acceleration subsequence before the first vertical acceleration; the length of the adjacent first acceleration subsequence is a first acceleration sampling length;

acquiring an adjacent second acceleration subsequence after the first vertical acceleration; the adjacent second acceleration subsequence is a second acceleration sampling length;

forming the adjacent first acceleration sub-sequence, the first vertical direction acceleration and the adjacent second acceleration sub-sequence into a first acceleration sequence;

the obtaining a second acceleration sequence including the second vertical direction acceleration comprises:

acquiring an adjacent third acceleration subsequence before the second vertical acceleration; the length of the adjacent third acceleration subsequence is a third acceleration sampling length;

acquiring an adjacent fourth acceleration subsequence after the second vertical acceleration; the adjacent fourth acceleration subsequence is a fourth acceleration sampling length;

grouping the adjacent third acceleration sub-sequence, the second vertical direction acceleration, and the adjacent fourth acceleration sub-sequence into a second acceleration sequence.

In a possible implementation manner, the first acceleration sample length, the second acceleration sample length, the third acceleration sample length, and the fourth acceleration sample length are determined according to a preset uneven road section length, a vehicle speed, a vehicle acceleration sample rate, and a sample point selection coefficient.

In a possible implementation manner, the determining an estimated rear wheel vibration time interval according to the front wheel vibration time includes:

calculating an interval time period according to the vehicle wheel base and the vehicle speed;

determining the moment when the vibration moment of the front wheel passes the interval time period as a target moment;

acquiring an adjacent first estimated rear wheel vibration time subinterval before the target moment and an adjacent second estimated rear wheel vibration time subinterval after the target moment;

and forming the estimated rear wheel vibration time interval by the adjacent first estimated rear wheel vibration time sub-interval, the target time and the adjacent second estimated rear wheel vibration time sub-interval.

The embodiment of the present application further provides a road surface detection device, the device includes:

the first acquisition unit is used for acquiring the acceleration of the vehicle in the vertical direction and the position of the vehicle in real time;

the vehicle control device comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring the vibration time of front wheels, the first vertical acceleration and the target vehicle position when the vertical acceleration of the vehicle meets a first preset condition;

a second acquisition unit configured to acquire a first acceleration sequence including the first vertical-direction acceleration;

the first determining unit is used for determining the estimated rear wheel vibration time interval according to the front wheel vibration time;

a third obtaining unit, configured to obtain, within the predicted rear wheel vibration time interval, a second vertical acceleration when a first preset condition is met when the vertical acceleration of the vehicle meets the first preset condition;

a fourth acquisition unit configured to acquire a second acceleration sequence including the second vertical-direction acceleration;

and the first calculation unit is used for calculating the correlation degree of the first acceleration sequence and the second acceleration sequence, and if the correlation degree meets a preset range, determining that the road surface at the position of the target vehicle is in an uneven state.

The embodiment of the application further provides a road surface detection device, including: the road surface detection device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the computer program, the road surface detection method is realized according to any one of the above items.

The embodiment of the application also provides a computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, and when the instructions are run on the terminal device, the terminal device is enabled to execute the road surface detection method according to any one of the above items.

According to the technical scheme, the method has the following beneficial effects:

the embodiment of the application provides a road surface detection method, a road surface detection device and road surface detection equipment, which are used for acquiring the acceleration of a vehicle in the vertical direction and the position of the vehicle in real time. When the vertical direction acceleration of the vehicle meets a first preset condition, the vibration of the front wheels of the vehicle is indicated. The front wheel shaking time, the first vertical direction acceleration, the target vehicle position, and the first acceleration sequence including the first vertical direction acceleration at this time are acquired. And determining the estimated rear wheel vibration time interval according to the front wheel vibration time. And in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets a first preset condition, the rear wheel of the vehicle is shown to be vibrated. The second vertical-direction acceleration at this time and a second acceleration sequence including the second vertical-direction acceleration are acquired. When the front wheel and the rear wheel of the vehicle pass through the uneven road surface at the same position to cause the wheel vibration, the correlation degree of the first acceleration sequence and the second acceleration sequence can meet the preset range. Therefore, the degree of correlation of the first acceleration sequence and the second acceleration sequence is calculated. When the correlation degree meets the preset range, determining that the vibration of the front wheel and the rear wheel of the vehicle is the vibration caused by passing through an uneven road surface at the same position, wherein the uneven road surface is the road surface at the target vehicle position. Therefore, the method for determining whether the road surface is uneven through calculating the correlation degree of the first acceleration sequence when the front wheels are likely to vibrate and the second acceleration sequence when the rear wheels are likely to vibrate is suitable for different vehicle parameters, and the detection accuracy of the uneven road surface is high.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic diagram of a framework of an exemplary application scenario provided in an embodiment of the present application;

fig. 2 is a flowchart of a road surface detection method according to an embodiment of the present disclosure;

fig. 3 is a flowchart of another road surface detection method provided in the embodiment of the present application;

fig. 4 is a schematic structural diagram of a road surface detection device according to an embodiment of the present application.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, embodiments accompanying figures and detailed description thereof are described in further detail below.

In order to facilitate understanding and explaining the technical solutions provided by the embodiments of the present application, the following first describes the background art of the embodiments of the present application.

In general, uneven road surfaces, such as depressed road surfaces and raised road surfaces, are present on roads. When the vehicle runs on an uneven road, the vehicle is accelerated to wear and even cause accidents. Therefore, it is important to determine the position of the rough road surface and to perform maintenance and repair on the rough road surface.

Specifically, some vehicles acquire road surface images using on-board video equipment, and process and analyze the road surface images to obtain road surface detection results. However, the road surface image is affected by the brightness of light, so that the accuracy of the road surface detection result is not high. In addition, some vehicles collect acceleration data via an acceleration sensor, compare the collected acceleration data to a fixed threshold, and determine that the road surface is uneven when the fixed threshold is exceeded. However, since the vehicle parameters of different vehicles are different, the same fixed threshold is used for judgment, and the accuracy is low.

Based on this, the embodiment of the application provides a road surface detection method, a road surface detection device and road surface detection equipment, which are used for acquiring the vertical direction acceleration and the vehicle position of a vehicle in real time. When the vertical direction acceleration of the vehicle meets a first preset condition, the vibration of the front wheels of the vehicle is indicated. The front wheel shaking time, the first vertical direction acceleration, the target vehicle position, and the first acceleration sequence including the first vertical direction acceleration at this time are acquired. And determining the estimated rear wheel vibration time interval according to the front wheel vibration time. And in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets a first preset condition, the rear wheel of the vehicle is shown to be vibrated. The second vertical-direction acceleration at this time and a second acceleration sequence including the second vertical-direction acceleration are acquired. When the vehicle wheel shakes due to the fact that the front wheel and the rear wheel of the vehicle pass through uneven road surfaces at the same position, the correlation degree of the first acceleration sequence and the second acceleration sequence can meet a preset range. Therefore, the degree of correlation of the first acceleration sequence and the second acceleration sequence is calculated. When the correlation degree meets the preset range, determining that the vibration of the front wheel and the rear wheel of the vehicle is the vibration caused by passing through an uneven road surface at the same position, wherein the uneven road surface is the road surface at the target vehicle position. Therefore, the method for determining whether the road surface is uneven is suitable for different vehicle parameters and enables the detection accuracy of the uneven road surface to be high.

In order to facilitate understanding of the road surface detection method provided in the embodiment of the present application, the following description is made with reference to a scene example shown in fig. 1. Referring to fig. 1, the figure is a schematic diagram of a framework of an exemplary application scenario provided in an embodiment of the present application.

In practical application, the vertical direction acceleration of the vehicle and the position of the vehicle are collected in real time.

When the vertical direction acceleration of the vehicle meets a first preset condition, determining that the front wheel of the vehicle shakes. But the cause of the front wheel shock cannot be determined at this time. The method comprises the steps of obtaining the vibration moment of a front wheel, the first vertical acceleration and the target vehicle position when the vertical acceleration of the vehicle meets a first preset condition. Further, a first acceleration sequence including a first vertical direction acceleration is acquired.

And determining the estimated rear wheel vibration time interval according to the front wheel vibration time. In the case where the front wheel vibration is caused by an uneven road surface, the rear wheel may pass through the same uneven road surface to generate vibration within an estimated time period of the rear wheel vibration.

In the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets a first preset condition, the rear wheel of the vehicle vibrates. At this time, the second vertical direction acceleration when the first preset condition is satisfied is acquired. Further, a second acceleration sequence including a second vertical direction acceleration is acquired.

And calculating the correlation degree of the first acceleration sequence and the second acceleration sequence, and if the correlation degree meets a preset range, indicating that the front wheel vibration and the rear wheel vibration are both caused by passing through the same uneven road surface. At this time, the road surface at the target vehicle position is determined to be in an uneven state.

Those skilled in the art will appreciate that the block diagram shown in fig. 1 is only one example in which embodiments of the present application may be implemented. The scope of applicability of the embodiments of the present application is not limited in any way by this framework.

In order to facilitate understanding of the present application, a road surface detection method provided in an embodiment of the present application is described below with reference to the accompanying drawings.

Referring to fig. 2, fig. 2 is a road surface detection method provided in the embodiment of the present application. As shown in fig. 2, the method includes S201-S207:

s201: the vertical direction acceleration of the vehicle and the vehicle position are collected in real time.

In practical applications, the acceleration sensor and the global positioning system GPS are mounted at the center of the top of the vehicle body by a magnet or other means. When the vehicle runs, the vertical direction acceleration of the vehicle and the position of the vehicle are collected in real time by using the vehicle-mounted acceleration sensor and the GPS.

As an alternative example, the acceleration sensor is a three-axis acceleration sensor.

S202: the method comprises the steps of obtaining the vibration moment of a front wheel, the first vertical acceleration and the target vehicle position when the vertical acceleration of the vehicle meets a first preset condition.

When the vehicle vibrates, the acceleration of the vehicle in the vertical direction obviously changes. Therefore, whether the vehicle is vibrated or not can be known by detecting the change of the vertical acceleration of the vehicle.

As an alternative example, it is detected in real time whether the vertical direction acceleration of the vehicle satisfies a first preset condition. When the vertical direction acceleration of the vehicle meets a first preset condition, the vehicle is considered to be vibrated due to the vibration of the front wheels of the vehicle.

It should be noted that, in the embodiment of the present application, when the vertical direction acceleration of the vehicle detected in real time satisfies the first preset condition, a scene in which the vehicle vibrates due to the vibration of the rear wheels of the vehicle is not considered. It should be noted that the vertical acceleration of the vehicle meeting the first preset condition in this step is the vertical acceleration that is acquired when the first preset condition is first met.

In one or more embodiments, the first preset condition is that the vertical direction acceleration of the vehicle is greater than a set first threshold value Y1.

And recording the vibration moment of the front wheels, the first vertical acceleration and the target vehicle position when the vertical acceleration of the vehicle meets a first preset condition. As an alternative example, the front wheel shaking time may be expressed in terms of a specific time, such as xx minutes xx seconds at xx times xx of xx months xx days in xx years.

As another alternative, the front wheel shake moment may also be represented by a discrete sampling moment of the acceleration sensor, for example, the sampling moment of the front wheel shake is a. The sampling time is the position of the sampling point acquired by the acceleration sensor, and when the sampling time of the vibration of the front wheel is a, the sampling point which represents the acceleration in the vertical direction when the front wheel vibrates is the a-th sampling point.

At the same time, the first vertical direction acceleration at this time is recorded as s_aThe target vehicle position is P_a。

It is understood that when determining the vibration of the front wheels of the vehicle, it is impossible to determine whether the vibration is caused by the front wheels of the vehicle passing over an uneven road surface or the vibration is caused by the noise of the vehicle, for example, the vibration of the front wheels of the vehicle caused by the sudden and large movement of the person in the rear row of the vehicle. Thus, further determination is required.

S203: a first acceleration sequence including a first vertical direction acceleration is acquired.

Since it is impossible to determine whether the vibration is caused by the front wheels of the vehicle passing over an uneven road surface or the vibration is caused by the noise of the vehicle. At this time, based on the first vertical-direction acceleration, a first acceleration sequence including the first vertical-direction acceleration is acquired, and the first acceleration sequence is used for subsequently determining whether the vehicle vibration is vibration caused by passing over an uneven road surface.

It is understood that the first vertical acceleration is only a certain acceleration value collected when the front wheel of the vehicle is vibrated, and if the vehicle is vibrated due to an uneven road, the uneven road may have a certain length, and the vertical acceleration data when the vehicle is vibrated when the front wheel of the vehicle passes through the uneven road is not only a value. Therefore, the acquired first acceleration sequence may be understood as vehicle vibration data generated when the front wheels of the vehicle may pass over an uneven road surface in a case where the vehicle is vibrated by the uneven road surface.

In one possible implementation, the present application provides a specific implementation manner of obtaining a first acceleration sequence including a first vertical direction acceleration, which is described in detail in a1-A3 below.

S204: and determining the estimated vibration time interval of the rear wheel according to the vibration time of the front wheel.

In general, if the vehicle vibration is a vehicle vibration caused by an uneven road surface, the vehicle rear wheel may also pass through the uneven road surface at the same position to cause the vehicle rear wheel to vibrate after the vehicle front wheel vibrates and if the vehicle is not steered. Based on the time, the estimated rear wheel vibration time interval is determined according to the front wheel vibration time. The rear wheel vibration time interval is estimated, and the rear wheel of the vehicle can vibrate.

In a possible implementation manner, the embodiment of the present application provides a specific implementation manner for determining the estimated rear wheel vibration time interval according to the front wheel vibration time, which is described in detail in B1-B4 below.

S205: and in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets a first preset condition, acquiring a second vertical direction acceleration meeting the first preset condition.

And in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets a first preset condition, determining that the rear wheel of the vehicle vibrates again. The vehicle vibration at this time is caused by the vibration of the rear wheels of the vehicle which may pass through the same uneven road surface.

It should be noted that the vertical acceleration of the vehicle meeting the first preset condition in this step is the vertical acceleration when the first preset condition is first met in the estimated rear wheel vibration time interval.

Recording a second vertical direction acceleration as s when the first preset condition is met in the estimated rear wheel vibration time interval_cAnd recording the rear wheel vibration time and the vehicle position P at the moment_c. Wherein, the rear wheel vibration moment can be represented by a sampling moment, which is denoted as c. It is understood that the rear wheel vibration moment is the moment when the vehicle vibration actually occurs and is not estimated.

S206: a second acceleration sequence including a second vertical direction acceleration is acquired.

The vehicle vibration generated at the moment of front wheel vibration and the moment of rear wheel vibration is verified to be vibration caused by the fact that the vehicle passes through the same uneven road surface. And acquiring a second acceleration sequence comprising the second vertical direction acceleration based on the second vertical direction acceleration. The second acceleration sequence is used to subsequently determine whether the vehicle vibration is a vibration caused by passing over an uneven road surface.

It is understood that the second vertical acceleration is only a certain acceleration value collected when the rear wheel of the vehicle is vibrated, and if the vehicle is vibrated due to an uneven road, the uneven road may have a certain length, and when the front wheel of the vehicle passes through the uneven road, the vertical acceleration data of the vehicle when the vehicle is vibrated is not only a value. Therefore, the acquired second acceleration sequence may be understood as vehicle vibration data generated when the rear wheels of the vehicle may pass over an uneven road surface in a case where the vehicle is vibrated by the uneven road surface.

In a possible implementation manner, the present application provides a specific implementation manner of obtaining a second acceleration sequence including a second vertical direction acceleration, specifically see C1-C3 below.

S207: and calculating the correlation degree of the first acceleration sequence and the second acceleration sequence, and determining that the road surface at the position of the target vehicle is in an uneven state if the correlation degree meets a preset range.

The first acceleration sequence may be understood as vehicle vibration data generated when the front wheels of the vehicle may pass over an uneven road surface in a case where the uneven road surface causes the vehicle to vibrate. The second acceleration sequence may be understood as vehicle shock data generated when the rear wheels of the vehicle may pass over an uneven road surface in a case where the vehicle is caused to shock by the uneven road surface.

Moreover, if the front and rear wheels of the vehicle pass through an uneven road surface at the same position to cause the vehicle to vibrate, the correlation degree of the first acceleration sequence and the second acceleration sequence should satisfy a preset range. Specifically, when the vehicle shakes as the front and rear wheels of the vehicle pass through an uneven road surface at the same position, the correlation degree of the first acceleration sequence and the second acceleration sequence should satisfy negative correlation, that is, the theoretical value of the correlation degree is-1, which indicates that the first acceleration sequence and the second acceleration sequence are in negative correlation.

Based on this, the degree of correlation of the first acceleration sequence and the second acceleration sequence is calculated. Whether the vehicle front wheel vibration and rear wheel vibration are caused by passing over an uneven road surface is determined by whether the degree of correlation satisfies a preset range. As an alternative example, the preset range is less than a set second threshold Y2, such as-0.2.

In an alternative example, the correlation coefficient of the first acceleration sequence and the second acceleration sequence is calculated, and the correlation coefficient is used to represent the degree of correlation. Specifically, the calculation formula of the correlation coefficient of the first acceleration sequence and the second acceleration sequence is as follows:

wherein S is₁Is a first acceleration sequence, S₂In the form of a second sequence of accelerations,

is S₁And S₂The correlation coefficient of (2). Cov (S)₁,S₂)＝E(S₁S₂)-E(S₁)E(S₂)，cov(S₁,S₂) Denotes S₁And S₂E (-) represents the mathematical expectation and σ (-) represents the standard deviation.

If it is

When the preset range is met, the vehicle is determined to pass through the uneven road, and the vibration of the front wheels and the vibration of the rear wheels of the vehicle pass through the same uneven road, namely the road at the position of the target vehicle. At this time, the vehicle will position information P_aAnd the detection result is uploaded to the cloud platform and provided for relevant departments of highway maintenance, so that the pavement can be repaired in time. In order to make the detection result more detailed, P can also be used_cAnd also uploaded to the cloud platform. In addition, if

If the preset range is not met, the vehicle is considered to run on a flat road.

It can be understood that the method for judging whether the vehicle passes through the rough road by calculating the correlation degree of the first acceleration sequence and the second acceleration sequence can reduce the interference on the rough road caused by the vibration caused by the vehicle noise, and can be suitable for different vehicle parameters, so that the detection accuracy of the rough road is high.

Based on the contents of S201 to S207, the embodiment of the present application provides a road surface detection method, which collects the vertical acceleration of a vehicle and the vehicle position in real time. When the vertical direction acceleration of the vehicle meets a first preset condition, the vehicle front wheel is indicated to vibrate. The front wheel shaking time, the first vertical direction acceleration, the target vehicle position, and the first acceleration sequence including the first vertical direction acceleration at this time are acquired. And determining the estimated rear wheel vibration time interval according to the front wheel vibration time. And in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets a first preset condition, the rear wheel of the vehicle is shown to be vibrated. The second vertical-direction acceleration at this time and a second acceleration sequence including the second vertical-direction acceleration are acquired. When the front wheel and the rear wheel of the vehicle pass through the uneven road surface at the same position to cause the wheel vibration, the correlation degree of the first acceleration sequence and the second acceleration sequence can meet the preset range. Therefore, the degree of correlation of the first acceleration sequence and the second acceleration sequence is calculated. When the correlation degree meets the preset range, determining that the vibration of the front wheel and the rear wheel of the vehicle is the vibration caused by passing through an uneven road surface at the same position, wherein the uneven road surface is the road surface at the target vehicle position. Therefore, the method for determining whether the road surface is uneven through calculating the correlation degree of the first acceleration sequence when the front wheels are likely to vibrate and the second acceleration sequence when the rear wheels are likely to vibrate is suitable for different vehicle parameters, and the detection accuracy of the uneven road surface is high.

In a possible implementation manner, an embodiment of the present application provides a specific implementation manner of acquiring a first acceleration sequence including a first vertical direction acceleration in S203, where the specific implementation manner includes:

a1: acquiring an adjacent first acceleration subsequence before the first vertical acceleration; the length of the adjacent first acceleration subsequence is a first acceleration sample length.

A2: acquiring an adjacent second acceleration subsequence after the first vertical acceleration; the adjacent second acceleration subsequence is a second acceleration sample length.

After the first vertical acceleration is acquired, an adjacent first acceleration subsequence before the first vertical acceleration and an adjacent second acceleration subsequence after the first vertical acceleration are acquired based on the first vertical acceleration.

Before the first vertical acceleration, after the first vertical acceleration, specifically, before the sampling time of the first vertical acceleration, after the sampling time of the first vertical acceleration. The adjacent first acceleration subsequence and the adjacent second acceleration subsequence are both adjacent to the first vertical acceleration.

In one or more embodiments, the first acceleration sample length and the second acceleration sample length are determined according to a preset uneven road section length, a vehicle speed, a vehicle acceleration sample rate and a sample point selection coefficient.

Specifically, the vehicle acceleration sensor sampling rate is h. For example, at a sampling rate of 500 hz, 500 samples (i.e., vertical acceleration) may be taken for 1 second. The vehicle speed is v meters per second. The acceleration sampling length is d, which represents a total of d sampling points, and the calculation formula is as follows:

wherein r is the length of the preset uneven road segment. The uneven state includes a dimpled state or a raised state. When the uneven road surface is in a convex state, the length of the uneven road surface is preset to be the length of the convex road surface. When the uneven road surface is in a hollow state, the length of the uneven road surface is preset to be the length of the hollow road surface. The predetermined uneven road section length is determined empirically, for example, to be 0.3 meters.

Beta is a sampling point selection coefficient, and in order to more fully cover the vehicle vibration data, the sampling point selection coefficient is generally larger than 1/2, for example 2/3 is preferable. The symbol [. cndot. ] represents rounding up.

For example, if h is 500, v is 10, r is 0.3, β is 2/3, and d is 10.

That is, both the first acceleration sample length and the second acceleration sample length may be determined according to the above calculation formula of the acceleration sample length d. It can be understood that, when the first acceleration sample length and the second acceleration sample length are calculated separately, if the parameters in the above formula are different, the calculated first acceleration sample length and the calculated second acceleration sample length are different, and if the parameters in the formula are the same, the calculated first acceleration sample length and the calculated second acceleration sample length are the same.

It should be noted that, the first acceleration sample length and the second acceleration sample length are not limited in the embodiments of the present application, and may be determined according to actual situations. As an alternative example, the first acceleration sample length and the second acceleration sample length are the same.

For example, when the length of the first acceleration subsequence and the second acceleration subsequence is the same and the length is denoted by d, the first vertical acceleration s is recorded and saved_aRespectively mining d in front and at backAnd (6) sampling points. Obtaining a first acceleration subsequence as s_a-d,…,s_a-1]The second acceleration sub-sequence is [ s ]_a+1,…,s_a+d]。

A3: the adjacent first acceleration sub-sequence, the first vertical direction acceleration and the adjacent second acceleration sub-sequence are combined into a first acceleration sequence.

After acquiring the adjacent first acceleration subsequence and the adjacent second acceleration subsequence, the adjacent first acceleration subsequence, the first vertical-direction acceleration and the adjacent second acceleration subsequence form a first acceleration sequence, and the first acceleration sequence is recorded as S₁I.e. S₁＝[s_a-d,…,s_a-1,s_a,s_a+1,…,s_a+d]。

It will be appreciated that the first acceleration sequence may be vehicle body vibration data generated when the front wheels of the vehicle traverse an uneven road surface.

Based on the contents of a1-A3, an adjacent first acceleration sub-sequence and an adjacent second acceleration sub-sequence of the first vertical direction acceleration can be determined based on the first vertical direction acceleration and the first acceleration sample length and the second acceleration sample length. Further, a first acceleration sequence consisting of an adjacent first acceleration subsequence, a first vertical direction acceleration and an adjacent second acceleration subsequence may be obtained.

In a possible implementation manner, an embodiment of the present application provides a specific implementation manner that in S204, an estimated rear wheel vibration time interval is determined according to a front wheel vibration time, including:

b1: the interval period is calculated based on the vehicle wheel base and the vehicle speed.

The spacing between the front wheels of the vehicle and the rear wheels of the vehicle may be expressed in terms of the vehicle wheelbase. When the front wheel and the rear wheel of the vehicle pass through the same uneven road surface, the moving distance of the vehicle is the distance expressed by the wheel base of the vehicle.

Then in this step the interval period is the quotient of the vehicle wheel base and the vehicle speed, representing the estimated interval between when the rear wheels of the vehicle might vibrate and when the front wheels of the vehicle vibrate.

As an alternative example, the interval period may be represented by a specific time. For example, the vehicle wheelbase is L, for example the vehicle wheelbase is 3 meters. And b is the interval time period, and b is L/v. For example, v is 10, L is 3, and b is 0.3 s.

As an alternative example, the interval period may be represented by a sample time. For example, if the vehicle wheel base is L, for example, the vehicle wheel base is 3 meters, and the interval period is b, then b is [ h (L/v) ]. For example, h is 500, v is 10, L is 3, and b is 150. b represents the estimated number of sampling points between when the rear wheel of the vehicle is likely to vibrate and when the front wheel vibrates.

B2: the time when the front wheel shaking time has elapsed the interval period is determined as the target time.

The target time is the estimated time when the rear wheel of the vehicle may vibrate.

For example, if the front wheel vibration timing is 3s and the interval period is 0.3s, the timing when the interval period elapses from the front wheel vibration timing is 3.3s, and this timing is determined as the target timing.

As another example, when the front wheel vibration timing is represented by the discrete sampling timing a, the target timing is represented by a + b.

B3: and acquiring an adjacent first estimated rear wheel vibration time subinterval before the target time and an adjacent second estimated rear wheel vibration time subinterval after the target time.

Since the vehicle rear wheel shock does not occur at only one target time, it may last for a period of time. Therefore, an adjacent first estimated rear wheel vibration time subinterval before the target time and an adjacent second estimated rear wheel vibration time subinterval after the target time are obtained.

And the target time and the adjacent second predicted rear wheel vibration time subinterval are some predicted time periods and moments when the rear wheel of the vehicle may vibrate.

B4: and forming the pre-estimated rear wheel vibration time interval by the adjacent first pre-estimated rear wheel vibration time sub-interval, the target time and the adjacent second pre-estimated rear wheel vibration time sub-interval.

It is understood that the time interval of the estimated rear wheel vibration after the composition is the time interval of the estimated rear wheel vibration after the front wheel of the vehicle is vibrated.

As an alternative example, the estimated rear wheel vibration time interval is represented by a specific time period. For example, when the target time is 3.3s, and the adjacent first estimated rear wheel vibration time sub-interval and the adjacent second estimated rear wheel vibration time sub-interval are both 1s, the estimated rear wheel vibration time interval is 2.3s to 4.3 s.

As an alternative example, the estimated rear wheel shock time interval may be represented by a sample time. For example, when the adjacent first estimated rear wheel vibration time subinterval and the adjacent second estimated rear wheel vibration time subinterval are both represented by d sampling points in sampling time, the estimated rear wheel vibration time subinterval is from a + b-d sampling time to a + b + d sampling time.

Based on B1-B4, the estimated rear wheel vibration time can be obtained based on the interval time period and the front wheel vibration time, and the estimated rear wheel vibration time interval can be obtained.

In a possible implementation manner, an embodiment of the present application provides a specific implementation manner of acquiring a second acceleration sequence including a second vertical direction acceleration in S206, where the specific implementation manner includes:

c1: acquiring an adjacent third acceleration subsequence before the second vertical acceleration; the length of the adjacent third acceleration subsequence is a third acceleration sample length.

C2: acquiring an adjacent fourth acceleration subsequence after the second vertical acceleration; the adjacent fourth acceleration subsequence is a fourth acceleration sample length.

After the second vertical acceleration is acquired, an adjacent third acceleration subsequence before the second vertical acceleration and an adjacent fourth acceleration subsequence after the second vertical acceleration are acquired based on the second vertical acceleration.

Before the second vertical acceleration, after the second vertical acceleration, specifically, before the sampling time of the second vertical acceleration, after the sampling time of the second vertical acceleration. And the adjacent third acceleration subsequence and the adjacent fourth acceleration subsequence are adjacent to the second vertical acceleration.

In one or more embodiments, the third acceleration sample length and the fourth acceleration sample length are each determined according to a preset uneven road section length, a vehicle speed, a vehicle acceleration sample rate, and a sample point selection coefficient. See a2 for details of implementation.

It is understood that, the third acceleration sample length and the fourth acceleration sample length are not limited in the embodiments of the present application, and may be determined according to actual situations. As an alternative example, the first, second, third and fourth acceleration sample lengths are the same.

For example, when the length of the third acceleration subsequence is the same as that of the fourth acceleration subsequence and the length is denoted by d, the second vertical acceleration s is recorded and saved_cAnd d sampling points respectively before and after. Obtaining a third acceleration sub-sequence of [ s ]_c-d,…,s_c-1]The fourth acceleration sub-sequence is [ s ]_c+1,…,s_c+d]。

C3: and combining the adjacent third acceleration subsequence, the second vertical direction acceleration and the adjacent fourth acceleration subsequence into a second acceleration sequence.

After the adjacent third acceleration subsequence and the adjacent fourth acceleration subsequence are obtained, the adjacent third acceleration subsequence, the second vertical-direction acceleration and the adjacent fourth acceleration subsequence are combined into a second acceleration sequence which is marked as S₂I.e. S₂＝[s_c-d,…,s_c-1,s_c,s_c+1,…,s_c+d]And d can be referred to as A2.

It will be appreciated that the second acceleration sequence may be body vibration data generated when the rear wheels of the vehicle traverse an uneven road surface.

Based on the contents of C1-C3, an adjacent third acceleration sub-sequence and an adjacent fourth acceleration sub-sequence of the second vertical direction acceleration may be determined based on the second vertical direction acceleration and the third acceleration sample length and the fourth acceleration sample length. Further, a second acceleration sequence consisting of an adjacent third acceleration subsequence, a second vertical direction acceleration and an adjacent fourth acceleration subsequence may be obtained.

It is understood that S204 describes a situation where the front wheels of the vehicle are vibrating, the vehicle is not turning, and the rear wheels of the vehicle are passing through the same uneven road surface. However, there are situations where the driver of the vehicle is aware of the shock occurring at the front wheels of the vehicle and turns the steering wheel to steer the vehicle to avoid the rear wheels of the vehicle passing over the same uneven road surface. Based on this, the embodiment of the application also discloses the technical details for judging whether the vibration of the front wheels of the vehicle is caused by the uneven road surface in the condition. The method specifically comprises the following steps:

d1: and collecting steering wheel angle data of the vehicle in real time.

The vehicle can acquire the steering wheel angle data of the vehicle in real time through the angle sensor.

D2: and in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle does not meet a first preset condition and the steering wheel corner data of the vehicle meets a second preset condition, determining that the road surface at the position of the target vehicle is in an uneven state.

And in the estimated rear wheel vibration time interval, if the vertical direction acceleration of the vehicle does not meet a first preset condition all the time, detecting steering wheel angle data of the vehicle. If the steering wheel corner data of the vehicle, it is determined that the front wheels of the vehicle pass through an uneven road surface when vibrating, and the driver rotates the steering wheel to realize avoidance adjustment in order to avoid the secondary vibration of the rear wheels.

As an alternative example, the second preset condition is that the steering wheel angle exceeds a set third threshold. The set third threshold may be set according to actual conditions, and is not limited in the embodiment of the present application.

In addition, if the vertical direction acceleration of the vehicle does not meet a first preset condition and the steering wheel angle data of the vehicle does not meet a second preset condition within the estimated rear wheel vibration time interval, the road surface at the position of the target vehicle is determined to be in a flat state. That is, when the steering wheel angle is always smaller than the set third threshold value, it is determined that the vehicle vibration caused at the time of the front wheel vibration is noise. Therefore, the detection misjudgment caused by the vibration noise of the vehicle body can be overcome by detecting the steering wheel angle data of the vehicle.

Since the uneven state of the road surface includes a pothole state or a bump state, after the vehicle is determined to pass through the uneven road surface to cause the vehicle to shake, the uneven state of the vehicle can be continuously identified as the pothole state or the bump state. Wherein, the vehicle vibration can be determined to be caused by the road surface unevenness under the condition of two vehicle vibration conditions. One is determined in the case where both the front and rear wheels of the vehicle are vibrated (see S201 to S207). The other is determined in the case where only the front wheels of the vehicle are vibrated and the rear wheels of the vehicle are subjected to avoidance adjustment (see D1-D2). In a first vehicle vibration situation, a first acceleration sequence and a second acceleration sequence may be acquired. In the second vehicle vibration situation, only the first acceleration sequence can be acquired.

Based on the above, in a first vehicle vibration situation, in a possible implementation manner, an embodiment of the present application provides a specific implementation manner for identifying an uneven state of a vehicle, including:

e1: acquiring a plurality of pre-selected acceleration sequences; the preselected acceleration sequence corresponds to a label; the label includes a dimpled state or a raised state.

It will be appreciated that the preselected acceleration sequence may be used as a reference sequence for a series of seismic accelerations generated by the vibrations of the vehicle during actual travel of the vehicle. In the first vehicle vibration condition, the vibration acceleration sequence is a first acceleration sequence and a second acceleration sequence. In the second vehicle vibration situation, the vibration acceleration sequence is only the first acceleration sequence.

There are a plurality of pre-selected acceleration sequences, and each pre-selected acceleration sequence has a respective tag. Wherein the label comprises a dimpled state or a raised state. For example, the tag corresponding to the preselected acceleration sequence 1 is in a hole state. The tag corresponding to the preselected acceleration sequence 1 is in a convex state.

The preselected acceleration sequence needs to be collected and stored in advance, for example, when the uneven road surface is a pothole road surface, the acceleration sequence generated by vehicle vibration when the vehicle speed is 8m/s (or 10m/s, 12m/s, 14m/s and the like) and the road pothole length is 0.2m (or 0.3m, 0.4m and the like) is collected and is used as the preselected acceleration sequence, and the corresponding label is recorded as the pothole state. The vehicle speed is a vehicle parameter, and the length of the pits or bulges on the road surface is a road parameter. The acquisition and storage process of the preselected acceleration sequence when the uneven road surface is in a convex state is similar to the above content, and the details are not repeated here.

In addition, under each set of the vehicle parameter and the road parameter, it is necessary to separately store the acceleration sequence of the vehicle front and rear wheel combination and the acceleration sequence of only the vehicle front wheel, corresponding to two vehicle vibration cases where both the vehicle front and rear wheels vibrate and where only the vehicle front wheel vibrates. For both the dimpled state and the bumped state, a plurality of preselected acceleration sequences of different lengths are assigned. Therefore, the identification of the uneven road surface state under different vehicle vibration conditions can be met.

E2: and if the acceleration of the vehicle in the vertical direction meets a first preset condition within the estimated rear wheel vibration time interval, forming a target acceleration sequence by the first acceleration sequence and the second acceleration sequence.

From S201 to S207, in the estimated rear wheel vibration time interval, the vertical direction acceleration of the vehicle satisfies the first preset condition and the correlation degree between the first acceleration sequence and the second acceleration sequence satisfies the preset range, which indicates that both the front and rear wheels of the vehicle are vibrated and are caused by the uneven road surface.

At this time, the first acceleration sequence and the second acceleration sequence can be acquired, and the first acceleration sequence and the second acceleration sequence are combined into the target acceleration sequence. The specific type of the road surface unevenness condition is identified based on a plurality of kinds of pre-selected acceleration sequences and a target acceleration sequence composed of a first acceleration sequence and a second acceleration sequence.

For example, the first acceleration sequence is S₁The second acceleration sequence is S₂The target acceleration sequence is S₃，S₃＝[s_a-d,…,s_a+d,s_c-d,…,s_c+d]. Further, the step S₃And matching with a plurality of pre-stored pre-selected acceleration sequences.

E3: and respectively calculating the normalized path distance between the target acceleration sequence and each pre-selected acceleration sequence based on a dynamic time normalization algorithm.

The dynamic time warping algorithm has a good detection effect on measuring the similarity of two time sequences, in addition, due to the fact that the lengths of pits, bulges and vehicle body parameters in an actual road are different, the lengths of various pre-selected acceleration sequences are inconsistent, and even if the lengths of a target acceleration sequence and the pre-selected acceleration sequence are different, the dynamic time warping algorithm can still calculate the warping path distance between the target acceleration sequence and each pre-selected acceleration sequence. Based on this, as an alternative example, a dynamic time warping algorithm is used to calculate the warped path distance between the target acceleration sequence and each of the pre-selected acceleration sequences.

For example, the preselected acceleration sequence is X ═ X₁,x₂,…,x_m]The sample length is m. The target acceleration sequence is Y ═ S₃＝[y₁,y₂,…,y_q]And the sample length is q. The regular path distance D (i, j) is calculated as:

D(i,j)＝Dist(i,j)+min{D(i-1,j),D(i,j-1),D(i-1,j-1)}

wherein Dist (i, j) represents the euclidean distance between the ith acceleration in the X sequence and the jth acceleration in the Y sequence. D (i, j) represents the euclidean distance between the total first i accelerations in the X sequence and the first j accelerations in the Y sequence. And (3) calculating a normalized path distance D (m, q) between the target acceleration sequence and each type of preselected acceleration sequence by taking i as m and j as q, and solving the normalized path distance D (m, q) by adopting the dynamic time normalization algorithm formula.

E4: and determining the label corresponding to the preselected acceleration sequence with the regular path distance meeting the third preset condition as the label of the road surface at the position of the target vehicle.

As an alternative example, the third preset condition is that the regular path distance is minimum. For example, the canonical path distance between the target acceleration sequence and the preselected acceleration sequence 1 is minimal. And if the label corresponding to the preselected acceleration sequence 1 is in a hollow state, determining that the uneven road surface at the target vehicle position is in the hollow state.

Based on E1-E4, the specific type of the road surface unevenness state at the target vehicle position can be accurately determined by sampling the preselected acceleration sequence and the dynamic time warping algorithm.

In addition, based on the above, in a second vehicle vibration situation, in a possible implementation manner, an embodiment of the present application provides a specific implementation manner for identifying an uneven state of a vehicle, including:

f1: acquiring a plurality of pre-selected acceleration sequences; the preselected acceleration sequence corresponds to a label; the label includes a dimpled state or a raised state.

F2: and if the vertical direction acceleration of the vehicle does not meet a first preset condition and the steering wheel corner data of the vehicle meets a second preset condition within the estimated rear wheel vibration time interval, taking the first acceleration sequence as a target acceleration sequence.

It is understood that, in the second vehicle vibration condition in D1-D2, the vertical direction acceleration of the vehicle does not satisfy the first preset condition and the steering wheel angle data of the vehicle satisfies the second preset condition within the estimated rear wheel vibration time interval, indicating that the front wheels of the vehicle are vibrated and are caused by an uneven road surface.

At this time, if only the first acceleration sequence is acquired, the first acceleration sequence is used as the target acceleration sequence.

F3: and respectively calculating the normalized path distance between the target acceleration sequence and each pre-selected acceleration sequence based on a dynamic time normalization algorithm.

F4: and determining the label corresponding to the preselected acceleration sequence with the regular path distance meeting the third preset condition as the label of the road surface at the position of the target vehicle.

It is understood that the technical details of F1 and F3-F4 are similar to those of the above embodiments E1 and E3-E4, and reference is made to the above embodiments, which are not repeated herein.

Referring to fig. 3, fig. 3 is a flowchart of another road surface detection method provided in the embodiment of the present application. As shown in fig. 3, the vertical acceleration and the vehicle position of the vehicle are collected in real time, the vertical acceleration of the vehicle is monitored, and whether the vertical acceleration of the vehicle meets a first preset condition is determined.

And if the acceleration of the vehicle in the vertical direction does not meet the first preset condition, ending the process. If the vertical direction acceleration of the vehicle meets a first preset condition, the vibration moment of the front wheels, the first vertical direction acceleration, the position of the target vehicle and a first acceleration sequence comprising the first vertical direction acceleration are obtained when the first preset condition is met.

And then, judging whether the vertical direction acceleration of the vehicle meets a first preset condition within the estimated rear wheel vibration time interval.

If the acceleration of the vehicle in the vertical direction meets a first preset condition within the estimated rear wheel vibration time interval, acquiring a second acceleration sequence including the second acceleration in the vertical direction and the second acceleration. And calculating correlation coefficients of the first acceleration sequence and the second acceleration sequence. And when the correlation coefficient does not meet the preset range, ending the process. And when the correlation coefficient meets a preset range, acquiring a target acceleration sequence from the first acceleration sequence and the second acceleration sequence. And identifying the depression state or the bulge state of the road surface by adopting a dynamic time warping algorithm based on the target acceleration sequence and the preselected acceleration sequence, and uploading the detection result and the position information to a cloud platform and the like.

If the vertical direction acceleration of the vehicle does not meet the first preset condition within the estimated rear wheel vibration time interval, judging whether the steering wheel rotation angle within the estimated rear wheel vibration time interval meets the second preset condition. And if the steering wheel rotation angle in the estimated rear wheel vibration time interval does not meet the second preset condition, ending the process. And if the steering wheel rotation angle in the estimated rear wheel vibration time interval meets a second preset condition, taking the first acceleration sequence as a target acceleration sequence. And identifying the depression state or the bulge state of the road surface by adopting a dynamic time warping algorithm based on the target acceleration sequence and the preselected acceleration sequence, and uploading the detection result and the position information to a cloud platform and the like.

As can be seen from the above, in the road surface detection method provided in the embodiment of the present application, it is determined whether vehicle vibration is generated due to whether the vehicle passes through an uneven road surface, and on the basis of determining that the vehicle vibration is generated due to whether the vehicle passes through the uneven road surface, it is determined whether the uneven road surface is a hollow road surface or a convex road surface. Moreover, in the process of determining that the vehicle passes through the uneven road surface, the condition that both the front wheels and the rear wheels of the vehicle vibrate or only the front wheels of the vehicle vibrate and the rear wheels of the vehicle avoid the vehicle is considered. The method can overcome detection misjudgment caused by vibration noise of the vehicle body, is suitable for different vehicle parameters, and can identify various scenes such as concave road surfaces and convex road surfaces.

Based on the road surface detection method provided by the above method embodiment, the embodiment of the present application further provides a road surface detection device, which will be described below with reference to the accompanying drawings.

Referring to fig. 4, the figure is a schematic view of a road surface detection device provided in an embodiment of the present application. As shown in fig. 4, the road surface detection device includes:

a first acquisition unit 401, configured to acquire vertical acceleration of a vehicle and a vehicle position in real time;

a first obtaining unit 402, configured to obtain a vibration time of a front wheel, a first vertical acceleration, and a target vehicle position when a vertical acceleration of the vehicle meets a first preset condition;

a second acquisition unit 403 for acquiring a first acceleration sequence including the first vertical-direction acceleration;

a first determining unit 404, configured to determine an estimated rear wheel vibration time interval according to the front wheel vibration time;

a third obtaining unit 405, configured to obtain, when the vertical acceleration of the vehicle meets the first preset condition, a second vertical acceleration that meets the first preset condition within the predicted rear wheel vibration time interval;

a fourth acquiring unit 406 configured to acquire a second acceleration sequence including the second vertical-direction acceleration;

a first calculating unit 407, configured to calculate a degree of correlation between the first acceleration sequence and the second acceleration sequence, and determine that the road surface at the target vehicle position is in an uneven state if the degree of correlation satisfies a preset range.

In one possible implementation, the uneven state includes a dimpled state or a raised state, and the apparatus further includes:

a fifth acquisition unit, configured to acquire multiple pre-selected acceleration sequences; the preselected acceleration sequence corresponds to a label; the label comprises a dimpled state or a raised state;

the first composition unit is used for composing the first acceleration sequence and the second acceleration sequence into a target acceleration sequence if the acceleration of the vehicle in the vertical direction meets the first preset condition within the estimated rear wheel vibration time interval;

the second calculation unit is used for calculating the normalized path distance between the target acceleration sequence and each type of the preselected acceleration sequence respectively based on a dynamic time warping algorithm;

and the second determining unit is used for determining a label corresponding to the pre-selected acceleration sequence with the regular path distance meeting a third preset condition as a label of the road surface at the position of the target vehicle.

In one possible implementation, the apparatus further includes:

the second acquisition unit is used for acquiring steering wheel angle data of the vehicle in real time;

and the third determining unit is used for determining that the road surface at the position of the target vehicle is in an uneven state when the vertical direction acceleration of the vehicle does not meet the first preset condition and the steering wheel angle data of the vehicle meets the second preset condition within the estimated rear wheel vibration time interval.

the sixth acquisition unit is used for acquiring various pre-selected acceleration sequences; the preselected acceleration sequence corresponds to a label; the label comprises a dimpled state or a raised state;

a fourth determining unit, configured to take the first acceleration sequence as a target acceleration sequence if, within the predicted rear wheel vibration time interval, the vertical acceleration of the vehicle does not satisfy the first preset condition and the steering wheel angle data of the vehicle satisfies a second preset condition;

the third calculation unit is used for calculating the normalized path distance between the target acceleration sequence and each type of the preselected acceleration sequence respectively based on a dynamic time warping algorithm;

and the fifth determining unit is used for determining a label corresponding to the pre-selected acceleration sequence with the regular path distance meeting a third preset condition as the label of the road surface at the position of the target vehicle.

In one possible implementation, the apparatus further includes:

and the sixth determining unit is used for determining that the road surface at the position of the target vehicle is in a flat state when the vertical direction acceleration of the vehicle does not meet the first preset condition and the steering wheel angle data of the vehicle does not meet the second preset condition within the estimated rear wheel vibration time interval.

In a possible implementation manner, the second obtaining unit 403 includes:

a first obtaining sub-unit, configured to obtain an adjacent first acceleration sub-sequence before the first vertical acceleration; the length of the adjacent first acceleration subsequence is a first acceleration sampling length;

a second obtaining sub-unit, configured to obtain an adjacent second acceleration sub-sequence after the first vertical acceleration; the adjacent second acceleration subsequence is a second acceleration sampling length;

a first composing subunit for composing the adjacent first acceleration sub-sequence, the first vertical direction acceleration and the adjacent second acceleration sub-sequence into a first acceleration sequence;

the fourth obtaining unit 406 includes:

a third obtaining sub-unit, configured to obtain an adjacent third acceleration sub-sequence before the second vertical acceleration; the length of the adjacent third acceleration subsequence is a third acceleration sampling length;

a fourth acquiring subunit, configured to acquire an adjacent fourth acceleration subsequence after the second vertical acceleration; the adjacent fourth acceleration subsequence is a fourth acceleration sampling length;

a second composing sub-unit for composing the adjacent third acceleration sub-sequence, the second vertical direction acceleration and the adjacent fourth acceleration sub-sequence into a second acceleration sequence.

In a possible implementation manner, the first determining unit 404 includes:

the calculating subunit is used for calculating the interval time period according to the vehicle wheel base and the vehicle speed;

a determination subunit configured to determine, as a target time, a time at which the front wheel shaking time has elapsed the interval period;

a fifth obtaining subunit, configured to obtain an adjacent first estimated rear wheel vibration time subinterval before the target time and an adjacent second estimated rear wheel vibration time subinterval after the target time;

and the third component subunit is used for forming the estimated rear wheel vibration time interval by the adjacent first estimated rear wheel vibration time subinterval, the target time and the adjacent second estimated rear wheel vibration time subinterval.

In addition, this application embodiment still provides a road surface check out test set, includes: the road surface detection device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the computer program, the road surface detection method is realized according to any one of the embodiments.

In addition, a computer-readable storage medium is provided, where instructions are stored, and when the instructions are executed on a terminal device, the terminal device is caused to execute the road surface detection method according to any one of the embodiments.

The embodiment of the application provides a road surface detection device and equipment, and the vertical direction acceleration and the vehicle position of a vehicle are collected in real time. When the vertical direction acceleration of the vehicle meets a first preset condition, the vibration of the front wheels of the vehicle is indicated. The front wheel shaking time, the first vertical direction acceleration, the target vehicle position, and the first acceleration sequence including the first vertical direction acceleration at this time are acquired. And determining the estimated rear wheel vibration time interval according to the front wheel vibration time. And in the estimated rear wheel vibration time interval, when the vertical direction acceleration of the vehicle meets a first preset condition, the rear wheel of the vehicle is shown to be vibrated. The second vertical-direction acceleration at this time and a second acceleration sequence including the second vertical-direction acceleration are acquired. When the vehicle wheel shakes due to the fact that the front wheel and the rear wheel of the vehicle pass through uneven road surfaces at the same position, the correlation degree of the first acceleration sequence and the second acceleration sequence can meet a preset range. Therefore, the degree of correlation of the first acceleration sequence and the second acceleration sequence is calculated. When the degree of correlation satisfies a preset range, it is determined that the vibrations of the front and rear wheels of the vehicle are vibrations caused by passing over an uneven road surface at the same position, which is the road surface at the target vehicle position. The device is suitable for different vehicle parameters, and the detection accuracy of the uneven road surface is high.

It should be noted that, in the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the system or the device disclosed by the embodiment, the description is simple because the system or the device corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.

It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of detecting a road surface, the method comprising:

determining a pre-estimated rear wheel vibration time interval according to the front wheel vibration time;

2. The method of claim 1, wherein the uneven condition comprises a dimpled condition or a bumped condition, the method further comprising:

3. The method of claim 1, further comprising:

collecting steering wheel angle data of a vehicle in real time;

4. The method of claim 3, wherein the uneven condition comprises a dimpled condition or a bumped condition, the method further comprising:

5. The method of claim 3, further comprising:

6. The method of claim 1, wherein said obtaining a first acceleration sequence comprising said first vertical direction acceleration comprises:

7. The method of claim 6 wherein the first acceleration sample length, the second acceleration sample length, the third acceleration sample length, and the fourth acceleration sample length are each determined from a preset rugged road segment length, a vehicle speed, a vehicle acceleration sample rate, and a sample point selection coefficient.

8. The method of claim 1, wherein determining an estimated rear wheel shock time interval based on the front wheel shock time comprises:

determining the moment when the vibration moment of the front wheel passes through the interval time period as a target moment;

and forming the pre-estimated rear wheel vibration time interval by the adjacent first pre-estimated rear wheel vibration time sub-interval, the target time and the adjacent second pre-estimated rear wheel vibration time sub-interval.

9. A road surface detecting device, characterized in that the device comprises:

the first acquisition unit is used for acquiring the vertical direction acceleration and the vehicle position of the vehicle in real time;

the first determining unit is used for determining the estimated vibration time interval of the rear wheel according to the vibration time of the front wheel;

10. A road surface detecting apparatus, characterized by comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the road surface detection method according to any one of claims 1 to 8 when executing the computer program.

11. A computer-readable storage medium having stored therein instructions that, when run on a terminal device, cause the terminal device to execute the road surface detection method according to any one of claims 1 to 8.