WO2024073938A1

WO2024073938A1 - Vehicle speed prediction method and device

Info

Publication number: WO2024073938A1
Application number: PCT/CN2022/137901
Authority: WO
Inventors: 徐康; 孔彩霞; 赵瑞; 张宝成
Original assignee: 合众新能源汽车股份有限公司
Priority date: 2022-10-08
Filing date: 2022-12-09
Publication date: 2024-04-11
Also published as: CN115556761A

Abstract

A vehicle speed prediction method, comprising: determining traffic flow information according to vehicle traveling parameters (101), wherein the vehicle traveling parameters at least comprise one of a vehicle traveling destination and a vehicle traveling route, and the traffic flow information is used for representing the traveling state of other vehicles under the vehicle traveling parameters; acquiring vehicle traveling data, and determining a vehicle control style on the basis of the vehicle traveling data (102), wherein the vehicle control style is used for representing the characteristics of a vehicle speed change when the vehicle is traveling; and predicting the traveling speed of the vehicle on the basis of the traffic flow information and the vehicle control style (103), the traveling speed being a predicted value of the vehicle speed within a target time period. Further disclosed is a vehicle speed prediction device. The vehicle speed prediction method and the vehicle speed prediction device can improve the accuracy of vehicle speed prediction.

Description

Vehicle speed prediction method and device

Technical Field

The present application relates to the field of vehicle technology, and in particular to a vehicle speed prediction method and device.

Background technique

As energy conservation and environmental protection concepts deepen, new energy vehicles are gradually emerging. In the process of using new energy vehicles, users' anxiety mainly comes from the cruising range. In the process of calculating the cruising range, the vehicle's driving speed needs to be predicted. In other words, if the accuracy of the predicted driving speed is low, it will directly affect the accuracy of the cruising range.

At present, in the process of predicting vehicle speed, it is often based on the route the vehicle has traveled and the corresponding feature matching. That is to say, after the vehicle travels a route, the vehicle's driving situation will be recorded and the road condition characteristics of this process will be determined. When the vehicle travels again, it will be matched based on the road condition characteristics of the vehicle at this time. Once it matches the route that has been traveled before, the vehicle speed will be predicted based on the historical records of the route. However, in actual applications, the existing vehicle speed prediction method relies on the data generated by the vehicle's past travel. When the vehicle travels to a new route, it will be difficult to match the appropriate historical data due to the road condition characteristics, which affects the accuracy of the vehicle speed prediction.

Summary of the invention

The embodiments of the present application provide a vehicle speed prediction method and device, the main purpose of which is to solve the problem that the existing method of relying on historical data to match road condition characteristics to predict vehicle speed leads to low accuracy of vehicle speed prediction on new routes or new road conditions.

In order to solve the above technical problems, the embodiments of the present application provide the following technical solutions:

In a first aspect, the present application provides a vehicle speed prediction method, the method comprising:

Determining traffic flow operation information according to vehicle driving parameters, wherein the vehicle driving parameters include at least one of a destination of the vehicle and a driving route of the vehicle, and the traffic flow operation information is used to characterize the driving status of other vehicles under the vehicle driving parameters;

Acquiring vehicle driving data, and determining a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize the characteristics of a speed change of the vehicle when the vehicle is driving;

Based on the traffic flow operation information and the vehicle control style, a driving speed of the vehicle is predicted, where the driving speed is a predicted value of the vehicle speed within a target time period.

Optionally, the traffic flow operation information includes an average speed, wherein the average speed is an average value of speeds of other vehicles when traveling based on the vehicle driving parameters;

The determining of the traffic flow operation information according to the vehicle driving parameters includes:

When the vehicle driving parameters include the destination, the driving route is determined based on the destination and the current position of the vehicle, and the historical driving data of the other vehicles on the driving route are obtained according to the driving route;

An average value is calculated based on the historical driving data to obtain the average speed.

Optionally, the vehicle control style includes a vehicle style parameter, and the vehicle style parameter is used to characterize the correction of the vehicle speed based on the driving style;

The acquiring of vehicle driving data and determining the vehicle control style based on the vehicle driving data includes:

Acquiring historical data of the vehicle, and calculating a vehicle speed correction factor based on the historical data;

Acquire a first speed change limit value of the vehicle according to the vehicle information of the vehicle, wherein the first speed change limit value is used to characterize a boundary value of the vehicle in a speed change process limited according to design requirements;

The vehicle style parameter is determined based on the vehicle speed correction factor and the first speed change limit.

Optionally, the acquiring vehicle driving data and determining the vehicle control style based on the vehicle driving data includes:

Determining a second speed change limit value of the vehicle according to vehicle data of the vehicle, wherein the vehicle data includes a speed change process of the vehicle when the vehicle is traveling, and the second speed change limit value is used to characterize a boundary value of the vehicle in a speed change process determined based on historical driving conditions;

The vehicle style parameter is determined based on the vehicle speed correction factor and the second speed change limit.

Optionally, determining the second speed change limit value of the vehicle according to the vehicle data of the vehicle includes:

Acquire and count the driving data of the vehicle each time it travels, and obtain the vehicle data;

Determine a speed distribution of the vehicle according to the vehicle data, and determine a first speed, a second speed, and a third speed from a plurality of speeds in the speed distribution according to a quartile rule, wherein the first speed, the second speed, and the third speed are three dividing values of the speed distribution divided into four equal parts after being sorted by size;

calculating an quartile parameter of the speed distribution based on the first speed, the second speed, and the third speed;

An upper limit value and a lower limit value of the speed are calculated based on the quartile parameter, the first speed, the second speed, and the third speed, and the upper limit value and the lower limit value are determined as the second speed change limit value.

Optionally, predicting the driving speed of the vehicle based on the traffic flow operation information and the vehicle control style includes:

The driving speed is predicted based on the average speed and the vehicle style parameter.

Optionally, predicting the driving speed according to the average speed and the vehicle style parameter includes:

Obtaining a speed fluctuation value of the vehicle within a first time period, and determining whether the speed fluctuation value exceeds a first threshold, wherein the first time period is a first specific time period of the vehicle before a current moment;

If it exceeds, obtaining the target time period as the second time period, calculating a vehicle speed correction value based on the vehicle style parameter and the second time period, and determining the driving speed based on the vehicle speed correction value and the average vehicle speed;

If not, the average speed is determined as the driving speed.

Optionally, the acquiring historical data of the vehicle and calculating the vehicle speed correction factor based on the historical data includes:

Calculating driving habits based on the historical data, wherein the driving habits are used to characterize the severity of the speed change of the vehicle while driving;

In a preset style relationship, the vehicle speed correction factor corresponding to the driving habit is determined, the preset style relationship is obtained based on the vehicle test, and the preset style relationship includes at least one of the driving habits and the vehicle speed correction factor corresponding to each of the driving habits.

In a second aspect, the present application further provides a vehicle speed prediction device, comprising:

a first determining unit, configured to determine traffic flow operation information according to vehicle driving parameters, wherein the vehicle driving parameters include at least one of a destination of the vehicle and a driving route of the vehicle, and the traffic flow operation information is used to characterize the driving status of other vehicles under the vehicle driving parameters;

a second determination unit, configured to obtain vehicle driving data, and determine a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize a feature of a speed change of the vehicle when the vehicle is driving;

A prediction unit is used to predict the driving speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the driving speed is a predicted value of the vehicle speed within a target time period.

The first determining unit includes:

a determination module, configured to determine the driving route based on the destination and the current position of the vehicle when the vehicle driving parameters include the destination, and to obtain historical driving data of the other vehicles on the driving route according to the driving route;

A calculation module is used to calculate an average value based on the historical driving data to obtain the average speed.

The second determining unit includes:

A first calculation module, used for acquiring historical data of the vehicle and calculating a vehicle speed correction factor based on the historical data;

An acquisition module, configured to acquire a first speed change limit value of the vehicle according to the vehicle information of the vehicle, wherein the first speed change limit value is used to represent a boundary value of the vehicle in a speed change process limited according to design requirements;

The first determination module is configured to determine the vehicle style parameter based on the vehicle speed correction factor and the first speed change limit.

Optionally, the second determining unit includes:

A second calculation module, used for acquiring historical data of the vehicle and calculating a vehicle speed correction factor based on the historical data;

a second determination module, configured to determine a second speed change limit of the vehicle according to vehicle data of the vehicle, wherein the vehicle data includes a speed change process of the vehicle when the vehicle is traveling, and the second speed change limit is used to characterize a boundary value of the vehicle in a speed change process determined based on a historical driving condition;

The third determination module is configured to determine the vehicle style parameter based on the vehicle speed correction factor and the second speed change limit.

Optionally, the second determining module includes:

An acquisition submodule is used to acquire and count the driving data of the vehicle each time it travels, so as to obtain the vehicle data;

a determination submodule, configured to determine a speed distribution of the vehicle according to the vehicle data, and determine a first speed, a second speed, and a third speed from a plurality of speeds in the speed distribution according to a quartile rule, wherein the first speed, the second speed, and the third speed are three dividing values of the speed distribution divided into four equal parts after being sorted by size;

A first calculation submodule, configured to calculate a quartile parameter of the speed distribution based on the first speed, the second speed, and the third speed;

The second calculation submodule is used to calculate the upper limit value and the lower limit value of the speed based on the quartile parameter, the first speed, the second speed and the third speed, and determine the upper limit value and the lower limit value as the second speed change limit value.

Optionally, the prediction unit is specifically used to predict the driving speed based on the average speed and the vehicle style parameters.

Optionally, the prediction unit includes:

A first determination module is used to obtain a speed fluctuation value of the vehicle within a first time period and determine whether the speed fluctuation value exceeds a first threshold value, wherein the first time period is a first specific time period of the vehicle before a current moment;

a second determination module, configured to obtain the target period as the second duration if it is determined that the vehicle speed fluctuation value exceeds a first threshold, calculate a vehicle speed correction value based on the vehicle style parameter and the second duration, and determine the driving speed based on the vehicle speed correction value and the average vehicle speed;

The third determination module is configured to determine the average speed as the driving speed if it is determined that the vehicle speed fluctuation value does not exceed a first threshold value.

Optionally, the second computing module includes:

A calculation submodule, used for calculating driving habits according to the historical data, wherein the driving habits are used to characterize the severity of the speed change of the vehicle while driving;

A determination submodule is used to determine the vehicle speed correction factor corresponding to the driving habit in a preset style relationship, wherein the preset style relationship is obtained based on the vehicle test, and the preset style relationship includes at least one of the driving habits and the vehicle speed correction factor corresponding to each driving habit.

In a third aspect, an embodiment of the present application provides a storage medium, wherein the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the vehicle speed prediction method described in any one of the first aspects.

In a fourth aspect, an embodiment of the present application provides a vehicle speed prediction device, which includes a storage medium; and one or more processors, wherein the storage medium is coupled to the processor, and the processor is configured to execute program instructions stored in the storage medium; when the program instructions are executed, the vehicle speed prediction method described in any one of the first aspects is executed.

By means of the above technical solution, the technical solution provided by this application has at least the following advantages:

The present application provides a vehicle speed prediction method and device. The present application first determines the traffic flow operation information according to the vehicle driving parameters, wherein the vehicle driving parameters include at least one of the destination of the vehicle and the driving route of the vehicle, and the traffic flow operation information is used to characterize the driving state of other vehicles under the vehicle driving parameters; then obtains the vehicle driving data, and determines the vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize the characteristics of the vehicle speed change when the vehicle is driving; finally, based on the traffic flow operation information and the vehicle control style, predicts the driving speed of the vehicle, and the driving speed is the predicted value of the vehicle speed of the vehicle within the target time period, thereby realizing the vehicle speed prediction function. Compared with the prior art, the present application can predict the driving speed of the vehicle based on the vehicle operation information and the vehicle control style, which does not need to match the characteristics of the road conditions when the vehicle is driving with the historical data, and thus avoids the problem of affecting the accuracy of the predicted vehicle speed due to the inability to match the appropriate road condition characteristics. Furthermore, in the present application, the vehicle operation information is the driving status of other vehicles while the vehicle is driving, and the vehicle control style is the characteristic of the speed change while the vehicle is driving. Therefore, in the process of predicting the vehicle speed, it is possible to consider the situation of other vehicles driving on a certain route while also taking into account the driving characteristics of the current vehicle, thereby ensuring that when the current vehicle encounters a new route, it can also make predictions based on the driving conditions of other vehicles, and while taking into account the driving characteristics of the current vehicle, it can ensure that the prediction results are more in line with the driving characteristics of the current vehicle driver, thereby ensuring that the prediction results are closer to the actual driving conditions, making the predicted vehicle speed more accurate.

BRIEF DESCRIPTION OF THE DRAWINGS

By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present application will become easy to understand. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

FIG1 shows a flow chart of a vehicle speed prediction method provided by an embodiment of the present application;

FIG2 shows a flow chart of another vehicle speed prediction method provided by an embodiment of the present application;

FIG3 shows a block diagram of a vehicle speed prediction device provided in an embodiment of the present application;

FIG4 shows a block diagram of another vehicle speed prediction device provided in an embodiment of the present application.

Detailed ways

The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by technicians in the field to which this application belongs.

The present application provides a vehicle speed prediction method, as shown in FIG1 , which includes:

101. Determine traffic flow operation information based on vehicle driving parameters.

The vehicle driving parameters include at least one of the destination of the vehicle and the driving route of the vehicle, and the traffic flow operation information is used to characterize the driving status of other vehicles under the vehicle driving parameters.

In this embodiment, the vehicle driving parameters can be understood as parameter information required to determine the route that the vehicle is about to travel. Among them, when the vehicle driving parameters can be the destination, then in the process of determining the route, it can be determined based on the current location and the destination. Of course, the vehicle driving parameters can also be directly a route set by the user.

During the driving process of a vehicle, the driving conditions of other vehicles can be used as a reference. For example, when a large number of vehicles are driving at a speed of 40km/h to 50km/h on Line 1, the driving speed of the current vehicle on Line 1 generally cannot differ much from 40km/h to 50km/h. For example, it is obviously unlikely that the current vehicle will reach a speed of 120km/h on Line 1.

102. Acquire vehicle driving data, and determine a vehicle control style based on the vehicle driving data.

The vehicle control style is used to characterize the characteristics of the vehicle speed change when the vehicle is traveling.

After determining the driving status of other vehicles under the vehicle driving parameters in the above steps, although it is of reference, it is still necessary to analyze it in combination with the driving characteristics of the current vehicle. Therefore, in this step, it is necessary to obtain the vehicle driving data and determine the vehicle control style. In this embodiment, the vehicle control style can be understood as a habit and style of the driver's vehicle control during the process of driving the vehicle. For example, some drivers like to accelerate and decelerate suddenly, while some drivers are used to slow acceleration and deceleration. This leads to the characteristics of the vehicle speed change affected by the driver's control habits and style during the driving process.

Meanwhile, the vehicle driving data may be the previous recorded data of the current vehicle driving, or the recorded data of the same driver driving the same model or the same type of vehicle as the current vehicle. Of course, the type of the vehicle driving data may be selected based on the needs of the user, and is not limited here, as long as it can reflect the characteristics of the driver driving the vehicle when the current vehicle is driving.

103. Predict a driving speed of the vehicle based on the traffic flow information and the vehicle control style.

The driving speed is a predicted value of the vehicle speed within the target time period.

Since the vehicle control style can reflect the characteristics of the speed change when the driver is driving the vehicle, in the process of predicting the driving speed, the possible speed change of the current vehicle when driving on a certain route can be determined based on the vehicle operation information and the vehicle control style, so the vehicle's driving speed can be determined.

It should be noted that the process of determining the driving speed of a vehicle may include but is not limited to the following methods: for example, when the traffic flow operation information includes the speed interval of other vehicles in the process of driving on route A, and it is determined that the vehicle control style of the driver when driving the vehicle is "smooth", then the middle value of the speed interval can be used as the predicted value of the vehicle. Conversely, when it is determined that the vehicle control style is "racing", then the maximum value of the speed interval can be determined as the driving speed of the vehicle.

This embodiment provides a vehicle speed prediction method. The embodiment of the present application first determines the traffic flow operation information according to the vehicle driving parameters, wherein the vehicle driving parameters include at least one of the destination of the vehicle and the driving route of the vehicle, and the traffic flow operation information is used to characterize the driving state of other vehicles under the vehicle driving parameters; then obtains the vehicle driving data, and determines the vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize the characteristics of the speed change when the vehicle is driving; finally, based on the traffic flow operation information and the vehicle control style, predicts the driving speed of the vehicle, and the driving speed is the predicted value of the vehicle speed of the vehicle within the target time period, thereby realizing the vehicle speed prediction function. Compared with the prior art, the present application can predict the driving speed of the vehicle based on the vehicle operation information and the vehicle control style, which does not need to match the characteristics of the road conditions when the vehicle is driving with the historical data, and avoids the problem of affecting the accuracy of the predicted vehicle speed due to the inability to match the appropriate road condition characteristics. Furthermore, in the present application, the vehicle operation information is the driving status of other vehicles while the vehicle is driving, and the vehicle control style is the characteristic of the speed change of the vehicle while driving. Therefore, in the process of predicting the vehicle speed, it is possible to consider the situation of other vehicles driving on a certain route while also taking into account the driving characteristics of the current vehicle, thereby ensuring that when the current vehicle encounters a new route, it can also be predicted in combination with the driving conditions of other vehicles, and while taking into account the driving characteristics of the current vehicle, it can ensure that the prediction result is more in line with the driving characteristics of the current vehicle driver, thereby ensuring that the prediction result is closer to the actual driving condition, making the predicted vehicle speed more accurate.

To illustrate in more detail below, the present application embodiment provides another access control method, as shown in FIG2 , the method includes:

201. Determine traffic flow operation information according to vehicle driving parameters.

Specifically, the traffic flow operation information includes an average speed, wherein the average speed is an average value of speeds of other vehicles when traveling based on the vehicle driving parameters;

Based on this, this step may include:

In this step, when the vehicle driving parameter is the destination, it means that the current user has only determined the destination of the vehicle, so it is necessary to determine the driving route based on the actual position of the current vehicle and the destination. Since other vehicles have reference significance in the process of driving on this route, in this embodiment, the speed of other vehicles driving on this route can be determined based on the driving route, and the average value can be determined based on these speeds. Of course, in this embodiment, the average value can be the average value of the speeds of all vehicles in the driving route, and it can also be further screened according to the needs of the user, such as selecting the speed of vehicles of the same type or even the same brand and model as the current vehicle, and determining the average speed based on this. Or based on the time when the current vehicle is driving on the driving route, determine the average speed of vehicles at the same time on other dates before. There is no limitation here, and the user can choose according to his needs.

202. Acquire vehicle driving data, and determine a vehicle control style based on the vehicle driving data.

Specifically, the vehicle control style includes a vehicle style parameter, and the vehicle style parameter is used to characterize the correction of the vehicle speed based on the driving style. Since different drivers have different control characteristics, driving styles, and driving habits during the driving process, the correction of the vehicle speed change will also be different.

Based on this, this step may include:

First, historical data of the vehicle is obtained, and a vehicle speed correction factor is calculated based on the historical data;

Then, according to the vehicle information of the vehicle, a first speed change limit value of the vehicle is obtained, where the first speed change limit value is used to characterize a boundary value of the vehicle in a speed change process limited according to design requirements;

Finally, the vehicle style parameter is determined based on the vehicle speed correction factor and the first speed change limit.

In this step, the historical data of the vehicle can be understood as the data recorded during the vehicle's previous driving process on other routes, which can reflect the driving characteristics of the driver of the vehicle. Therefore, the vehicle's change characteristics during the vehicle's speed change process, that is, the vehicle speed correction factor, can be determined based on the historical data.

At the same time, no matter how the vehicle is controlled during driving, it will not deviate from the requirements of the vehicle's design process, that is to say, each vehicle will have a speed change extreme value based on the vehicle's body strength, safety and other requirements, and no matter how the vehicle is driven, it will not deviate from the control of this extreme value, that is, the first speed change limit. Therefore, in this embodiment, the vehicle style parameters can be determined based on the vehicle speed correction factor and the first speed change limit.

Specifically, during the execution of this step, the following steps may be performed:

Among them, since there are two types of speed changes, one is acceleration and the other is deceleration, the determination of vehicle style parameters needs to be divided into two, namely, acceleration conditions and deceleration conditions. In the above formula 1, k _acc is the first speed change limit value under the acceleration condition, and k _dec is the first speed change limit value under the deceleration condition.

is the vehicle speed correction factor, and α is the vehicle style parameter.

Furthermore, in the process of determining the vehicle correction factor, it can be determined based on the driver's driving habits and a preset relationship.

Based on this, in this step, the historical data of the vehicle is obtained, and the vehicle speed correction factor is calculated based on the historical data. When executed, the following steps may be included:

This step can be performed according to the following formula:

in,

is the speed correction factor, ε _driver is the driving habit, and f(ε _driver ) represents the operation of searching for the corresponding driving habit in the preset style relationship.

Furthermore, in some cases, although the speed change limit of the vehicle is specified during design, the limit is not actually reached during operation by some drivers. Instead, the driver drives with a set of limits suitable for himself from the perspective of safety and driving experience. The speed change limit of the vehicle can also be determined based on the actual driving conditions of the user.

Based on this, this step may also include:

Then, determining a second speed change limit value of the vehicle according to vehicle data of the vehicle, wherein the vehicle data includes a speed change process of the vehicle when the vehicle is traveling, and the second speed change limit value is used to characterize a boundary value of the speed change process of the vehicle determined based on historical driving conditions;

Finally, the vehicle style parameter is determined based on the vehicle speed correction factor and the second speed change limit.

In the above method in this step, the first speed change limit in the previous step is no longer used to determine the vehicle style parameters, but the second speed change limit is determined based on the vehicle data. This process is actually based on the situation when the vehicle is driving, and the speed change limit of the driver's actual driving process is determined. Therefore, it can be more in line with the driver's actual driving situation, thereby ensuring that the vehicle style parameters are more accurate and laying the foundation for the accuracy of determining the driving speed based on the vehicle style parameters.

Furthermore, the step of determining the second speed change limit of the vehicle according to the vehicle data of the vehicle may specifically include:

Calculate an quartile parameter of the speed distribution based on the first speed, the second speed, and the third speed;

In this step, the quartile rule (Quartile, called quartile) is also called quartile point, which refers to the rule of arranging all values from small to large and dividing them into four equal parts in statistics to determine the values at the three split point positions. It is mostly used in box plotting in statistics. It is the endpoint value at 25%, 50%, and 75% after a group of data is sorted. The quartile is to divide all the data into 4 parts by 3 points, each of which contains 25% of the data. Therefore, the first speed, the second speed, and the third speed in this step are divided into endpoint values at 25%, 50%, and 75% positions in the corresponding speed distribution. Then, based on these three values, the interquartile range, that is, the quartile parameter, can be determined, that is, the gap between the three values is determined, and the upper limit and the lower limit are determined by the quartile parameter in turn, thereby obtaining the second speed change limit.

Specifically, the above process can be: for example, when the first speed is Q1, the second speed is Q2, and the third speed is Q3, and based on the quartile data rule, Q1 is determined as the lower quartile and Q3 is the upper quartile, then the quartile parameter S can be Q3-Q1, and then the upper limit value can be determined to be Q3+1.5S, and the lower limit value can be Q1-1.5S.

203. Predict a driving speed of the vehicle based on the traffic flow information and the vehicle control style.

Based on the description of the above steps, it can be seen that when the vehicle operation information is specifically an average speed, and the vehicle control style is specifically a vehicle style parameter, the driving speed in this step is determined by the above two. Therefore, this step may include:

Furthermore, in this step, predicting the driving speed according to the average speed and the vehicle style parameter includes:

If not, the average speed is determined as the driving speed.

Specifically, in this embodiment, when it is determined that the speed fluctuation value of the vehicle in the first time period exceeds the first threshold value, it means that the speed fluctuation of the vehicle is large, so it is necessary to use the vehicle style parameters for correction; conversely, when it is determined that the speed fluctuation value of the vehicle in the first time period exceeds the second threshold value, it means that the speed fluctuation of the vehicle is small, that is to say, the driver's driving habits have little effect on the vehicle speed, so the speed of other vehicles on the driving route can be directly referred to.

Specifically, this step can be performed as shown in the following formula:

in,

is the predicted driving speed,

is the current speed of the vehicle,

is the speed of the vehicle before the first duration,

is the average speed of other vehicles, α is the vehicle style parameter, and β is the first threshold.

In the above formula 3, it can be seen that when t=1, it means the current time, then the predicted driving speed is equal to the current vehicle speed. When t＞1, it means the predicted speed is the vehicle speed after the target period, then there are two cases, corresponding to the above two cases, one of which is

This indicates that the speed fluctuation is small, so the average speed of other vehicles can be directly determined as the predicted speed.

When , it means that the vehicle speed fluctuates greatly, then it is necessary to use the vehicle style parameters to make corrections based on the average vehicle speed before the first period of time.

Furthermore, in some cases, the first threshold value may also be a vehicle style parameter, that is, the determination of the speed fluctuation of the vehicle is based on the vehicle style parameter. That is, β in Formula 3 is replaced by α. Of course, in practical applications,

and

You can also replace them with

and

That is to say, the average speed of other vehicles may no longer be used to determine the speed, but the real-time speed of the current vehicle may be used for correction and determination. Specifically, the selection may be made based on the actual needs of the user, and no limitation is made here.

In order to achieve the above-mentioned purpose, according to another aspect of the present application, an embodiment of the present application further provides a storage medium, wherein the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the above-mentioned vehicle speed prediction method.

In order to achieve the above-mentioned purpose, according to another aspect of the present application, an embodiment of the present application also provides a vehicle speed prediction device, which includes a storage medium; and one or more processors, the storage medium is coupled to the processor, and the processor is configured to execute program instructions stored in the storage medium; when the program instructions are executed, the above-mentioned vehicle speed prediction method is executed.

Furthermore, as an implementation of the method shown in FIG. 1 and FIG. 2 , another embodiment of the present application also provides a vehicle speed prediction device. The vehicle speed prediction device embodiment corresponds to the aforementioned method embodiment. For ease of reading, the vehicle speed prediction device embodiment will no longer repeat the details of the aforementioned method embodiment one by one, but it should be clear that the system in this embodiment can correspond to all the contents of the aforementioned method embodiment. Specifically, as shown in FIG. 3 , the vehicle speed prediction device includes:

The first determining unit 31 may be used to determine traffic flow operation information according to vehicle driving parameters, wherein the vehicle driving parameters include at least one of a destination of the vehicle and a driving route of the vehicle, and the traffic flow operation information may be used to characterize the driving status of other vehicles under the vehicle driving parameters;

The second determination unit 32 may be used to obtain vehicle driving data and determine a vehicle control style based on the vehicle driving data, wherein the vehicle control style may be used to characterize the characteristics of a speed change of the vehicle when the vehicle is driving;

The prediction unit 33 may be used to predict the driving speed of the vehicle based on the traffic flow operation information and the vehicle control style, where the driving speed is a predicted value of the vehicle speed within a target time period.

Further, as shown in FIG4 , the traffic flow operation information includes an average speed, wherein the average speed is an average value of the speeds of other vehicles when traveling based on the vehicle driving parameters;

The first determining unit 31 includes:

The determination module 311 may be configured to determine the driving route based on the destination and the current position of the vehicle when the vehicle driving parameters include the destination, and to obtain historical driving data of other vehicles on the driving route according to the driving route;

The calculation module 312 may be configured to calculate an average value based on the historical driving data to obtain the average speed.

Further, as shown in FIG4 , the vehicle control style includes a vehicle style parameter, and the vehicle style parameter can be used to characterize the correction of the vehicle speed based on the driving style;

The second determining unit 32 includes:

A first calculation module 321 may be used to obtain historical data of the vehicle and calculate a vehicle speed correction factor based on the historical data;

The acquisition module 322 may be used to acquire a first speed change limit value of the vehicle according to the vehicle information of the vehicle, wherein the first speed change limit value may be used to characterize a boundary value of the vehicle in a speed change process limited according to design requirements;

The first determination module 323 may be configured to determine the vehicle style parameter based on the vehicle speed correction factor and the first speed change limit.

Further, as shown in FIG4 , the second determining unit 32 includes:

A second calculation module 324 may be used to obtain historical data of the vehicle and calculate a vehicle speed correction factor based on the historical data;

A second determination module 325 may be used to determine a second speed change limit of the vehicle according to vehicle data of the vehicle, wherein the vehicle data includes a speed change process of the vehicle when the vehicle is traveling, and the second speed change limit may be used to characterize a boundary value of a speed change process of the vehicle determined based on a historical driving condition;

The third determination module 326 may be configured to determine the vehicle style parameter based on the vehicle speed correction factor and the second speed change limit.

Further, as shown in FIG4 , the second determination module 325 includes:

The acquisition submodule 3251 may be used to acquire and count the driving data of the vehicle each time it travels, thereby obtaining the vehicle data;

The determination submodule 3252 may be used to determine a speed distribution of the vehicle according to the vehicle data, and determine a first speed, a second speed, and a third speed from a plurality of speeds in the speed distribution according to a quartile rule, wherein the first speed, the second speed, and the third speed are three dividing values of the speed distribution divided into four equal parts after being sorted by size;

A first calculation submodule 3253 may be used to calculate a quartile parameter of the speed distribution based on the first speed, the second speed, and the third speed;

The second calculation submodule 3254 can be used to calculate the upper limit value and the lower limit value of the speed based on the quartile parameter, the first speed, the second speed and the third speed, and determine the upper limit value and the lower limit value as the second speed change limit value.

Furthermore, as shown in FIG. 4 , the prediction unit 33 may be specifically configured to predict the driving speed according to the average speed and the vehicle style parameter.

Further, as shown in FIG4 , the prediction unit 33 includes:

The first determination module 331 may be used to obtain a speed fluctuation value of the vehicle within a first time period and determine whether the speed fluctuation value exceeds a first threshold value, wherein the first time period is a first specific time period of the vehicle before a current moment;

The second determination module 332 may be configured to obtain the target period as the second duration if it is determined that the vehicle speed fluctuation value exceeds a first threshold, calculate a vehicle speed correction value based on the vehicle style parameter and the second duration, and determine the driving speed based on the vehicle speed correction value and the average vehicle speed;

The third determination module 333 may be configured to determine the average speed as the driving speed if it is determined that the vehicle speed fluctuation value does not exceed a first threshold.

Further, as shown in FIG4 , the second calculation module 324 includes:

The calculation submodule 3241 may be used to calculate the driving habit according to the historical data, wherein the driving habit may be used to characterize the severity of the speed change of the vehicle while driving;

The determination submodule 3242 can be used to determine the vehicle speed correction factor corresponding to the driving habit in a preset style relationship, wherein the preset style relationship is obtained based on the vehicle test, and the preset style relationship includes at least one of the driving habits and the vehicle speed correction factor corresponding to each of the driving habits.

The embodiment of the present application provides a vehicle speed prediction method and device. The embodiment of the present application first determines the traffic flow operation information according to the vehicle driving parameters, wherein the vehicle driving parameters include at least one of the destination of the vehicle and the driving route of the vehicle, and the traffic flow operation information is used to characterize the driving state of other vehicles under the vehicle driving parameters; then obtains the vehicle driving data, and determines the vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize the characteristics of the speed change when the vehicle is driving; finally, based on the traffic flow operation information and the vehicle control style, predicts the driving speed of the vehicle, and the driving speed is the predicted value of the vehicle speed of the vehicle within the target time period, thereby realizing the vehicle speed prediction function. Compared with the prior art, the present application can predict the driving speed of the vehicle based on the vehicle operation information and the vehicle control style, which does not need to match the characteristics of the road conditions when the vehicle is driving with the historical data, and avoids the problem of affecting the accuracy of the predicted vehicle speed due to the inability to match the appropriate road condition characteristics. Moreover, in the present application, the vehicle operation information is the driving state of other vehicles when the vehicle is driving, and the vehicle control style is the characteristics of the speed change of the vehicle when driving. Therefore, in the process of predicting the vehicle speed, it is possible to consider the situation of other vehicles driving a certain route while taking into account the driving characteristics of the current vehicle, thereby ensuring that the current vehicle can also be predicted in combination with the driving conditions of other vehicles when encountering a new route, and taking into account the driving characteristics of the current vehicle, it can ensure that the prediction result is more in line with the driving characteristics of the current vehicle driver, thereby ensuring that the prediction result is closer to the actual driving situation and making the predicted speed more accurate. The storage medium may include non-permanent memory in a computer-readable medium, random access memory (RAM) and/or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one storage chip.

An embodiment of the present application also provides a vehicle speed prediction device, which includes a storage medium; and one or more processors, wherein the storage medium is coupled to the processor, and the processor is configured to execute program instructions stored in the storage medium; when the program instructions are executed, the above-mentioned vehicle speed prediction method is executed.

An embodiment of the present application provides a device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: determining traffic flow operation information based on vehicle driving parameters, wherein the vehicle driving parameters include at least one of a destination of the vehicle and a driving route of the vehicle, and the traffic flow operation information is used to characterize the driving status of other vehicles under the vehicle driving parameters; acquiring vehicle driving data, and determining a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize the characteristics of the speed change of the vehicle when it is driving; based on the traffic flow operation information and the vehicle control style, predicting the driving speed of the vehicle, and the driving speed is a predicted value of the vehicle speed of the vehicle within a target time period.

Further, the traffic flow operation information includes an average speed, wherein the average speed is an average value of the speeds of other vehicles when traveling based on the vehicle driving parameters;

Further, the vehicle control style includes a vehicle style parameter, and the vehicle style parameter is used to characterize the correction of the vehicle speed based on the driving style;

Furthermore, the acquiring of vehicle driving data and determining the vehicle control style based on the vehicle driving data includes:

Further, determining the second speed change limit value of the vehicle according to the vehicle data of the vehicle includes:

Furthermore, the predicting the driving speed of the vehicle based on the traffic flow operation information and the vehicle control style includes:

Further, predicting the driving speed according to the average speed and the vehicle style parameter includes:

If not, the average speed is determined as the driving speed.

Furthermore, the acquiring of historical data of the vehicle and calculating the vehicle speed correction factor based on the historical data includes:

The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program code that initializes the following method steps: determining traffic flow operation information based on vehicle driving parameters, wherein the vehicle driving parameters include at least one of the destination of the vehicle and the driving route of the vehicle, and the traffic flow operation information is used to characterize the driving status of other vehicles under the vehicle driving parameters; obtaining vehicle driving data, and determining a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize the characteristics of the vehicle speed change when the vehicle is driving; based on the traffic flow operation information and the vehicle control style, predicting the driving speed of the vehicle, the driving speed being the predicted value of the vehicle speed within a target time period.

Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

The present application is described with reference to the flowchart and/or block diagram of the method, device (system), and computer program product according to the embodiment of the present application. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of the process and/or box in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one process or multiple processes in the flowchart and/or one box or multiple boxes in the block diagram.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

In a typical configuration, a computing device includes one or more processors (CPU), input/output interfaces, network interfaces, and memory.

Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and/or non-volatile memory in the form of read-only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined in this article, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

A vehicle speed prediction method, characterized in that the method comprises:

Determining traffic flow operation information according to vehicle driving parameters, wherein the vehicle driving parameters include at least one of a destination of the vehicle and a driving route of the vehicle, and the traffic flow operation information is used to characterize the driving status of other vehicles under the vehicle driving parameters;

Acquiring vehicle driving data, and determining a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize the characteristics of a speed change of the vehicle when the vehicle is driving;

Based on the traffic flow operation information and the vehicle control style, a driving speed of the vehicle is predicted, where the driving speed is a predicted value of the vehicle speed within a target time period.
The method according to claim 1, characterized in that the traffic flow operation information includes an average speed, wherein the average speed is an average value of the speeds of other vehicles when traveling based on the vehicle driving parameters;

The determining of the traffic flow operation information according to the vehicle driving parameters includes:

When the vehicle driving parameters include the destination, the driving route is determined based on the destination and the current position of the vehicle, and the historical driving data of the other vehicles on the driving route are obtained according to the driving route;

An average value is calculated based on the historical driving data to obtain the average speed.
The method according to claim 2, characterized in that the vehicle control style includes a vehicle style parameter, and the vehicle style parameter is used to characterize the correction of the vehicle speed based on the driving style;

The acquiring of vehicle driving data and determining the vehicle control style based on the vehicle driving data includes:

Acquiring historical data of the vehicle, and calculating a vehicle speed correction factor based on the historical data;

Acquire a first speed change limit value of the vehicle according to the vehicle information of the vehicle, wherein the first speed change limit value is used to represent a boundary value of the vehicle in a speed change process limited according to design requirements;

The vehicle style parameter is determined based on the vehicle speed correction factor and the first speed change limit.
The method according to claim 2, characterized in that the acquiring of vehicle driving data and determining the vehicle control style based on the vehicle driving data comprises:

Acquiring historical data of the vehicle, and calculating a vehicle speed correction factor based on the historical data;

Determining a second speed change limit value of the vehicle according to vehicle data of the vehicle, wherein the vehicle data includes a speed change process of the vehicle when the vehicle is traveling, and the second speed change limit value is used to characterize a boundary value of the vehicle in a speed change process determined based on historical driving conditions;

The vehicle style parameter is determined based on the vehicle speed correction factor and the second speed change limit.
The method according to claim 4, characterized in that the determining the second speed change limit value of the vehicle according to the vehicle data of the vehicle comprises:

Acquire and count the driving data of the vehicle each time it travels, and obtain the vehicle data;

Determine a speed distribution of the vehicle according to the vehicle data, and determine a first speed, a second speed, and a third speed from a plurality of speeds in the speed distribution according to a quartile rule, wherein the first speed, the second speed, and the third speed are three dividing values of the speed distribution divided into four equal parts after being sorted by size;

calculating an quartile parameter of the speed distribution based on the first speed, the second speed, and the third speed;

An upper limit value and a lower limit value of the speed are calculated based on the quartile parameter, the first speed, the second speed, and the third speed, and the upper limit value and the lower limit value are determined as the second speed change limit value.
The method according to any one of claims 3 to 5, characterized in that predicting the vehicle's travel speed based on the traffic flow information and the vehicle control style comprises:

The driving speed is predicted based on the average speed and the vehicle style parameter.
The method according to claim 6, characterized in that the predicting the driving speed according to the average speed and the vehicle style parameter comprises:

Obtaining a speed fluctuation value of the vehicle within a first time period, and determining whether the speed fluctuation value exceeds a first threshold, wherein the first time period is a first specific time period of the vehicle before a current moment;

If it exceeds, obtaining the target time period as the second time period, calculating a vehicle speed correction value based on the vehicle style parameter and the second time period, and determining the driving speed based on the vehicle speed correction value and the average vehicle speed;

If not, the average speed is determined as the driving speed.
The method according to claim 3, characterized in that the acquiring of historical data of the vehicle and calculating the vehicle speed correction factor based on the historical data comprises:

Calculating driving habits based on the historical data, wherein the driving habits are used to characterize the severity of the speed change of the vehicle while driving;

In a preset style relationship, the vehicle speed correction factor corresponding to the driving habit is determined, the preset style relationship is obtained based on the vehicle test, and the preset style relationship includes at least one of the driving habits and the vehicle speed correction factor corresponding to each of the driving habits.
A vehicle speed prediction device, characterized in that the device comprises:

a first determining unit, configured to determine traffic flow operation information according to vehicle driving parameters, wherein the vehicle driving parameters include at least one of a destination of the vehicle and a driving route of the vehicle, and the traffic flow operation information is used to characterize the driving status of other vehicles under the vehicle driving parameters;

a second determination unit, configured to obtain vehicle driving data, and determine a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used to characterize a feature of a speed change of the vehicle when the vehicle is driving;

A prediction unit is used to predict the driving speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the driving speed is a predicted value of the vehicle speed within a target time period.
The device according to claim 9, characterized in that the traffic flow operation information includes an average speed, wherein the average speed is an average of the speeds of other vehicles when traveling based on the vehicle driving parameters;

The first determining unit includes:

a determination module, configured to determine the driving route based on the destination and the current position of the vehicle when the vehicle driving parameters include the destination, and to obtain historical driving data of the other vehicles on the driving route according to the driving route;

A calculation module is used to calculate an average value based on the historical driving data to obtain the average speed.
The device according to claim 10, characterized in that the vehicle control style includes a vehicle style parameter, and the vehicle style parameter is used to characterize the correction of the vehicle speed based on the driving style;

The second determining unit includes:

A first calculation module, used for acquiring historical data of the vehicle and calculating a vehicle speed correction factor based on the historical data;

An acquisition module, configured to acquire a first speed change limit value of the vehicle according to the vehicle information of the vehicle, wherein the first speed change limit value is used to represent a boundary value of the vehicle in a speed change process limited according to design requirements;

The first determination module is configured to determine the vehicle style parameter based on the vehicle speed correction factor and the first speed change limit.
The device according to claim 10, wherein the second determining unit comprises:

A second calculation module, used for acquiring historical data of the vehicle and calculating a vehicle speed correction factor based on the historical data;

a second determination module, configured to determine a second speed change limit of the vehicle according to vehicle data of the vehicle, wherein the vehicle data includes a speed change process of the vehicle when the vehicle is traveling, and the second speed change limit is used to characterize a boundary value of the vehicle in a speed change process determined based on a historical driving condition;

The third determination module is configured to determine the vehicle style parameter based on the vehicle speed correction factor and the second speed change limit.
The device according to claim 12, wherein the second determining module comprises:

An acquisition submodule is used to acquire and count the driving data of the vehicle each time it travels, so as to obtain the vehicle data;

a determination submodule, configured to determine a speed distribution of the vehicle according to the vehicle data, and determine a first speed, a second speed, and a third speed from a plurality of speeds in the speed distribution according to a quartile rule, wherein the first speed, the second speed, and the third speed are three dividing values of the speed distribution divided into four equal parts after being sorted by size;

A first calculation submodule, configured to calculate a quartile parameter of the speed distribution based on the first speed, the second speed, and the third speed;

The second calculation submodule is used to calculate the upper limit value and the lower limit value of the speed based on the quartile parameter, the first speed, the second speed and the third speed, and determine the upper limit value and the lower limit value as the second speed change limit value.
The device according to any one of claims 11-13 is characterized in that the prediction unit is specifically used to predict the driving speed based on the average speed and the vehicle style parameter.
The device according to claim 14, characterized in that the prediction unit comprises:

A first determination module is used to obtain a speed fluctuation value of the vehicle within a first time period and determine whether the speed fluctuation value exceeds a first threshold value, wherein the first time period is a first specific time period of the vehicle before a current moment;

a second determination module, configured to obtain the target period as the second duration if it is determined that the vehicle speed fluctuation value exceeds a first threshold, calculate a vehicle speed correction value based on the vehicle style parameter and the second duration, and determine the driving speed based on the vehicle speed correction value and the average vehicle speed;

The third determination module is configured to determine the average speed as the driving speed if it is determined that the vehicle speed fluctuation value does not exceed a first threshold value.
The device according to claim 11, characterized in that the second calculation module comprises:

A calculation submodule, used for calculating driving habits according to the historical data, wherein the driving habits are used to characterize the severity of the speed change of the vehicle while driving;

A determination submodule is used to determine the vehicle speed correction factor corresponding to the driving habit in a preset style relationship, wherein the preset style relationship is obtained based on the vehicle test, and the preset style relationship includes at least one of the driving habits and the vehicle speed correction factor corresponding to each driving habit.
A storage medium, characterized in that the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the vehicle speed prediction method described in any one of claims 1 to 8.
A vehicle speed prediction device, characterized in that the device includes a storage medium; and one or more processors, the storage medium is coupled to the processor, and the processor is configured to execute program instructions stored in the storage medium; when the program instructions are executed, the vehicle speed prediction method described in any one of claims 1 to 8 is executed.