CN115556761A

CN115556761A - Vehicle speed prediction method and device

Info

Publication number: CN115556761A
Application number: CN202211222647.XA
Authority: CN
Inventors: 徐康; 孔彩霞; 赵瑞; 张宝成
Original assignee: Hozon New Energy Automobile Co Ltd
Current assignee: Hozon New Energy Automobile Co Ltd
Priority date: 2022-10-08
Filing date: 2022-10-08
Publication date: 2023-01-03
Also published as: WO2024073938A1

Abstract

The application discloses a vehicle speed prediction method and device, and relates to the technical field of vehicles. The method of the present application comprises: determining traffic flow operation information according to vehicle running parameters, wherein the vehicle running parameters at least comprise one of a destination where the vehicle runs and a running route where the vehicle runs, and the traffic flow operation information is used for representing the running states of other vehicles under the vehicle running parameters; acquiring vehicle driving data, and determining a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used for representing the characteristic of vehicle speed change when the vehicle drives; and predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is the predicted value of the vehicle speed of the vehicle in a target time period.

Description

Vehicle speed prediction method and device

Technical Field

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

Background

With the deepening of the energy-saving and environment-friendly concept, new energy vehicles are gradually developed. During the use process of the new energy vehicle, anxiety of a user mainly comes from the mileage, and during the process of calculating the mileage, the driving speed of the vehicle needs to be predicted. That is, once the accuracy of the prediction result of the driving speed is low, the accuracy of the driving range is directly influenced.

At present, in the process of predicting the vehicle speed, the vehicle speed is often predicted based on the running route of the vehicle and corresponding feature matching, that is, after one route is run in the vehicle running process, the running condition of the vehicle is recorded, the road condition feature in the process is determined, when the vehicle runs again, the vehicle speed is predicted based on the road condition feature when the vehicle runs at the moment, and once the route which is run before is matched, the vehicle speed is predicted based on the historical record of the route. However, in practical application, the existing vehicle speed prediction mode depends on data generated when the vehicle runs in the past, and when the vehicle runs to a new route, the accuracy of vehicle speed prediction is affected because the road condition characteristics are difficult to match with proper historical data.

Disclosure of Invention

The embodiment of the application provides a vehicle speed prediction method and device, and mainly aims to solve the problem that the accuracy of vehicle speed prediction on a new route or a new road condition is low due to the fact that the vehicle speed is predicted in the conventional road condition characteristic matching mode depending on historical data.

In order to solve the above technical problem, an embodiment of the present application provides 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 running parameters, wherein the vehicle running parameters at least comprise one of a destination where the vehicle runs and a running route where the vehicle runs, and the traffic flow operation information is used for representing the running states of other vehicles under the vehicle running parameters;

acquiring vehicle running data, and determining a vehicle control style based on the vehicle running data, wherein the vehicle control style is used for representing the characteristic of vehicle speed change when the vehicle runs;

and predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is the predicted value of the vehicle speed of the vehicle in a target time period.

Optionally, the traffic flow operation information includes an average speed, where the average speed is an average value of speeds of other vehicles when the other vehicles travel based on the vehicle travel parameter;

the method for determining traffic flow operation information according to the vehicle running parameters comprises the following steps:

when the vehicle driving parameters comprise the destination, determining the driving route based on the destination and the current position of the vehicle, and acquiring historical driving data of the other vehicles on the driving route according to the driving route;

and calculating an average value based on the historical running data to obtain the average speed.

Optionally, the vehicle control style comprises a vehicle style parameter, and the vehicle style parameter is used for representing the correction of the vehicle speed based on the driving style;

the acquiring vehicle driving data and determining a vehicle control style based on the vehicle driving data comprises the following steps:

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

acquiring 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 for representing a boundary value of the vehicle in a speed change process limited according to design requirements;

determining the vehicle style parameter based on the vehicle speed correction factor and the first speed change limit.

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

determining a second speed change limit of the vehicle according to vehicle data of the vehicle, wherein the vehicle data comprises a speed change process when the vehicle runs, and the second speed change limit is used for representing a boundary value of the vehicle in a speed change process determined based on historical running conditions;

determining the vehicle style parameter based on the vehicle speed correction factor and the second speed change limit.

Optionally, the determining a second speed variation limit of the vehicle according to the vehicle data of the vehicle includes:

acquiring and counting running data of the vehicle running each time to obtain vehicle data;

determining a speed distribution of the vehicle according to the vehicle data, and determining a first speed, a second speed and a third speed in 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 boundary values which are quartered after being sorted according to size in the speed distribution;

calculating a quartile parameter of the velocity profile based on the first velocity, the second velocity, and the third velocity;

calculating an upper limit value and a lower limit value of the speed based on the quartile parameter, the first speed, the second speed, and the third speed, and determining the upper limit value and the lower limit value as the second speed change limit value.

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

and predicting the running speed according to the average speed and the vehicle style parameters.

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

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

if the average vehicle speed exceeds the second time length, acquiring the target time period as the second time length, calculating a vehicle speed correction value based on the vehicle style parameter and the second time length, and determining the running speed based on the vehicle speed correction value and the average vehicle speed;

and if not, determining the average speed as the running speed.

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

calculating driving habits according to the historical data, wherein the driving habits are used for representing the intensity of the vehicle when the speed changes during running;

and determining the vehicle speed correction factor corresponding to the driving habits in a preset style relationship, wherein the preset style relationship is obtained based on the vehicle test, and the preset style relationship comprises at least one driving habit and the vehicle speed correction factor corresponding to each driving habit.

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

a first determination unit, configured to determine traffic operation information according to a vehicle driving parameter, where the vehicle driving parameter includes at least one of a destination where the vehicle drives and a driving route where the vehicle drives, and the traffic operation information is used to represent a driving state of another vehicle under the vehicle driving parameter;

the second determining unit is used for acquiring vehicle running data and determining a vehicle control style based on the vehicle running data, wherein the vehicle control style is used for representing the characteristic of vehicle speed change when the vehicle runs;

and the prediction unit is used for predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is a predicted value of the vehicle speed of the vehicle in a target time period.

Optionally, the traffic flow operation information includes an average speed, where the average speed is an average value of speeds of other vehicles when the other vehicles run based on the vehicle running parameter;

the first determination unit includes:

the determining module is used for determining the driving route based on the destination and the current position of the vehicle when the vehicle driving parameters comprise the destination, and acquiring historical driving data of the other vehicles on the driving route according to the driving route;

and the calculating module is used for calculating an average value based on the historical running data to obtain the average speed.

the second determination unit includes:

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

the acquisition module is used for acquiring a first speed change limit value of the vehicle according to vehicle information of the vehicle, wherein the first speed change limit value is used for representing a boundary value of the vehicle in a speed change process limited according to design requirements;

a first determination module 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:

the second calculation module is 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, where the vehicle data includes a speed change process while the vehicle is traveling, and the second speed change limit is used to represent a boundary value of the vehicle during a gear change process determined based on historical traveling conditions;

a third determination module 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:

the acquisition submodule is used for acquiring the driving data of each driving of the vehicle and counting the driving data to obtain the vehicle data;

the determining submodule is used for determining a speed distribution of the vehicle according to the vehicle data and determining a first speed, a second speed and a third speed in 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 boundary values which are divided into four parts in the speed distribution after being sorted according to the size;

a first calculation submodule for calculating a quartile parameter of the velocity profile based on the first velocity, the second velocity, and the third velocity;

a second calculation submodule configured to calculate an upper limit value and a 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 predicting unit is specifically configured to predict the traveling speed according to the average speed and the vehicle style parameter.

Optionally, the prediction unit includes:

the first determination module is used for acquiring a vehicle speed fluctuation value of the vehicle within a first time length, and determining whether the vehicle speed fluctuation value exceeds a first threshold value, wherein the first time length is a first specific time period before the current time of the vehicle;

the second determination module is used for acquiring the target time period as the second time period if the vehicle speed fluctuation value is determined to exceed the first threshold value, calculating a vehicle speed correction value based on the vehicle style parameter and the second time period, and determining the running speed based on the vehicle speed correction value and the average vehicle speed;

and the third determination module is used for determining the average speed as the running speed if the vehicle speed fluctuation value is determined not to exceed a first threshold value.

Optionally, the second computing module includes:

the calculation submodule is used for calculating driving habits according to the historical data, wherein the driving habits are used for representing the intensity of the vehicle when the speed changes during running;

the determining submodule is used for determining the vehicle speed correction factor corresponding to the driving habits in a preset style relationship, the preset style relationship is obtained based on the vehicle test, and the preset style relationship comprises at least one driving habit 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 including a stored program, wherein a device on which the storage medium is located is controlled to execute the vehicle speed prediction method according to any one of the first aspect when the program is executed.

In a fourth aspect, embodiments of the present application provide a vehicle speed prediction device that includes a storage medium; and one or more processors, the storage medium coupled with the processors, the processors configured to execute program instructions stored in the storage medium; the program instructions when executed perform the vehicle speed prediction method of any one of the first aspect.

By means of the technical scheme, the technical scheme provided by the application at least has the following advantages:

the application provides a vehicle speed prediction method and a vehicle speed prediction device, firstly, traffic flow operation information is determined according to vehicle running parameters, wherein the vehicle running parameters at least comprise one of a destination where the vehicle runs and a running route where the vehicle runs, and the traffic flow operation information is used for representing the running state of other vehicles under the vehicle running parameters; then vehicle running data are obtained, and a vehicle control style is determined based on the vehicle running data, wherein the vehicle control style is used for representing the characteristic of vehicle speed change when the vehicle runs; and finally, predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is the predicted value of the vehicle speed of the vehicle in a target time period, so that the function of predicting the vehicle speed is realized. Compared with the prior art, the method and the device have the advantages that the running speed of the vehicle can be predicted based on the vehicle running information and the vehicle control style, so that the characteristics of the road condition when the vehicle runs do not need to be matched with historical data, and the problem that the accuracy of the predicted speed is influenced because the characteristics of the proper road condition cannot be matched is solved. In addition, in the application, the vehicle operation information is the driving state of other vehicles when the vehicles run, and the vehicle control style is the characteristic of speed change when the vehicles run, so that the driving characteristics of the current vehicle can be considered on the premise that the other vehicles run on a certain route in the process of predicting the vehicle speed, the current vehicle can be predicted by combining the driving conditions of other vehicles when meeting a new route, the prediction result can be ensured to be more consistent with the driving characteristics of the driver of the current vehicle under the condition of considering the driving characteristics of the current vehicle, the prediction result is ensured to approach the actual driving condition, and the predicted vehicle speed is more accurate.

Drawings

The above and other objects, features and advantages of exemplary embodiments of the present application will become readily apparent from the following detailed description read in conjunction with the accompanying drawings. Several embodiments of the present application are illustrated by way of example and not by way of limitation in the figures of the accompanying drawings and in which like reference numerals refer to similar or corresponding parts and in which:

FIG. 1 is a flow chart illustrating a method for predicting vehicle speed provided by an embodiment of the present application;

FIG. 2 is a flow chart illustrating another method for predicting vehicle speed provided by an embodiment of the present application;

FIG. 3 is a block diagram showing the components of a vehicle speed prediction device provided by an embodiment of the present application;

fig. 4 is a block diagram showing another vehicle speed prediction apparatus according to the embodiment of the present application.

Detailed Description

Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which this application belongs.

The embodiment of the application provides a vehicle speed prediction method, which is specifically shown in fig. 1 and comprises the following steps:

101. and determining traffic flow operation information according to the vehicle running parameters.

The vehicle running parameter at least comprises one of a destination where the vehicle runs and a running route where the vehicle runs, and the traffic flow running information is used for representing the running state of other vehicles under the vehicle running parameter.

In this embodiment, the vehicle driving parameter may be understood as parameter information required for determining a route to be traveled by the vehicle, where the vehicle driving parameter may be a destination, and then the vehicle driving parameter may be determined based on the current location and the destination in the process of determining the route, and of course, the vehicle driving parameter may also be directly a certain route set by the user.

Since the driving conditions of other vehicles can be used as a reference during the driving of the vehicle, for example, when the speeds of a large number of vehicles in the driving process of the line 1 are 40km/h to 50km/h, the driving process of the current vehicle on the line 1 generally cannot be far away from 40km/h to 50km/h, for example, the speed of the current vehicle on the line 1 reaches 120km/h obviously less likely.

102. Vehicle travel data is acquired and a vehicle control style is determined based on the vehicle travel data.

The vehicle control style is used for representing the characteristics of the vehicle speed change when the vehicle runs.

After the driving state of the other vehicle under the condition of the vehicle driving parameters is determined in the foregoing steps, although the analysis is referential, the analysis needs to be carried out in combination with the driving specification of the current vehicle. Therefore, in this step, it is necessary to acquire the vehicle driving data and determine the vehicle control style. In the present embodiment, the vehicle control style may be understood as a habit and a style of controlling the vehicle during the driving of the vehicle by the driver, for example, some drivers prefer to accelerate and decelerate suddenly, and some drivers are accustomed to accelerate and decelerate slowly, which results in a characteristic that the speed change of the vehicle is influenced by the habit and the style of the operation of the driver during the driving of the vehicle.

Meanwhile, the vehicle driving data can be recorded data of the current vehicle driving before, and can also be recorded data of the same type or the same type of vehicle driving with the same driver 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 herein, and only the characteristics of the driver when driving the vehicle when the current vehicle is driving can be reflected.

103. And predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style.

Wherein the travel speed is a predicted value of a vehicle speed of the vehicle within a target period.

Since the vehicle control style can embody the characteristic of the speed change of the driver when the driver drives the vehicle, in the process of predicting the running speed, the possible speed change condition of the current vehicle when the vehicle runs on a certain route can be determined by combining the vehicle control style on the basis of the vehicle running information, so that the running speed of the vehicle can be determined.

It should be noted that, the following manners may be included in the process of determining the running speed of the vehicle, but are not limited to: for example, when the traffic flow operation information includes a speed section of the other vehicle during the travel of the route a, and it is determined that the vehicle control style when the driver drives the vehicle belongs to "stationary", the intermediate value of the speed section may be used as the predicted value of the vehicle. Conversely, when it is determined that the vehicle control style belongs to a "race", the maximum value of the speed interval may be determined as the traveling speed of the vehicle.

The embodiment of the application firstly determines traffic flow operation information according to vehicle running parameters, wherein the vehicle running parameters at least comprise one of a destination where the vehicle runs and a running route where the vehicle runs, and the traffic flow operation information is used for representing the running state of other vehicles under the vehicle running parameters; then vehicle driving data are obtained, and a vehicle control style is determined based on the vehicle driving data, wherein the vehicle control style is used for representing the characteristics of vehicle speed change when the vehicle drives; and finally, predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is a predicted value of the vehicle speed of the vehicle in a target time period, so that the function of predicting the vehicle speed is realized. Compared with the prior art, the method and the device have the advantages that the running speed of the vehicle can be predicted based on the vehicle running information and the vehicle control style, so that the characteristics of the road condition when the vehicle runs do not need to be matched with historical data, and the problem that the accuracy of the predicted speed is influenced because the characteristics of the proper road condition cannot be matched is solved. In addition, in the application, the vehicle operation information is the driving state of other vehicles when the vehicles run, and the vehicle control style is the characteristic of speed change when the vehicles run, so that the driving characteristics of the current vehicle can be considered on the premise that the other vehicles run on a certain route in the process of predicting the vehicle speed, the current vehicle can be predicted by combining the driving conditions of other vehicles when meeting a new route, the prediction result can be ensured to be more consistent with the driving characteristics of the driver of the current vehicle under the condition of considering the driving characteristics of the current vehicle, the prediction result is ensured to approach the actual driving condition, and the predicted vehicle speed is more accurate.

For the following description in more detail, an embodiment of the present application provides another access control method, specifically as shown in fig. 2, the method includes:

201. and determining traffic flow operation information according to the vehicle running 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 the other vehicles travel based on the vehicle travel parameter;

based on this, this step may be performed by:

In this step, when the vehicle driving parameter is a destination, it is described that the current user only determines where the target of the vehicle is to be driven, and therefore, it is necessary to determine a driving route based on the actual position of the current vehicle and the destination, and since other vehicles have a reference meaning in driving the route, it is possible in this embodiment to determine the vehicle speeds of the other vehicles driving on the route based on the driving route, and determine the average value based on these vehicle speeds. Of course, in this embodiment, the average value may be an average value of the vehicle speeds of all vehicles in the travel route, or may be further filtered according to the user's needs, for example, the vehicle speed of a vehicle of the same type, even the same brand and model, as the current vehicle is selected, and the average speed is determined according to the selected vehicle speed. Or determining the average speed of the vehicle at the same time on other dates before based on the time when the current vehicle runs the running route. Without limitation, the user may select the content on his or her own basis.

202. Vehicle travel data is acquired and a vehicle control style is determined based on the vehicle travel data.

Specifically, the vehicle control style includes a vehicle style parameter that characterizes a modification of vehicle speed based on a driving style. Since the driving characteristics, driving style and driving habits of different drivers during driving the vehicle are different, the speed change of the vehicle can be corrected differently.

Based on this, the step may comprise, when executed:

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

then, acquiring 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 for representing a boundary value of the vehicle in a speed change process limited according to design requirements;

and finally, determining the vehicle style parameter based on the vehicle speed correction factor and the first speed change limit value.

In this step, the historical data of the vehicle can be understood as data recorded by the vehicle during the driving process on other routes, and the driving characteristics of the driver of the vehicle can be embodied. Therefore, the vehicle speed correction factor, which is a vehicle speed change characteristic in the vehicle speed change process, can be determined based on the historical data.

Meanwhile, no matter how the vehicle is controlled in the driving process, the vehicle cannot be separated from the requirement of the design process of the vehicle, namely, each vehicle has a speed variation extreme value under the requirements of the strength, the safety and the like of the vehicle body, and the vehicle cannot be separated from the control of the extreme value, namely, the first speed variation limit value, no matter how the vehicle is driven, so that the vehicle style parameters can be determined based on the vehicle speed correction factor and the first speed variation limit value in the embodiment.

Specifically, the step may be performed as follows:

wherein, since the speed variation is divided into two types, one is acceleration and one is deceleration, the determination of the vehicle style parameter needs to be divided into two types, i.e. acceleration condition and deceleration condition, where k is shown in the above formula 1 _acc To correspond to a first speed variation limit, k, under accelerated conditions _dec To correspond to a first speed change limit under deceleration conditions,

alpha is a vehicle style parameter, a vehicle speed correction factor.

Further, the determination of the vehicle correction factor may be made based on the driver's habit of driving the vehicle and a preset relationship.

Based on this, the step of obtaining the historical data of the vehicle and calculating the vehicle speed correction factor based on the historical data may comprise:

This step can be performed according to the following formula:

wherein the content of the first and second substances,

as vehicle speed correction factor, epsilon _driver For driving habit, f (epsilon) _driver ) And the representation searches the corresponding driving habit operation in the preset style relationship.

Further, in some cases, although the vehicle is designed to have a speed variation limit, in some driver's operation processes, the speed variation limit does not really reach the speed variation limit, but a set of limit suitable for the driver is provided for driving in terms of safety and driving experience, and the speed variation limit of the vehicle can also be determined based on the actual driving condition of the user.

Based on this, this step may also include when executed:

then, determining a second speed change limit value of the vehicle according to vehicle data of the vehicle, wherein the vehicle data comprises a speed change process when the vehicle runs, and the second speed change limit value is used for representing a boundary value of the vehicle in a speed change process determined based on historical running conditions;

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

In the method in the step, the first speed change limit value in the step is not used for determining the vehicle style parameter, but the second speed change limit value is determined based on the vehicle data, and the condition of the vehicle speed change limit value in the actual driving process of the driver is determined based on the condition of the vehicle in the process, so that the actual driving condition of the driver can be better met, the vehicle style parameter is more accurate, and a foundation is laid for determining the accuracy of the driving speed based on the vehicle style parameter.

Further, in this step, the determining a second speed change limit of the vehicle according to the vehicle data of the vehicle may specifically include, when executed:

In this step, the Quartile rule (referred to as Quartile) is also referred to as a Quartile point, and is a rule that all values are arranged from small to large in statistics and divided into four equal parts, and the values at three division points are determined. The method is mainly applied to box line drawing in statistics. It is an endpoint value where a set of data is sorted to 25%, 50%, 75% locations. The quartile is the division of the entire data into 4 parts by 3 points, where each part contains 25% of the data. Therefore, the first speed, the second speed, and the third speed in this step are end point values at positions of 25%, 50%, and 75% in the corresponding speed profiles. Then, according to the three values, a quartile distance, namely a quartile parameter, can be determined, namely, the difference between the three values is determined, and an upper limit value and a lower limit value are sequentially determined by the quartile parameter, so that a second speed change limit value is obtained.

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

203. And predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style.

Based on the foregoing description, when the vehicle operation information is an average speed, and the vehicle control style is a vehicle style parameter, the driving speed in this step is determined by the average speed and the vehicle control style, and therefore this step may include:

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

and if not, determining the average speed as the running speed.

Specifically, in this embodiment, when it is determined that the vehicle speed fluctuation value of the vehicle in the first time period exceeds the first threshold, it is determined that the vehicle speed fluctuation of the vehicle is large, and it is determined that the vehicle style parameter needs to be used for correction, whereas when it is determined that the vehicle speed fluctuation value of the vehicle in the first time period exceeds the second threshold, it is determined that the vehicle speed fluctuation of the vehicle is small, that is, the influence of the driving habit of the driver on the vehicle speed is small, and then the vehicle speed of another vehicle on the travel route may be directly referred to.

Specifically, the step may be executed as shown in the following formula:

wherein the content of the first and second substances,

in order to be able to predict the speed of travel,

is the current speed of the vehicle,

is the vehicle speed of the vehicle prior to the first time period,

is the average vehicle speed of the other vehicles, alpha is the vehicle style parameter, and beta is the first threshold.

As can be seen from equation 3, when t =1, it is assumed that the current time is the current time, and the predicted traveling speed is equal to the current vehicle speed. When t is more than 1, the predicted vehicle speed after the target time interval is described, and then the two conditions are divided into two conditions, wherein one condition corresponds to the two conditions

Since the vehicle speed fluctuation is small, the average vehicle speed of the other vehicle can be directly determined as the predicted vehicle speed. On the contrary, when

When the vehicle speed fluctuation range is large, the vehicle style parameters are required to be corrected on the basis of the average vehicle speed before the first time.

Further, in some cases, the first threshold may be a vehicle style parameter, that is, a vehicle style based on which the speed fluctuation of the vehicle is determined to be changedThe parameters are defined. That is, β in equation 3 is replaced by α. Of course, in practical applications, in equation 3

And

can also be replaced by

And

that is, the determination may be corrected and determined based on the real-time vehicle speed of the current vehicle without using the average vehicle speed of the other vehicles. Specifically, the selection may be performed based on the actual needs of the user, and is not limited herein.

In order to achieve the above object, according to another aspect of the present application, an embodiment of the present application further provides a storage medium including a stored program, wherein when the program runs, a device on which the storage medium is located is controlled to execute the vehicle speed prediction method.

In order to achieve the above object, according to another aspect of the present application, an embodiment of the present application further provides a vehicle speed prediction apparatus, which includes a storage medium; and one or more processors, the storage medium coupled with the processors, the processors configured to execute program instructions stored in the storage medium; the program instructions, when executed, implement the vehicle speed prediction method described above.

Further, as an implementation of the method shown in fig. 1 and fig. 2, another embodiment of the present application further provides a vehicle speed prediction device. The embodiment of the vehicle speed prediction apparatus corresponds to the foregoing method embodiment, and details in the foregoing method embodiment are not repeated in the embodiment of the vehicle speed prediction apparatus for convenience of reading, but it should be clear that the system in this embodiment can correspondingly implement all the contents in the foregoing method embodiment. As shown in fig. 3 in detail, the vehicle speed prediction device includes:

a first determining unit 31, configured to determine traffic operation information according to a vehicle driving parameter, where the vehicle driving parameter includes at least one of a destination where the vehicle drives and a driving route where the vehicle drives, and the traffic operation information may be used to characterize driving states of other vehicles under the vehicle driving parameter;

a second determining unit 32, configured to obtain vehicle driving data, and determine a vehicle control style based on the vehicle driving data, where the vehicle control style may be used to characterize a vehicle speed change while the vehicle is driving;

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

Further, as shown in fig. 4, 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 travel parameter;

the first determination unit 31 includes:

a determining module 311, configured to determine the driving route based on the destination and the current location of the vehicle when the vehicle driving parameter includes the destination, and obtain historical driving data of the other vehicle on the driving route according to the driving route;

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

Further, as shown in FIG. 4, the vehicle control style includes vehicle style parameters that may be used to characterize a modification to vehicle speed based on driving style;

the second determining unit 32 includes:

a first calculating module 321, configured to obtain historical data of the vehicle, and calculate a vehicle speed correction factor based on the historical data;

an obtaining module 322, configured to obtain a first speed change limit of the vehicle according to vehicle information of the vehicle, where the first speed change limit may be used to represent a boundary value of the vehicle during a gear shifting process limited according to a design requirement;

a 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 fig. 4, the second determining unit 32 includes:

a second calculating module 324, which may be configured to obtain historical data of the vehicle and calculate a vehicle speed correction factor based on the historical data;

a second determination module 325, configured to determine a second speed variation limit of the vehicle according to vehicle data of the vehicle, where the vehicle data includes a speed variation process while the vehicle is running, and the second speed variation limit may be used to characterize a boundary value during a gear shift process determined by the vehicle based on historical running conditions;

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

Further, as shown in fig. 4, the second determining module 325 includes:

the obtaining submodule 3251 may be configured to obtain driving data of each driving of the vehicle, and perform statistics to obtain the vehicle data;

a determining sub-module 3252, 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 among a plurality of speeds in the speed distribution according to a quartile rule, where the first speed, the second speed, and the third speed are three boundary values of a fourth quarter in the speed distribution;

a first calculation submodule 3253 operable to calculate a quartile parameter of the velocity profile based on the first velocity, the second velocity, and the third velocity;

a second calculating submodule 3254 may be configured to calculate an upper limit value and a 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 variation limit value.

Further, as shown in fig. 4, the prediction unit 33 may be specifically configured to predict the traveling speed according to the average speed and the vehicle style parameter.

Further, as shown in fig. 4, the prediction unit 33 includes:

the first determining module 331 may be configured to obtain a vehicle speed fluctuation value of the vehicle within a first time period, and determine whether the vehicle speed fluctuation value exceeds a first threshold, where the first time period is a first specific time period before the current time of the vehicle;

a second determining module 332, configured to, if it is determined that the vehicle speed fluctuation value exceeds a first threshold, obtain the target time period as the second time period, calculate a vehicle speed correction value based on the vehicle style parameter and the second time period, and determine the running speed based on the vehicle speed correction value and the average vehicle speed;

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

Further, as shown in fig. 4, the second calculating module 324 includes:

a calculating submodule 3241, configured to calculate driving habits according to the historical data, where the driving habits may be used to represent the intensity of the vehicle when the speed changes during driving;

the determining submodule 3242 may be configured to determine the vehicle speed correction factor corresponding to the driving habit in a preset style relationship, where the preset style relationship is obtained based on the vehicle test, and the preset style relationship includes at least one driving habit and the vehicle speed correction factor corresponding to each driving habit.

The embodiment of the application provides a vehicle speed prediction method and a vehicle speed prediction device, firstly, traffic flow operation information is determined according to vehicle running parameters, wherein the vehicle running parameters at least comprise one of a destination where the vehicle runs and a running route where the vehicle runs, and the traffic flow operation information is used for representing the running state of other vehicles under the vehicle running parameters; then vehicle driving data are obtained, and a vehicle control style is determined based on the vehicle driving data, wherein the vehicle control style is used for representing the characteristics of vehicle speed change when the vehicle drives; and finally, predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is the predicted value of the vehicle speed of the vehicle in a target time period, so that the function of predicting the vehicle speed is realized. Compared with the prior art, the method and the device have the advantages that the running speed of the vehicle can be predicted based on the vehicle running information and the vehicle control style, so that the characteristics of the road condition when the vehicle runs do not need to be matched with historical data, and the problem that the accuracy of the predicted speed is influenced because the characteristics of the proper road condition cannot be matched is solved. In addition, in the application, the vehicle operation information is the driving state of other vehicles when the vehicles run, and the vehicle control style is the characteristic of speed change when the vehicles run, so that the driving characteristics of the current vehicle can be considered on the premise that the other vehicles run on a certain route in the process of predicting the vehicle speed, the current vehicle can be predicted by combining the driving conditions of other vehicles when meeting a new route, the prediction result can be ensured to be more consistent with the driving characteristics of the driver of the current vehicle under the condition of considering the driving characteristics of the current vehicle, the prediction result is ensured to approach the actual driving condition, and the predicted vehicle speed is more accurate. The storage medium may include volatile memory in a computer readable medium, random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.

The embodiment of the application also provides a vehicle speed prediction device, which comprises a storage medium; and one or more processors, the storage medium coupled with the processors, the processors configured to execute program instructions stored in the storage medium; the program instructions, when executed, implement the vehicle speed prediction method described above.

The embodiment of the application provides equipment, the equipment comprises a processor, a memory and a program which is stored on the memory and can run on the processor, and the following steps are realized when the processor executes the program: determining traffic flow operation information according to vehicle running parameters, wherein the vehicle running parameters at least comprise one of a destination where the vehicle runs and a running route where the vehicle runs, and the traffic flow operation information is used for representing the running states of other vehicles under the vehicle running parameters; acquiring vehicle driving data, and determining a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used for representing the characteristic of vehicle speed change when the vehicle drives; and predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is the predicted value of the vehicle speed of the vehicle in a target time period.

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

Further, the vehicle control style comprises a vehicle style parameter, and the vehicle style parameter is used for representing the correction of the vehicle speed based on the driving style;

the acquiring vehicle driving data and determining a vehicle control style based on the vehicle driving data comprises:

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

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

calculating upper and lower limit values of the speed based on the quartile parameter, the first speed, the second speed, and the third speed, and determining the upper and lower limit values as the second speed change limit value.

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

Further, the predicting the travel speed according to the average speed and the vehicle style parameter comprises:

and if not, determining the average speed as the running speed.

Further, the obtaining historical data of the vehicle and calculating a vehicle speed correction factor based on the historical data includes:

calculating driving habits according to the historical data, wherein the driving habits are used for representing the intensity of the vehicle when the speed changes during driving;

The present application further provides a computer program product adapted to perform program code for initializing the following method steps when executed on a data processing device: determining traffic flow operation information according to vehicle running parameters, wherein the vehicle running parameters at least comprise one of a destination where the vehicle runs and a running route where the vehicle runs, and the traffic flow operation information is used for representing the running states of other vehicles under the vehicle running parameters; acquiring vehicle driving data, and determining a vehicle control style based on the vehicle driving data, wherein the vehicle control style is used for representing the characteristic of vehicle speed change when the vehicle drives; and predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is a predicted value of the vehicle speed of the vehicle in a target time period.

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

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

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

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

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

The memory may include forms of volatile 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). The memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, 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 disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that 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 a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.

The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A vehicle speed prediction method, characterized by comprising:

and predicting the running speed of the vehicle based on the traffic flow operation information and the vehicle control style, wherein the running speed is a predicted value of the vehicle speed of the vehicle in a target time period.

2. The method according to claim 1, wherein the traffic flow operation information includes an average speed, wherein the average speed is an average of speeds of other vehicles when traveling based on the vehicle travel parameter;

3. The method of claim 2, wherein the vehicle control style comprises a vehicle style parameter characterizing a driving style based modification to vehicle speed;

4. The method of claim 2, wherein the obtaining vehicle travel data and determining a vehicle control style based on the vehicle travel data comprises:

5. The method of claim 4, wherein determining a second speed change limit for the vehicle based on vehicle data for the vehicle comprises:

6. The method according to any one of claims 3-5, wherein predicting the travel speed of the vehicle based on the traffic flow operation information and the vehicle control style comprises:

7. The method of claim 6, wherein the predicting the travel speed from the average speed and the vehicle style parameter comprises:

and if not, determining the average speed as the running speed.

8. The method of claim 3, wherein said obtaining historical data of the vehicle and calculating a vehicle speed correction factor based on the historical data comprises:

9. A vehicle speed prediction apparatus, characterized by comprising:

10. The apparatus according to claim 9, wherein the traffic flow operation information includes an average speed, wherein the average speed is an average of speeds of other vehicles when traveling based on the vehicle travel parameter;

the first determination unit includes:

11. The apparatus of claim 10, wherein the vehicle control style comprises a vehicle style parameter characterizing a modification to vehicle speed based on driving style;

the second determination unit includes:

12. The apparatus of claim 10, wherein the second determining unit comprises:

and the third determining module is used for determining the vehicle style parameter based on the vehicle speed correction factor and the second speed change limit value.

13. The apparatus of claim 12, wherein the second determining module comprises:

14. The arrangement according to any of claims 11-13, characterized in that the prediction unit, in particular, is adapted to predict the travel speed based on the average speed and the vehicle style parameter.

15. The apparatus of claim 14, wherein the prediction unit comprises:

and the third determination module is used for determining the average speed as the running speed if the vehicle speed fluctuation value is determined not to exceed the first threshold value.

16. The apparatus of claim 11, wherein the second computing module comprises:

17. A storage medium characterized by comprising a stored program, wherein a device in which the storage medium is located is controlled to execute a vehicle speed prediction method according to any one of claims 1 to 8 when the program is executed.

18. A vehicle speed prediction apparatus, characterized in that the apparatus includes a storage medium; and one or more processors, the storage medium coupled with the processors, the processors configured to execute program instructions stored in the storage medium; the program instructions when executed perform a vehicle speed prediction method as defined in any one of claims 1 to 8.