CN113673756B

CN113673756B - Method and device for determining recommended speed of vehicle and computer equipment

Info

Publication number: CN113673756B
Application number: CN202110934885.2A
Authority: CN
Inventors: 石正发; 郭平; 李振雷; 王皓; 陆帅; 施井才; 王丙新; 张健; 王明剑
Original assignee: FAW Jiefang Automotive Co Ltd
Current assignee: FAW Jiefang Automotive Co Ltd
Priority date: 2021-08-16
Filing date: 2021-08-16
Publication date: 2024-06-07
Anticipated expiration: 2041-08-16
Also published as: CN113673756A

Abstract

The application relates to a recommended vehicle speed determining method, a recommended vehicle speed determining device, computer equipment and a storage medium. The method comprises the following steps: according to the vehicle related information and the route related information of the user vehicle, carrying out matching recommendation on the user vehicle based on an economic vehicle speed model, and determining the average recommended vehicle speed of each running road section of the user vehicle on a preset running route; acquiring real-time position information of a user vehicle in the running process of the user vehicle, and acquiring running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment based on the real-time position information; and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the average recommended speed of the user vehicle and the running characteristic information of the rest vehicles, and recommending the real-time recommended speed. The method can remarkably reduce fuel waste, and is energy-saving and environment-friendly.

Description

Method and device for determining recommended speed of vehicle and computer equipment

Technical Field

The application relates to the technical field of internet of vehicles, in particular to a method and a device for determining recommended speed of a vehicle, computer equipment and a storage medium.

Background

The fuel consumption of heavy commercial vehicles is statistically more than 30% of its full life cycle cost, and therefore fuel economy is one of the key properties of heavy commercial vehicles. Meanwhile, the fuel oil emission of the heavy commercial vehicle can cause air pollution in cities, and along with the gradual enhancement of environmental awareness, how to reduce the fuel oil emission also becomes a discussion hot spot.

Therefore, a method is needed to ensure that the fuel consumption of the heavy commercial vehicle is reduced as much as possible under the condition of meeting the task aging, and the fuel waste is avoided, so that the aims of economy, energy conservation and environmental protection are achieved.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a recommended vehicle speed determination method, apparatus, computer device, and storage medium for a vehicle that can save energy and reduce oil for the vehicle running speed.

A recommended vehicle speed determination method of a vehicle, the method comprising:

According to the vehicle related information and the route related information of the user vehicle, carrying out matching recommendation on the user vehicle based on an economic vehicle speed model, and determining the average recommended vehicle speed of each running road section of the user vehicle on a preset running route; the vehicle-related information includes at least one of vehicle configuration information and vehicle load information; the route related information at least comprises one of operation route information and operation aging information;

acquiring real-time position information of a user vehicle in the running process of the user vehicle, and acquiring running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment based on the real-time position information; the operation characteristic information at least comprises one of vehicle speed information and gear information;

And determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the average recommended speed of the user vehicle and the running characteristic information of the rest vehicles, and recommending the real-time recommended speed.

In one embodiment, the determining, according to the vehicle related information and the route related information of the user vehicle, the average recommended vehicle speed of each running road section of the user vehicle on the preset running route based on the matching recommendation of the user vehicle by using the economic vehicle speed model includes:

determining a plurality of vehicle speed ranges matched with each running road section on a preset running route of the user vehicle by using an economic vehicle speed model according to the route related information of the user vehicle and the type of the user vehicle;

and determining the average recommended speed of each running road section of the user vehicle on a preset running route based on the speed range according to the vehicle related information of the user vehicle.

In one embodiment, the step of establishing the economic vehicle speed model includes:

Acquiring historical driving information of a plurality of types of vehicles on a plurality of running routes; the history driving information at least comprises one of driving road information, vehicle load information and fuel consumption information; the operation road information at least comprises one of longitude and latitude information, altitude information and heading information;

segmenting each running route to obtain a plurality of running road sections corresponding to each running route;

Acquiring the historical fuel consumption of vehicles belonging to the same type on each running road section, screening a plurality of candidate vehicles with the fuel consumption smaller than a threshold value, and acquiring the historical running characteristic information of the plurality of candidate vehicles on the corresponding road section; wherein the type of vehicle at least comprises one of a tractor, a truck and a special vehicle;

And classifying and storing the historical driving information and the historical driving characteristic information of each driving road section according to the type of the vehicle, and establishing an economic vehicle speed model.

In one embodiment, the determining, according to the average speed of the user vehicle and the operation feature information of the rest vehicles, the real-time recommended speed of the corresponding operation road section of the user vehicle at the current moment includes:

determining a vehicle speed threshold value of a corresponding running road section at the current moment according to the running characteristic information of the rest vehicles;

and comparing the average recommended speed of the user vehicle with the speed threshold value, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment based on the comparison result.

In one embodiment, the comparing the average recommended speed of the user vehicle with the speed threshold value, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment based on the comparison result includes:

if the average recommended speed of the user vehicle is smaller than the speed threshold, determining the average recommended speed as the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment;

and if the average recommended speed of the user vehicle is greater than the speed threshold, taking the speed threshold as the maximum value of the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the maximum value.

In one embodiment, the determining, according to the average recommended speed of the user vehicle and the operation feature information of the rest vehicles, the real-time recommended speed of the corresponding operation road section of the user vehicle at the current moment and recommending the real-time recommended speed includes:

Acquiring road characteristic information on a corresponding running road section based on the real-time position information of the user vehicle; the road characteristic information at least comprises one of road gradient information, speed limit information and road curvature information;

And determining the real-time recommended speed of the user vehicle at each moment of the corresponding running road section based on a real-time speed analysis model according to the average speed of the user vehicle, the running characteristic information of the rest vehicles and the road characteristic information on the corresponding running road section, and recommending.

In one embodiment, the method further comprises:

Controlling a vehicle controller of the user vehicle to adjust the speed of the user vehicle to the real-time recommended speed; and/or the number of the groups of groups,

And prompting by utilizing a prompting device on the user vehicle so as to guide the user to adjust the speed of the user vehicle to the real-time recommended speed.

A recommended vehicle speed determination device of a vehicle, the device comprising:

The matching module is used for carrying out matching recommendation on the user vehicle based on the economic vehicle speed model according to the vehicle related information and the route related information of the user vehicle, and determining the average recommended vehicle speed of each running road section of the user vehicle on a preset running route; the vehicle-related information includes at least one of vehicle configuration information and vehicle load information; the route related information at least comprises one of operation route information and operation aging information;

The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring real-time position information of a user vehicle in the running process of the user vehicle and acquiring running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment based on the real-time position information; the operation characteristic information at least comprises one of vehicle speed information and gear information;

and the processing module is used for determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the average recommended speed of the user vehicle and the running characteristic information of the rest vehicles and recommending the real-time recommended speed.

A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:

A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

The recommended speed determining method, the recommended speed determining device, the computer equipment and the storage medium of the vehicle are used for carrying out matching recommendation by utilizing a pre-established economic speed model through the vehicle related information and the route related information of the user vehicle, and determining the average recommended speed of each running road section of the user vehicle on a preset running route; therefore, the running vehicle speed with lower oil consumption, energy conservation and emission reduction can be recommended to the user under the condition of meeting the running requirement of the user, and the fuel waste caused by bad driving habits is improved. Meanwhile, in the running process of the user vehicle, the real-time position information of the user vehicle is obtained, the running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment is obtained based on the real-time position information, the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment is determined and recommended based on the average recommended speed and the running characteristic information of the other vehicles, the dynamic information of the current road can be analyzed through real-time Internet of vehicles data, the running speed of the vehicle is corrected dynamically in real time, and the fuel consumption under the actual running working condition is greatly reduced; under various complex external environments, the method not only meets the operation requirement, but also ensures that the actual use oil consumption is the lowest, and is more energy-saving, environment-friendly and economical.

Drawings

FIG. 1 is an application environment diagram of a method for determining a recommended speed of a vehicle in one embodiment;

FIG. 2 is a flow chart of a method of determining a recommended speed of a vehicle in one embodiment;

FIG. 3 is a flow chart of the steps for establishing an economic vehicle speed model in one embodiment;

FIG. 4 is a flowchart illustrating steps for matching recommendations for the user vehicle based on an economic vehicle speed model in one embodiment;

FIG. 5 is a flowchart illustrating steps for determining and recommending real-time recommended speeds of the user vehicle corresponding to the road segments at the current moment in one embodiment;

FIG. 6 is a flowchart illustrating a step of determining a real-time recommended speed of the user vehicle at a current time for a corresponding road segment;

FIG. 7 is a logical frame diagram of a method of determining a recommended speed of a vehicle in one embodiment;

FIG. 8 is a block diagram showing a configuration of a recommended speed determining device of a vehicle in one embodiment;

fig. 9 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

Heavy commercial vehicles are commonly used for long distance transportation, delivery, and other tasks. Compared with vehicles (such as cars) running in short distance in a common city, the fuel consumption of the heavy commercial vehicle is more prominent, the phenomenon of fuel waste is more severe, and the air pollution is more serious. And the actual fuel consumption difference caused by improper driving of the driver can reach more than 30% when the same vehicle executes the same long-distance transportation task according to statistics.

In view of the above, the present application provides a method for determining a recommended speed of a vehicle, thereby solving the problem of large fuel consumption of a heavy commercial vehicle.

The method for determining the recommended speed of the vehicle can be applied to an application environment shown in fig. 1. The vehicle is connected to a cloud server 120 (also called a cloud platform, a cloud end, etc.) through a vehicle-mounted terminal 110 through a network, and performs data transmission. The vehicle-mounted terminal 110 refers to an intelligent terminal installed on a vehicle, and in some embodiments, the vehicle-mounted terminal 110 may also be a portable terminal of a user bound to the vehicle, such as a smart phone, a tablet computer, a smart watch, and other portable wearable electronic devices. Cloud server 120 may be implemented as a stand-alone server or as a cluster of servers.

The recommended vehicle speed determination method of the vehicle provided by the application can be executed by an on-board terminal installed in the vehicle or by a cloud server according to the equipment/hardware configuration condition of the vehicle. For example, in some embodiments, if the device/hardware configuration condition of the vehicle is insufficient to process the internet of vehicles data or the data processing speed is insufficient, the cloud server may perform steps such as acquiring and processing the internet of vehicles data, and transmit the processing result to the vehicle-mounted terminal, or the portable terminal of the user; accordingly, the in-vehicle terminal may perform only a partial data/information acquisition operation and a partial data/information transmission operation. In some embodiments, if the device/hardware configuration of the vehicle is better, the storage space is enough, and the vehicle-mounted terminal may also execute the recommended vehicle speed determining method of the vehicle.

In one embodiment, as shown in fig. 2, a recommended vehicle speed determining method of a vehicle is provided, and an example in which the method is applied to the cloud server in fig. 1 is described. The method comprises the following steps:

step S202, matching recommendation is carried out on the user vehicle based on the economic vehicle speed model according to the vehicle related information and the route related information of the user vehicle, and the average recommended vehicle speed of each running road section of the user vehicle on a preset running route is determined.

Wherein the vehicle-related information includes at least one of vehicle configuration information and vehicle load information. The vehicle configuration information includes, but is not limited to, configuration information such as a vehicle identification number (Vehicle Identification Number, VIN) engine model, tire model, transmission model, and rear axle final drive ratio. The vehicle load information includes rated load information and actual load information of the vehicle. The rated load information of the vehicle can be obtained through configuration information when the vehicle leaves the factory. The actual load information of the vehicle can be collected through a sensor of the vehicle and uploaded to the cloud server through the vehicle-mounted terminal.

The route related information includes at least one of operation route information and operation timeliness information. The travel route information refers to a route along which the vehicle travels, and may be determined based on a departure position and a destination position provided by the user. For example, the operation route information includes a highway route from beijing to the upper ocean. Illustratively, the user inputs departure place and destination information through the vehicle-mounted terminal, and the cloud server uploads and acquires the information through the vehicle-mounted terminal, so that the running route information is determined. The operation timeliness information refers to time limit requirements which need to be met by the running, such as the duration of the whole journey. For example, for cargo transportation, the operational aging information may indicate that the transportation needs to reach the destination/complete delivery within X days or X hours.

Specifically, the cloud server carries out matching recommendation on the user vehicle based on the economic vehicle speed model according to the vehicle related information and the route related information of the user vehicle, and determines average recommended vehicle speeds of all running sections of the user vehicle on a preset running route. For example, the cloud server inputs vehicle-related information and route-related information of the user vehicle into an economic vehicle speed model, and an average recommended vehicle speed is output by the economic vehicle speed model.

In some embodiments, as shown in fig. 3, the cloud server may pre-build an economic vehicle speed model by performing the following steps:

Step S302, historical driving information of a plurality of types of vehicles on a plurality of running routes is acquired.

Wherein the history traveling information includes at least one of traveling road information, vehicle load information, and fuel consumption information. In some embodiments, the historical driving information further includes operational characteristic information of the vehicle during actual operation. The running characteristic information at least comprises one of position information, heading information, vehicle speed information, gear information and the like of the vehicle in the actual running process. The operation road information at least includes one of longitude and latitude information, altitude information, gradient information, slope length information, and heading information. The fuel consumption information refers to the fuel consumption of the vehicle.

Specifically, the cloud server acquires historical driving information of each type of vehicle on each running route through vehicle network data or big data, so that data preparation is performed for subsequent establishment of an economic vehicle speed model.

Step S304, segmenting each operation route to obtain a plurality of operation road sections corresponding to each operation route.

Specifically, in order to improve the calculation accuracy, the cloud server segments each of the operation routes according to a preset standard, thereby dividing each of the operation routes into a plurality of operation sections. For example, the cloud server may divide the entire travel route into a plurality of travel sections according to a standard every 5km distance. As another example, the cloud server may divide the entire operation route into a plurality of operation sections by taking the location of a toll gate on a highway as a basis for dividing the operation sections.

Step S306, the historical fuel consumption of vehicles belonging to the same type on each running road section is obtained, a plurality of candidate vehicles with the fuel consumption smaller than a threshold value are screened out, and the historical running characteristic information of the plurality of candidate vehicles on the corresponding road section is obtained.

The type of vehicle comprises at least one of a tractor, a truck and a special vehicle. In some embodiments, the types of vehicles may also be divided by driving style, such as 4×2,6×2,6×4,8×4, etc., with the numbers preceding the "×" indicating the total number of vehicle wheels and the numbers following the "×" indicating the number of driving wheels.

Specifically, the cloud server acquires the historical fuel consumption of vehicles belonging to the same type on each running road section, screens out a plurality of candidate vehicles with the fuel consumption smaller than a threshold value on each running road section, and acquires the historical running characteristic information, such as position, course, vehicle speed, gear and the like, of the candidate vehicles on the corresponding running road section. By way of example, the cloud server combines the actual load of a certain type of vehicle with the actual fuel consumption of the vehicle of the certain type on each operation road section, screens 10% vehicles (i.e. candidate vehicles) with lower actual fuel consumption in the vehicles operated on the same operation road section, and establishes an economic vehicle speed model according to the operation characteristic information of the 10% vehicles.

Step S308, the historical driving information and the historical driving characteristic information of each driving road section are classified and stored according to the type of the vehicle, and an economic vehicle speed model is built.

Specifically, the cloud server classifies and stores the historical driving information and the historical driving characteristic information of each driving road section according to the type of the vehicle, and establishes an economic vehicle speed model. The cloud server stores the corresponding historical driving information and the historical characteristic information in the form of a relational table in a database according to different vehicle types and different running road sections. Thus, when determining the vehicle type and the running route/section, the cloud server may determine corresponding historical driving information and historical characteristic information. For another example, the cloud server may further fit various data to obtain a fitting function according to the stored data, so as to complete the establishment of the economic vehicle speed model. Thus, after determining the vehicle type and the running route/road section, the cloud server can calculate a corresponding result, namely an average recommended vehicle speed, according to the fitting function.

Meanwhile, as the data of the Internet of vehicles continuously increases, the cloud server can continuously update and iterate the economic vehicle speed model, so that the accuracy of the economic vehicle speed model is continuously optimized and improved.

In the above embodiment, the economic vehicle speed model is pre-established through the internet of vehicles data, and the recommended average vehicle speed of the current road section can be obtained based on the economic vehicle speed model after the type and the running route/road section of the vehicle are obtained, so that the vehicle can have the minimum fuel consumption and the optimal running scheme on the premise of meeting the running aging requirement.

In some embodiments, as shown in fig. 4, according to the vehicle related information and the route related information of the user vehicle, matching recommendation is performed on the user vehicle based on an economic vehicle speed model, and the step of determining the average recommended vehicle speed of each running road section of the user vehicle on the preset running route includes:

Step S402, determining a plurality of vehicle speed ranges matched with each running road section on a preset running route of the user vehicle by using an economic vehicle speed model according to the route related information of the user vehicle and the type of the user vehicle.

In step S404, according to the vehicle related information of the user vehicle, based on the vehicle speed range, an average recommended vehicle speed of each operation road section of the user vehicle on the preset operation route is determined.

Specifically, the cloud server performs matching recommendation by using an economic vehicle speed model according to the route related information of the user vehicle and the type of the user vehicle, so as to determine a plurality of vehicle speed ranges matched with each operation road section on a preset operation route of the user vehicle. In the multiple vehicle speed ranges, the cloud server further determines average recommended vehicle speeds of all running road sections of the user vehicle on a preset running route according to vehicle related information of the user vehicle.

Illustratively, the cloud server obtains that the type of the user vehicle is a tractor, the operation route information is a highway from Beijing to the Shanghai, and the operation timeliness information is 20 hours. Based on this information, the cloud server determines a vehicle speed range (for example, 60km/h to 65 km/h) corresponding to each of the operation sections (for example, divided into one operation section every 10 km) on the expressway of beijing to the coast using the economic vehicle speed model established in advance. Then, the cloud server further determines an average recommended vehicle speed (for example, 65 km/h) of each of the operation sections on the preset operation route according to the vehicle-related information (for example, actual load of the vehicle) of the user vehicle.

In the above embodiment, the matching and recommendation of the vehicle speed are performed by using the pre-established economic vehicle speed model according to the type of the user vehicle, the route related information and the vehicle related information, so that the vehicle can have the minimum fuel consumption and the optimal operation scheme on the premise of meeting the operation timeliness requirement.

Step S204, acquiring real-time position information of the user vehicle during the running process of the user vehicle, and acquiring running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment based on the real-time position information.

Wherein the operation characteristic information at least includes one of vehicle speed information and gear information.

In consideration of real-time dynamic change road condition information in actual road traffic, specifically, the cloud server acquires real-time position information of a user vehicle in the running process of the user vehicle, and acquires running characteristic information of other vehicles except the user vehicle running on the same running road section at the same moment based on the real-time position information, so as to evaluate the real-time road condition information according to the running characteristic information of the other vehicles. In some embodiments, the cloud server preferentially acquires the operation characteristic information of vehicles of the same type as the user vehicle among the rest vehicles except the user vehicle. When the number of vehicles of the same type as the user vehicles is small, the cloud server acquires the operation characteristic information of the other types of vehicles.

Step S206, determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment and recommending according to the average recommended speed of the user vehicle and the running characteristic information of the rest vehicles.

Specifically, the cloud server evaluates real-time road condition information according to the operation characteristic information of the rest vehicles, and further determines and recommends the real-time recommended speed of the corresponding operation road section of the user vehicle at the current moment by combining the determined average recommended speed. The cloud server sends the real-time recommended vehicle speed to the vehicle-mounted terminal, and the vehicle-mounted terminal displays the real-time recommended vehicle speed in a mode of characters, images, voices and the like through devices such as a display screen, so that the real-time recommended vehicle speed is recommended to a user. As another example, the cloud server transmits the real-time recommended vehicle speed to the portable terminal of the user, thereby recommending the real-time recommended vehicle speed to the user.

In some embodiments, road characteristic information on the corresponding operation section may be acquired in addition to the operation characteristic information of the remaining vehicles. As shown in fig. 5, determining and recommending the real-time recommended vehicle speed of the corresponding operation road section of the user vehicle at the current moment according to the average recommended vehicle speed of the user vehicle and the operation characteristic information of the rest vehicles, including:

Step S502, acquiring road characteristic information on a corresponding running road section based on real-time position information of a user vehicle; the road characteristic information includes at least one of road gradient information, speed limit information, and road curvature information.

Step S504, determining the real-time recommended speed of the user vehicle at each moment of the corresponding operation road section based on the real-time speed analysis model according to the average speed of the user vehicle, the operation characteristic information of the rest vehicles and the road characteristic information on the corresponding operation road section, and recommending.

Specifically, the cloud server may further obtain road feature information of an actual running road section, so as to determine, based on the real-time vehicle speed analysis model, a real-time recommended vehicle speed of the user vehicle at each moment of the corresponding running road section and recommend the real-time recommended vehicle speed according to an average vehicle speed of the user vehicle, running feature information of other vehicles, and road feature information on the corresponding running road section. The cloud server can acquire road characteristic information of an actual running road section according to the internet of vehicles data, or can also be in butt joint with data of a map provider, so that the road characteristic information of the actual running road section is acquired. The specific flow and steps are similar to those of the above embodiments, please refer to the above embodiments, and the detailed description is omitted herein.

In the embodiment, the real-time recommended speed of the user vehicle at each moment of the corresponding running road section is determined by additionally considering the road characteristic information of the actual running road section and based on the real-time speed analysis model, so that errors caused by inaccurate road gradient estimation, insufficient transient working condition consideration and the like in theoretical calculation are avoided, the speed recommended result is more accurate, and the energy-saving and emission-reduction effects are better.

In some embodiments, as shown in fig. 6, the step of determining the real-time recommended speed of the user vehicle on the corresponding running road section at the current moment according to the average speed of the user vehicle and the running characteristic information of the rest vehicles includes:

Step S602, determining a vehicle speed threshold value of a corresponding running road section at the current moment according to the running characteristic information of the rest vehicles.

In step S604, the average recommended speed of the user vehicle is compared with a speed threshold, and the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment is determined based on the comparison result.

Specifically, the cloud server evaluates real-time road conditions of the current running road section according to running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment, and determines a vehicle speed threshold value of the corresponding running road section at the current moment. Wherein the vehicle speed threshold value characterizes the maximum value of the drivable speed of the user vehicle, typically determined by the lower value of the vehicle speed range in which the vehicle speeds of the remaining vehicles lie. And the cloud server compares the determined average recommended speed with a speed threshold value, and determines the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment based on the comparison result.

For example, if the speeds of the other vehicles except the user vehicle are lower (for example, lower than the recommended speed), the current running road section is more congested, so that according to the running characteristic information of the other vehicles, the speed range of the other vehicles, namely, the speed threshold value, can be determined, and the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment can be determined based on the average recommended speed and the speed threshold value; or if the speeds of the other vehicles except the user vehicle are higher, the current running road section can be smoothly passed, and the speed threshold can be determined according to the speed range of the other vehicles, so that the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment is determined.

In some embodiments, determining the real-time recommended speed of the user vehicle for the corresponding travel segment at the current time based on the comparison result includes: if the average recommended speed of the user vehicle is smaller than the speed threshold, determining the average recommended speed as the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment; if the average recommended speed of the user vehicle is greater than the speed threshold, taking the speed threshold as the maximum value of the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the maximum value.

Specifically, the cloud server compares the average recommended speed of the user vehicle with the speed threshold, if the average recommended speed of the user vehicle is smaller than the speed threshold, the current running road section can run smoothly, that is, the user vehicle runs according to the average recommended speed and is not limited by real-time road conditions, so that the cloud server can directly determine the average recommended speed as the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment. For example, if the average recommended speed is 55km/h and the speed range of the other vehicles is between 60km/h and 65km/h (correspondingly, the speed threshold is 60 km/h), the current running road section is smooth, the other vehicles can all run at a higher speed, and the user vehicles can run according to the average recommended speed, so that the purposes of reducing oil consumption, saving energy and reducing emission are achieved. If the average recommended speed of the user vehicle is greater than the speed threshold, taking the speed threshold as the maximum value of the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the maximum value. For example, if the average recommended speed is 55km/h and the speed range of the rest vehicles is between 45km/h and 50km/h (the speed threshold is 45km/h correspondingly), the rest vehicles all run at a lower speed, which indicates that the current running road section may have a congestion phenomenon, the user vehicle can run with the speed corresponding to the speed threshold as the real-time recommended speed of the corresponding running road section at the current moment, thereby reducing fuel consumption, saving energy and reducing emission, simultaneously considering the complexity of real-time road conditions and performing dynamic adjustment, and the speed recommendation result is more accurate.

In the above embodiment, the real-time road conditions of the current running road section are evaluated through the running characteristic information of the other vehicles except the user vehicle on the same running road section at the same time, the vehicle speed threshold value of the corresponding running road section at the current time is determined, the real-time recommended vehicle speed of the user vehicle at each time of the corresponding running road section is comprehensively determined based on the vehicle speed threshold value and the average recommended vehicle speed, the dynamic information of the current road can be analyzed according to the real-time internet of vehicles data, the passing vehicle speed of the vehicle is corrected, the lowest actual use fuel consumption is ensured under various complex external environments, and the energy saving and emission reduction effects are better.

According to the recommended speed determining method of the vehicle, through the vehicle related information and the route related information of the user vehicle, matching recommendation is carried out by utilizing a pre-established economic speed model, and the average recommended speed of each running road section of the user vehicle on a preset running route is determined; therefore, the running vehicle speed with lower oil consumption, energy conservation and emission reduction can be recommended to the user under the condition of meeting the running requirement of the user, and the fuel waste caused by bad driving habits is improved. Meanwhile, in the running process of the user vehicle, the real-time position information of the user vehicle is obtained, the running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment is obtained based on the real-time position information, the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment is determined and recommended based on the average recommended speed and the running characteristic information of the other vehicles, the dynamic information of the current road can be analyzed through real-time Internet of vehicles data, the running speed of the vehicle is corrected dynamically in real time, and the fuel consumption under the actual running working condition is greatly reduced; under various complex external environments, the method not only meets the operation requirement, but also ensures that the actual use oil consumption is the lowest, and is more energy-saving, environment-friendly and economical.

In some embodiments, the method for determining a recommended vehicle speed of the vehicle further includes the following steps: controlling a vehicle controller of the user vehicle to adjust the speed of the user vehicle to the real-time recommended speed; and/or prompting by utilizing a prompting device on the user vehicle so as to guide the user to adjust the speed of the user vehicle to the real-time recommended speed.

Specifically, after obtaining the real-time recommended vehicle speed, the cloud server sends the real-time recommended vehicle speed to the vehicle-mounted terminal, and the vehicle-mounted terminal controls the controller of the vehicle, so that the vehicle speed of the user vehicle is adjusted to the real-time recommended vehicle speed. For example, when the vehicle is an autonomous vehicle or the vehicle is set to an autonomous mode, the cloud server may control the controller of the vehicle through the vehicle-mounted terminal, adjust the vehicle speed toward the value of the real-time recommended vehicle speed, and continuously circulate until the steady vehicle speed is reached or the real-time recommended vehicle speed is changed. Or after the cloud server obtains the real-time recommended speed, the real-time recommended speed is sent to the vehicle-mounted terminal, and the vehicle-mounted terminal prompts by utilizing a prompting device on the user vehicle so as to guide the user to adjust the speed of the user vehicle to the real-time recommended speed. The presentation device may be, for example, a display screen, a speaker, or the like of the vehicle-mounted terminal, or may be a portable terminal (for example, a smart phone, or the like) of a user who is bound to the vehicle. For example, when the vehicle is in a user driving mode, the cloud server sends the real-time recommended vehicle speed to the vehicle-mounted terminal after obtaining the real-time recommended vehicle speed, the vehicle-mounted terminal displays the real-time recommended vehicle speed on a display screen and prompts the user to increase or decrease the speed through voice, so that the purposes of reducing the oil consumption, saving energy and reducing emission are achieved.

In the above embodiment, the vehicle speed can be automatically adjusted to the real-time recommended vehicle speed by controlling the vehicle controller of the user vehicle, and the adjustment result is faster and more accurate without manual adjustment by the user. Meanwhile, the prompt device guides the user to adjust the speed of the user vehicle to the real-time recommended speed, the real-time recommended speed can be visually displayed to the user, and the user can have good driving experience.

In a specific embodiment, a logic frame diagram of the above-mentioned method for determining a recommended speed of a vehicle may be as shown in fig. 7. The cloud server establishes an economic vehicle speed model according to running road information such as longitude, latitude, altitude, heading and the like, vehicle load information and fuel consumption information, inputs the parameters into the economic vehicle speed model according to vehicle configuration, actual vehicle load, running route and time efficiency requirements of a user vehicle, and matches the economic vehicle speed model to output average recommended vehicle speed. Meanwhile, in order to further adjust according to the real-time road conditions, the cloud server also acquires information such as real-time positioning of the vehicle, road characteristics, running characteristics of other vehicles on the current running road section and the like, and dynamically adjusts the average recommended speed by integrating the information, so that the real-time recommended speed of the corresponding road section at each moment is obtained. The cloud server can also send the real-time recommended speed to the vehicle-mounted terminal, and the vehicle-mounted terminal controls the vehicle controller, so that the automatic speed adjustment of the vehicle is realized; or the vehicle instrument can be used for prompting, so that a user is guided to manually adjust the vehicle speed, and the purposes of reducing oil consumption, saving energy and reducing emission are achieved.

It should be understood that, although the steps in the flowcharts of fig. 2-6 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2-6 may include multiple steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the steps or stages in other steps or other steps.

In one embodiment, as shown in fig. 8, there is provided a recommended vehicle speed determining device of a vehicle, including: a matching module 810, an acquisition module 820, and a processing module 830, wherein:

The matching module 810 is configured to perform matching recommendation on the user vehicle based on the economic vehicle speed model according to the vehicle related information and the route related information of the user vehicle, and determine an average recommended vehicle speed of each operation road section of the user vehicle on a preset operation route; the vehicle-related information includes at least one of vehicle configuration information and vehicle load information; the route related information includes at least one of operation route information and operation timeliness information.

The acquiring module 820 is configured to acquire real-time position information of a user vehicle during a running process of the user vehicle, and acquire running characteristic information of other vehicles except the user vehicle on the same running road section at the same time based on the real-time position information; the operation characteristic information includes at least one of vehicle speed information and gear information.

The processing module 830 is configured to determine, according to the average recommended speed of the user vehicle and the operation feature information of the remaining vehicles, a real-time recommended speed of a corresponding operation road section of the user vehicle at the current moment, and recommend the real-time recommended speed.

In one embodiment, the matching module is further configured to determine a plurality of vehicle speed ranges matched with each operation road segment on the preset operation route of the user vehicle by using the economic vehicle speed model according to the route related information of the user vehicle and the type of the user vehicle; and determining the average recommended speed of each running road section of the user vehicle on the preset running route based on the speed range according to the vehicle related information of the user vehicle.

In one embodiment, the apparatus further comprises a modeling module for obtaining historical travel information for a plurality of types of vehicles on a plurality of travel routes; the history traveling information includes at least one of traveling road information, vehicle load information, and fuel consumption information; the operation road information at least comprises one of longitude and latitude information, altitude information and heading information; segmenting each running route to obtain a plurality of running road sections corresponding to each running route; acquiring the historical fuel consumption of vehicles belonging to the same type on each running road section, screening a plurality of candidate vehicles with the fuel consumption smaller than a threshold value, and acquiring the historical running characteristic information of the plurality of candidate vehicles on the corresponding road section; wherein the type of vehicle at least comprises one of a tractor, a truck and a special vehicle; and classifying and storing the historical driving information and the historical driving characteristic information of each driving road section according to the type of the vehicle, and establishing an economic vehicle speed model.

In one embodiment, the processing module is further configured to determine a vehicle speed threshold of a corresponding operation road section at the current moment according to operation feature information of the remaining vehicles; and comparing the average recommended speed of the user vehicle with a speed threshold value, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment based on the comparison result.

In one embodiment, the processing module is further configured to determine the average recommended speed as a real-time recommended speed of the road section where the user vehicle runs at the current moment if the average recommended speed of the user vehicle is less than the speed threshold; if the average recommended speed of the user vehicle is greater than the speed threshold, taking the speed threshold as the maximum value of the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the maximum value.

In one embodiment, the processing module is further configured to obtain road feature information on a corresponding running road section based on real-time location information of the user vehicle; the road characteristic information at least comprises one of road gradient information, speed limit information and road curvature information; and determining the real-time recommended speed of the user vehicle at each moment of the corresponding running road section based on the real-time speed analysis model according to the average speed of the user vehicle, the running characteristic information of the rest vehicles and the road characteristic information on the corresponding running road section, and recommending.

The specific limitation of the recommended vehicle speed determining device for the vehicle may be referred to the limitation of the recommended vehicle speed determining method for the vehicle hereinabove, and will not be described in detail herein. The respective modules in the recommended speed determination device of the vehicle described above may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be the cloud server in the foregoing embodiment, and an internal structure diagram thereof may be as shown in fig. 9. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing vehicle-related information, route-related information, historical driving information, road characteristic information and other internet-of-vehicles information. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of determining a recommended vehicle speed for a vehicle.

It will be appreciated by persons skilled in the art that the architecture shown in fig. 9 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of: according to the vehicle related information and the route related information of the user vehicle, carrying out matching recommendation on the user vehicle based on an economic vehicle speed model, and determining the average recommended vehicle speed of each running road section of the user vehicle on a preset running route; the vehicle-related information includes at least one of vehicle configuration information and vehicle load information; the route related information at least comprises one of operation route information and operation aging information; acquiring real-time position information of a user vehicle in the running process of the user vehicle, and acquiring running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment based on the real-time position information; the operation characteristic information at least comprises one of vehicle speed information and gear information; and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the average recommended speed of the user vehicle and the running characteristic information of the rest vehicles, and recommending the real-time recommended speed.

In one embodiment, the processor when executing the computer program further performs the steps of: determining a plurality of vehicle speed ranges matched with each running road section on a preset running route of the user vehicle by using an economic vehicle speed model according to the route related information of the user vehicle and the type of the user vehicle; and determining the average recommended speed of each running road section of the user vehicle on the preset running route based on the speed range according to the vehicle related information of the user vehicle.

In one embodiment, the processor when executing the computer program further performs the steps of: acquiring historical driving information of a plurality of types of vehicles on a plurality of running routes; the history traveling information includes at least one of traveling road information, vehicle load information, and fuel consumption information; the operation road information at least comprises one of longitude and latitude information, altitude information and heading information; segmenting each running route to obtain a plurality of running road sections corresponding to each running route; acquiring the historical fuel consumption of vehicles belonging to the same type on each running road section, screening a plurality of candidate vehicles with the fuel consumption smaller than a threshold value, and acquiring the historical running characteristic information of the plurality of candidate vehicles on the corresponding road section; wherein the type of vehicle at least comprises one of a tractor, a truck and a special vehicle; and classifying and storing the historical driving information and the historical driving characteristic information of each driving road section according to the type of the vehicle, and establishing an economic vehicle speed model.

In one embodiment, the processor when executing the computer program further performs the steps of: determining a vehicle speed threshold value of a corresponding running road section at the current moment according to the running characteristic information of other vehicles; and comparing the average recommended speed of the user vehicle with a speed threshold value, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment based on the comparison result.

In one embodiment, the processor when executing the computer program further performs the steps of: if the average recommended speed of the user vehicle is smaller than the speed threshold, determining the average recommended speed as the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment; if the average recommended speed of the user vehicle is greater than the speed threshold, taking the speed threshold as the maximum value of the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the maximum value.

In one embodiment, the processor when executing the computer program further performs the steps of: controlling a vehicle controller of the user vehicle to adjust the speed of the user vehicle to the real-time recommended speed; and/or prompting by utilizing a prompting device on the user vehicle so as to guide the user to adjust the speed of the user vehicle to the real-time recommended speed.

The computer equipment carries out matching recommendation by utilizing the vehicle related information and the route related information of the user vehicle and utilizing a pre-established economic vehicle speed model to determine the average recommended vehicle speed of each running road section of the user vehicle on a preset running route; therefore, the running vehicle speed with lower oil consumption, energy conservation and emission reduction can be recommended to the user under the condition of meeting the running requirement of the user, and the fuel waste caused by bad driving habits is improved. Meanwhile, in the running process of the user vehicle, the real-time position information of the user vehicle is obtained, the running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment is obtained based on the real-time position information, the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment is determined and recommended based on the average recommended speed and the running characteristic information of the other vehicles, the dynamic information of the current road can be analyzed through real-time Internet of vehicles data, the running speed of the vehicle is corrected dynamically in real time, and the fuel consumption under the actual running working condition is greatly reduced; under various complex external environments, the method not only meets the operation requirement, but also ensures that the actual use oil consumption is the lowest, and is more energy-saving, environment-friendly and economical.

In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of: according to the vehicle related information and the route related information of the user vehicle, carrying out matching recommendation on the user vehicle based on an economic vehicle speed model, and determining the average recommended vehicle speed of each running road section of the user vehicle on a preset running route; the vehicle-related information includes at least one of vehicle configuration information and vehicle load information; the route related information at least comprises one of operation route information and operation aging information; acquiring real-time position information of a user vehicle in the running process of the user vehicle, and acquiring running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment based on the real-time position information; the operation characteristic information at least comprises one of vehicle speed information and gear information; and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the average recommended speed of the user vehicle and the running characteristic information of the rest vehicles, and recommending the real-time recommended speed.

In one embodiment, the computer program when executed by the processor further performs the steps of: determining a plurality of vehicle speed ranges matched with each running road section on a preset running route of the user vehicle by using an economic vehicle speed model according to the route related information of the user vehicle and the type of the user vehicle; and determining the average recommended speed of each running road section of the user vehicle on the preset running route based on the speed range according to the vehicle related information of the user vehicle.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring historical driving information of a plurality of types of vehicles on a plurality of running routes; the history traveling information includes at least one of traveling road information, vehicle load information, and fuel consumption information; the operation road information at least comprises one of longitude and latitude information, altitude information and heading information; segmenting each running route to obtain a plurality of running road sections corresponding to each running route; acquiring the historical fuel consumption of vehicles belonging to the same type on each running road section, screening a plurality of candidate vehicles with the fuel consumption smaller than a threshold value, and acquiring the historical running characteristic information of the plurality of candidate vehicles on the corresponding road section; wherein the type of vehicle at least comprises one of a tractor, a truck and a special vehicle; and classifying and storing the historical driving information and the historical driving characteristic information of each driving road section according to the type of the vehicle, and establishing an economic vehicle speed model.

In one embodiment, the computer program when executed by the processor further performs the steps of: determining a vehicle speed threshold value of a corresponding running road section at the current moment according to the running characteristic information of other vehicles; and comparing the average recommended speed of the user vehicle with a speed threshold value, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment based on the comparison result.

In one embodiment, the computer program when executed by the processor further performs the steps of: if the average recommended speed of the user vehicle is smaller than the speed threshold, determining the average recommended speed as the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment; if the average recommended speed of the user vehicle is greater than the speed threshold, taking the speed threshold as the maximum value of the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the maximum value.

In one embodiment, the computer program when executed by the processor further performs the steps of: controlling a vehicle controller of the user vehicle to adjust the speed of the user vehicle to the real-time recommended speed; and/or prompting by utilizing a prompting device on the user vehicle so as to guide the user to adjust the speed of the user vehicle to the real-time recommended speed.

The computer readable storage medium is used for carrying out matching recommendation by utilizing a pre-established economic vehicle speed model through vehicle related information and route related information of the user vehicle, and determining the average recommended vehicle speed of each running road section of the user vehicle on a preset running route; therefore, the running vehicle speed with lower oil consumption, energy conservation and emission reduction can be recommended to the user under the condition of meeting the running requirement of the user, and the fuel waste caused by bad driving habits is improved. Meanwhile, in the running process of the user vehicle, the real-time position information of the user vehicle is obtained, the running characteristic information of other vehicles except the user vehicle on the same running road section at the same moment is obtained based on the real-time position information, the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment is determined and recommended based on the average recommended speed and the running characteristic information of the other vehicles, the dynamic information of the current road can be analyzed through real-time Internet of vehicles data, the running speed of the vehicle is corrected dynamically in real time, and the fuel consumption under the actual running working condition is greatly reduced; under various complex external environments, the method not only meets the operation requirement, but also ensures that the actual use oil consumption is the lowest, and is more energy-saving, environment-friendly and economical.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.

Claims

1. A recommended vehicle speed determination method of a vehicle, characterized by comprising:

According to the route related information of the user vehicle and the type of the user vehicle, matching recommendation is carried out by using an economic vehicle speed model, and a plurality of vehicle speed ranges matched with each running road section on a preset running route of the user vehicle are determined;

in a plurality of vehicle speed ranges, determining average recommended vehicle speeds of all running road sections of a user vehicle on a preset running route according to vehicle related information of the user vehicle; the vehicle-related information includes at least one of vehicle configuration information and vehicle load information; the route related information at least comprises one of operation route information and operation aging information;

Determining a vehicle speed threshold value of a corresponding running road section at the current moment according to the running characteristic information of the other vehicles, wherein the vehicle speed threshold value is determined by a lower value of a vehicle speed range in which the vehicle speed of the other vehicles is positioned;

2. The method of claim 1, wherein the step of establishing the economic vehicle speed model comprises:

3. The method according to claim 1, wherein the method further comprises:

4. The method according to claim 1, wherein the method further comprises:

And controlling a vehicle controller of the user vehicle to adjust the speed of the user vehicle to the real-time recommended speed.

5. The method according to claim 1, wherein the method further comprises:

6. A recommended vehicle speed determination device of a vehicle, characterized by comprising:

The matching module is used for carrying out matching recommendation by utilizing an economic vehicle speed model according to the route related information of the user vehicle and the type of the user vehicle, and determining a plurality of vehicle speed ranges matched with each running road section on a preset running route of the user vehicle; in a plurality of vehicle speed ranges, determining average recommended vehicle speeds of all running road sections of a user vehicle on a preset running route according to vehicle related information of the user vehicle; the vehicle-related information includes at least one of vehicle configuration information and vehicle load information; the route related information at least comprises one of operation route information and operation aging information;

The processing module is used for determining a vehicle speed threshold value of a corresponding running road section at the current moment according to the running characteristic information of the other vehicles, wherein the vehicle speed threshold value is determined by a lower value of a vehicle speed range in which the vehicle speed of the other vehicles is positioned;

The processing module is used for determining the average recommended speed of the user vehicle as the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment if the average recommended speed of the user vehicle is smaller than the speed threshold; and if the average recommended speed of the user vehicle is greater than the speed threshold, taking the speed threshold as the maximum value of the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment, and determining the real-time recommended speed of the corresponding running road section of the user vehicle at the current moment according to the maximum value.

7. The apparatus of claim 6, further comprising a modeling module for obtaining historical travel information for a plurality of types of vehicles on a plurality of travel routes; the history driving information at least comprises one of driving road information, vehicle load information and fuel consumption information; the operation road information at least comprises one of longitude and latitude information, altitude information and heading information; segmenting each running route to obtain a plurality of running road sections corresponding to each running route; acquiring the historical fuel consumption of vehicles belonging to the same type on each running road section, screening a plurality of candidate vehicles with the fuel consumption smaller than a threshold value, and acquiring the historical running characteristic information of the plurality of candidate vehicles on the corresponding road section; wherein the type of vehicle at least comprises one of a tractor, a truck and a special vehicle; and classifying and storing the historical driving information and the historical driving characteristic information of each driving road section according to the type of the vehicle, and establishing an economic vehicle speed model.

8. The apparatus of claim 6, wherein the processing module is configured to obtain road feature information on a corresponding operating road segment based on real-time location information of the user vehicle; the road characteristic information at least comprises one of road gradient information, speed limit information and road curvature information; and determining the real-time recommended speed of the user vehicle at each moment of the corresponding running road section based on a real-time speed analysis model according to the average speed of the user vehicle, the running characteristic information of the rest vehicles and the road characteristic information on the corresponding running road section, and recommending.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 5 when the computer program is executed.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 5.