CN117565876A

CN117565876A - Method for counting driving data of commercial vehicle, commercial vehicle and storage medium

Info

Publication number: CN117565876A
Application number: CN202311605411.9A
Authority: CN
Inventors: 聂利井; 孙建兴; 李忠伟; 于泽涛
Original assignee: Beijing Foton Daimler Automobile Co Ltd
Current assignee: Beijing Foton Daimler Automobile Co Ltd
Priority date: 2023-11-28
Filing date: 2023-11-28
Publication date: 2024-02-20

Abstract

The invention discloses a method for counting running data of a commercial vehicle, the commercial vehicle and a storage medium, wherein the method for counting the running data of the commercial vehicle comprises the following steps: determining an adaptive cruise control mode start of the commercial vehicle; triggering a curve driving habit data acquisition event in response to the commercial vehicle meeting curve working condition; and counting and storing curve driving habit data of the driver on the commercial vehicle. By adopting the method, the driving habits of the drivers in the curve scene can be stored, the driving habits of the drivers in a large number of curve scenes can be analyzed, and data support is provided for development of auxiliary driving functions such as self-adaptive cruising of subsequent commercial vehicles.

Description

Method for counting driving data of commercial vehicle, commercial vehicle and storage medium

Technical Field

The present invention relates to the field of vehicles, and more particularly, to a method for counting driving data of a commercial vehicle, and a non-volatile readable storage medium.

Background

In the related art, in the development process of auxiliary driving functions such as a current self-adaptive cruise system, curve speed limiting processing is carried out on curve working conditions, but the definition of lower speed limiting values of different curve radiuses and threshold values of lateral acceleration only meet the requirements of related regulations, and the driving habit of a driver is not analyzed from the aspect of subjective feeling of the driver.

Disclosure of Invention

The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, an object of the present invention is to provide a method for calculating driving data of a commercial vehicle, by which driving habit data of a driver in a curve scene can be stored, and data support is provided for development of auxiliary driving functions such as adaptive cruise of a subsequent commercial vehicle.

The second object of the invention is to provide a commercial vehicle.

It is a further object of the invention to provide a non-volatile readable storage medium.

In order to solve the above problem, an embodiment of a first aspect of the present invention provides a method for calculating driving data of a commercial vehicle, which is characterized by comprising: determining an adaptive cruise control mode start of the commercial vehicle; triggering a curve driving habit data acquisition event in response to the commercial vehicle meeting curve working condition; and counting and storing curve driving habit data of the driver on the commercial vehicle.

According to the method for counting the driving data of the commercial vehicle, which is disclosed by the embodiment of the invention, under the curve working condition, the driving habit data of the driver on the curve is collected and stored, namely, the driving habit of the driver in the curve scene is analyzed to obtain the driving data of the vehicle in the curve scene, and data support is provided for the development of auxiliary driving functions such as self-adaptive cruising of the subsequent commercial vehicle.

In some embodiments, the commercial vehicle meeting curve operating conditions includes: the speed of the commercial vehicle is greater than 40km/h.

In some embodiments, the commercial vehicle meeting curve operating conditions further comprises: the curve radius of the commercial vehicle is larger than 500m.

In some embodiments, the curve driving habit data includes: steering wheel angle, lateral acceleration, longitudinal acceleration, brake pedal depth, and accelerator pedal depth.

In some embodiments, the method further comprises: and when the speed of the commercial vehicle is less than or equal to 40km/h or the curve radius of the commercial vehicle is less than or equal to 500m, not triggering the curve driving habit data acquisition event.

In some embodiments, the curve driving habit data is collected by an onboard T-BOX and transmitted.

An embodiment of a second aspect of the present invention provides a commercial vehicle, including: at least one processor; a memory communicatively coupled to the at least one processor; the memory stores a computer program executable by the at least one processor, the at least one processor implementing the method for calculating the commercial vehicle driving data according to any one of the above embodiments when executing the computer program.

According to the commercial vehicle provided by the embodiment of the invention, under the curve working condition, the driving habit data of the driver on the curve is collected and stored, and the driving habit of the driver in the curve scene is analyzed to obtain the vehicle driving data in the curve scene, so that data support is provided for the development of auxiliary driving functions such as self-adaptive cruising of the subsequent commercial vehicle.

In some embodiments, the commercial vehicle further comprises: and the sensors are connected with the at least one processor and are used for collecting curve driving habit data.

In some embodiments, the commercial vehicle is characterized in that the commercial vehicle travel data comprises curve driving habit data; the commercial vehicle further comprises an adaptive cruise control system for executing an adaptive cruise mode, which is optimized based on the curve driving habit data.

An embodiment of a third aspect of the present invention provides a non-transitory readable storage medium having stored thereon a computer program, wherein the computer program when executed implements the method for counting travel data of a commercial vehicle according to any one of the above embodiments.

Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

Drawings

The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

FIG. 1 is a flow chart of a method of counting travel data of a commercial vehicle according to one embodiment of the invention;

FIG. 2 is a flow chart of statistical commercial vehicle travel data according to one embodiment of the present invention;

FIG. 3 is a block diagram of a commercial vehicle according to one embodiment of the present invention.

Reference numerals:

a commercial vehicle 10;

a processor 1; a memory 2; a sensor 3.

Detailed Description

Embodiments of the present invention are described in detail below, which are exemplary with reference to the accompanying drawings.

A method of counting travel data of a commercial vehicle according to an embodiment of the first aspect of the present invention is described below with reference to fig. 1. As shown in fig. 1, the method at least includes steps S1 to S3.

Step S1, determining that an adaptive cruise control mode of the commercial vehicle is started.

Specifically, during running of the vehicle, the driver determines whether to turn on the adaptive cruise control mode according to the road condition, driving habits, and the like. The adaptive cruise may be referred to as an active cruise, and the system includes a radar sensor, a digital signal processor, and a control module, similar to conventional constant speed cruise control. In an adaptive cruise system, the system uses a low power radar or infrared beam to obtain the exact position of the lead vehicle, and if the lead vehicle is decelerated or a new target is detected, the system sends an execution signal to the engine or brake system to reduce the speed of the vehicle, thereby maintaining a safe distance between the vehicle and the lead vehicle. After the obstacle on the road in front is cleared, the speed of the vehicle is accelerated to be recovered to the set speed, and the radar system automatically monitors the next target. The adaptive cruise control mode replaces the driver to control vehicle speed, avoiding frequent cancellation and setting of cruise control.

And step S2, triggering a curve driving habit data acquisition event in response to the fact that the commercial vehicle meets the curve working condition.

Specifically, after the commercial vehicle starts the adaptive cruise control mode, the commercial vehicle adaptive cruise control mode passes through a curve under the curve working condition according to the preset curve working condition, if the preset curve working condition can not effectively enable the commercial vehicle to pass through the curve, a driver controls the vehicle to pass through the curve at the moment, when the vehicle passes through the curve in the process of starting the commercial vehicle adaptive cruise control mode, a detected driver controls the vehicle and then triggers a curve driving habit data acquisition event to acquire the curve driving habit data of the driver.

And S3, counting and storing curve driving habit data of the driver on the commercial vehicle.

Specifically, in the adaptive cruise control mode, the collected driving habit number of the curve is statistically uploaded to a memory and stored, and corresponding driving habit data of the driver is obtained through analysis of a large amount of data.

According to the method for counting the driving data of the commercial vehicle, which is disclosed by the embodiment of the invention, under the curve working condition, the driving habit data of the driver on the curve is collected and stored, and the driving habit of the driver in the curve scene is analyzed to obtain the driving data of the vehicle in the curve scene, so that data support is provided for the development of auxiliary driving functions such as self-adaptive cruising of the subsequent commercial vehicle.

In some embodiments, the commercial vehicle meeting the curve operating condition includes: the speed of the commercial vehicle is greater than 40km/h.

Specifically, the vehicle speed is controlled below 40km/h to be the safest when the vehicle turns on the curve, and the turning angle is considered, if the angle is larger, the number of vehicles is correspondingly reduced, so that after the adaptive cruise control mode of the commercial vehicle is started, the adaptive cruise control system of the commercial vehicle controls the vehicle to pass through the curve at the vehicle speed of less than or equal to 40km/h per hour when the commercial vehicle turns on the curve, and only safety factors are considered at the moment; if the driver judges that the road is safe at the moment, the driver controls the vehicle to pass through the curve at the speed greater than 40km/h, and at the moment, the road information and the corresponding speed are statistically stored.

In some embodiments, the commercial vehicle meeting curve operating conditions further comprises: the curve radius of the commercial vehicle is more than 500m.

Specifically, the expressway design standard requires that the radius of the curve is required to meet the regulations, the curve radius refers to the curvature radius of the central line of the curve, the size of the curve radius directly influences the running speed and stability of the vehicle in the curve, and generally, the curve radius of the expressway or the urban expressway should be more than or equal to 500m, so that the condition that the vehicle does not sideslip or run out of control when running in the curve can be ensured. The curve radius of the expressway or the urban expressway is generally larger than or equal to 500m, so that the condition that the vehicle enters the curve can be determined when the curve radius of the commercial vehicle is detected to be larger than 500m, and the running data of the commercial vehicle is statistically stored.

Specifically, when the commercial vehicle passes through a curve, detecting the steering wheel angle of the commercial vehicle under the current curve working condition through a steering wheel angle sensor; the lateral acceleration of the commercial vehicle refers to the acceleration in the direction perpendicular to the running direction of the automobile, and the acceleration caused by the centrifugal force generated when the commercial vehicle runs in a turning way, namely the tendency of the commercial vehicle to be thrown away, is easy to be thrown away from a running path theoretically when the lateral acceleration is larger, so that the lateral acceleration of the commercial vehicle under the current curve working condition is detected through a lateral acceleration sensor when the commercial vehicle passes through a curve; the longitudinal acceleration of the commercial vehicle is the acceleration along the trend of the commercial vehicle, and the longitudinal acceleration of the commercial vehicle under the current curve working condition is detected by a longitudinal acceleration sensor when the commercial vehicle passes through a curve; detecting the depth of a brake pedal when the commercial vehicle passes through a curve through a brake pedal depth sensor, and detecting the depth of an accelerator pedal when the commercial vehicle passes through the curve through an accelerator pedal depth sensor; and storing the detected curve driving habit data.

In some embodiments, the method of counting commercial vehicle travel data further comprises: and when the speed of the commercial vehicle is less than or equal to 40km/h or the radius of the curve of the commercial vehicle is less than or equal to 500m, the curve driving habit data acquisition event is not triggered.

Specifically, the vehicle speed is controlled below 40km/h to be the safest when the vehicle turns on the curve, so that after the self-adaptive cruise control mode of the commercial vehicle is started, the self-adaptive cruise control system of the commercial vehicle controls the vehicle to pass through the curve at the vehicle speed of less than or equal to 40km/h per hour when the commercial vehicle turns on the curve, the vehicle speed is the safe vehicle speed at the moment, and the driving habit data acquisition event of the curve is not triggered for the number of vehicles with the vehicle speed of less than or equal to 40 km/h; the curve radius of the expressway or the urban expressway is generally larger than or equal to 500m, so that the situation that the vehicle does not sideslip or run away when running in the curve can be guaranteed. Therefore, the vehicle can be determined to enter the curve working condition when the curve radius of the commercial vehicle is detected to be larger than 500m, the running data of the commercial vehicle is statistically stored, the commercial vehicle can deviate from a lane when the curve radius of the commercial vehicle is smaller than or equal to 500m and turns under the curve working condition, and therefore the curve driving habit data acquisition event is not triggered.

Specifically, a vehicle-mounted T-BOX (Telematics BOX) is specially used for vehicles, namely, services such as driving data acquisition, remote inquiry, control and fault monitoring are provided for the vehicles by using remote communication and information science technology; in the running process of the vehicle, if the self-adaptive cruise control mode is started, a curve driving habit data acquisition event is triggered, the vehicle-mounted T-BOX acquires and stores curve driving habit data, the acquired data are sent to the cloud, a large amount of driving habit data are analyzed, and corresponding turning speeds of the curve under different road conditions are obtained.

The following describes an example of statistical commercial vehicle driving data steps according to an embodiment of the present invention with reference to fig. 2, and the specific contents are as follows.

And S4, starting the adaptive cruise control mode.

Step S5, vehicle speed >40km/h? If yes, go to step S7, otherwise go to step S6.

Step S6, the data recording event is not triggered.

Step S7, curve radius >500CM? If yes, go to step S8, otherwise go to step S6.

Step S8, triggering the T-BOX data record, and collecting and uploading signals: steering wheel angle, lateral acceleration, longitudinal acceleration, brake pedal depth, and accelerator pedal depth.

Step S9, ending.

A second aspect of the present invention provides a commercial vehicle, as shown in fig. 3, the commercial vehicle 20 comprising: at least one processor 1 and a memory 2.

The memory 2 stores a computer program executable by the at least one processor 1, and the method for counting the driving data of the commercial vehicle according to the above embodiment is implemented when the at least one processor 1 executes the computer program.

In some embodiments, as shown in fig. 3, the commercial vehicle 20 includes: a plurality of sensors 3.

Wherein a plurality of sensors 3 are connected with at least one processor for gathering curve driving habit data.

Specifically, after the self-adaptive cruise control mode is started in the running process of the commercial vehicle, the steering wheel angle, the transverse acceleration, the longitudinal acceleration, the brake pedal depth and the accelerator pedal depth of the commercial vehicle are respectively detected by a plurality of sensors 3 under the curve working condition, the detected data are sent to a processor, and the processor collects and analyzes curve driving habit data.

In some embodiments, the commercial vehicle travel data includes curve driving habit data; the commercial vehicle further comprises an adaptive cruise control system for executing an adaptive cruise mode, which is optimized based on curve driving habit data.

Specifically, the commercial vehicle driving data comprise curve driving habit data, and the curve driving habit data are acquired through acquisition of steering wheel rotation angle, transverse acceleration, longitudinal acceleration, brake pedal depth and accelerator pedal depth; the commercial vehicle analyzes the acquired curve driving habit data to obtain the optimal turning speed under certain road conditions; the commercial vehicle comprises an adaptive cruise control system, the adaptive cruise control system is used for executing an adaptive cruise mode, the adaptive cruise mode is obtained based on curve driving habit data in an optimized mode, and when the commercial vehicle analyzes a large amount of curve driving habit data, the optimal turning speed under certain road conditions is obtained; and after obtaining the optimal turning speed, controlling the commercial vehicle to pass through the curve at the obtained optimal turning speed when the adaptive cruise control mode is started for the second time.

An embodiment of the third aspect of the present invention provides a non-transitory readable storage medium having stored thereon a computer program, characterized in that the computer program when executed implements the method of counting travel data of a commercial vehicle according to the above embodiment.

In the description of this specification, any process or method description in a flowchart or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing logical functions or steps of the process, and in which the scope of the preferred embodiments of the present invention include additional implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present invention.

Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.

It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.

Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.

The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.

In the description of the present specification, a description referring to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, substrate, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples.

While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method of calculating travel data for a commercial vehicle, comprising:

determining an adaptive cruise control mode start of the commercial vehicle;

triggering a curve driving habit data acquisition event in response to the commercial vehicle meeting curve working condition;

and counting and storing curve driving habit data of the driver on the commercial vehicle.

2. The method of calculating driving data of a commercial vehicle according to claim 1, wherein the commercial vehicle satisfies a curve condition comprises: the speed of the commercial vehicle is greater than 40km/h.

3. The method of calculating travel data for a commercial vehicle of claim 2, wherein the commercial vehicle meeting curve conditions further comprises: the curve radius of the commercial vehicle is larger than 500m.

4. A method of calculating driving data of a commercial vehicle according to any one of claims 1-3, wherein the curve driving habit data comprises: steering wheel angle, lateral acceleration, longitudinal acceleration, brake pedal depth, and accelerator pedal depth.

5. A method of calculating travel data for a commercial vehicle according to claim 3, further comprising:

and when the speed of the commercial vehicle is less than or equal to 40km/h or the curve radius of the commercial vehicle is less than or equal to 500m, not triggering the curve driving habit data acquisition event.

6. A method of calculating driving data of a commercial vehicle according to any one of claims 1 to 3, wherein the curve driving habit data is collected by an on-board T-BOX and transmitted.

7. A commercial vehicle, comprising:

at least one processor;

a memory communicatively coupled to the at least one processor;

stored in the memory is a computer program executable by the at least one processor, which when executing the computer program implements the method of counting commercial vehicle travel data according to any one of claims 1-6.

8. The commercial vehicle of claim 7, further comprising:

and the sensors are connected with the at least one processor and are used for collecting curve driving habit data.

9. The commercial vehicle of claim 8, wherein the vehicle is configured to provide a vehicle body,

the commercial vehicle driving data comprise curve driving habit data;

the commercial vehicle further comprises an adaptive cruise control system for executing an adaptive cruise mode, which is optimized based on the curve driving habit data.

10. A non-transitory readable storage medium having stored thereon a computer program, characterized in that the computer program when executed implements the method of counting commercial vehicle travel data according to any one of claims 1-6.