CN110636468A - Road condition detection method, system, storage medium and vehicle machine - Google Patents
Road condition detection method, system, storage medium and vehicle machine Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
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- H—ELECTRICITY
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Abstract
The invention provides a road condition detection method, a system, a storage medium and a vehicle machine, wherein the road condition detection method comprises the following steps: the vehicle machine is in communication connection with at least one mobile intelligent terminal; receiving sensor real-time data sent by a mobile intelligent terminal; the real-time data comprises acceleration data; calculating a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the real-time data; and obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal. The invention solves the problem that the vehicle can not detect the road condition information in the prior art, and the vehicle owner can only judge the road condition information according to the bumping degree by experience. The mobile phones on the vehicle are creatively utilized to monitor the road condition in the driving process of the vehicle, and the more the number of the mobile phones are accessed, the more real the monitored road condition is.
Description
Technical Field
The invention belongs to the technical field of vehicles, and particularly relates to a road condition detection method, a road condition detection system, a storage medium and a vehicle machine.
Background
In the prior art, the vehicle cannot detect the road condition information, the vehicle owner can only judge the road condition information according to the degree of bumping by experience, the driving risk of the vehicle on the bumpy road condition is high, the vehicle owner is required to adjust the driving speed in time according to the road condition information, and the vehicle owner judges that certain errors and hysteresis exist in the road condition information according to the experience of the vehicle owner, so that the driving safety is not facilitated.
In the prior art, a method for detecting the road flatness exists, which uses an accelerometer to detect the relative displacement generated by a laser distance measuring device due to road bumping, and then uses a three-way gyroscope to detect the angle of inclination of the laser distance measuring device due to road bumping, calculates the vertical distance between the laser distance measuring device and the road, obtains each vertical distance according to the detection density, obtains the difference value between the vertical distance and a standard reference distance, and obtains the flatness of a longitudinal section curve and the road surface.
Disclosure of Invention
In view of the above disadvantages of the prior art, an object of the present invention is to provide a road condition detection method, system, storage medium and vehicle device, which are used to solve the problems that in the prior art, a vehicle cannot detect road condition information, a vehicle owner can only judge the road condition information according to a degree of jounce by experience, the vehicle is highly dangerous to drive on a bumpy road condition, the vehicle owner needs to adjust a driving speed in time according to the road condition information, and the vehicle owner judges that the road condition information has a certain error and hysteresis according to own experience, which is not favorable for driving safety.
In order to achieve the above and other related objects, the present invention provides a road condition detecting method, including: the vehicle machine is in communication connection with at least one mobile intelligent terminal; receiving sensor real-time data sent by a mobile intelligent terminal; the real-time data comprises acceleration data; calculating a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the real-time data; and obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal.
In an embodiment of the present invention, the communication connection includes: bluetooth connection, or/and AP hotspot connection.
In an embodiment of the present invention, the acceleration data includes: acceleration component a in x-axis, y-axis, and z-axis directionsx、ay、az。
In an embodiment of the present invention, an implementation process of calculating a periodic variation difference of a coordinate point of a mobile intelligent terminal includes: setting a periodic variation difference value of a coordinate point in a preset period of a mobile intelligent terminal as { x, y, z }, wherein components of the acceleration data in an x axis, a y axis and a z axis are respectively ax、ay、azPresetting the sampling time as t; (lateraln-1))/n; (longitudinal n-longitudinal n-1))/n; z ═ ((vertical 2-vertical 1) + (vertical 3-vertical 2) +. (vertical n-vertical n-1))/n; a is the average nx×t2；longitudinal n＝ay×t2；vertical n＝az×t2(ii) a The sampling method comprises the steps that n represents sampling times in a preset period, n is preset period duration/preset sampling duration, lateraln represents x-axis displacement data during nth sampling, longitudinal n represents y-axis displacement data during nth sampling, vertical n represents z-axis displacement data during nth sampling, lateraln-1 represents a displacement data change difference value between nth sampling and an x-axis of (n-1) th sampling, longitudinal n-longitudinal n-1 represents a displacement data change difference value between nth sampling and a y-axis of (n-1) th sampling, and vertical n-vertical n-1 represents a displacement data change difference value between nth sampling and a z-axis of (n-1) th sampling.
In an embodiment of the present invention, an implementation process of obtaining a road surface condition of a road segment covered by the at least one mobile intelligent terminal according to a periodically varying difference of the coordinate point of the at least one mobile intelligent terminal includes: judging whether the periodic variation difference values of the coordinate points of the one or more mobile intelligent terminals are all smaller than a preset threshold value; if yes, judging the road condition of the corresponding road section to be flat; otherwise, judging the road condition of the corresponding road section as bumpiness.
In order to achieve the above and other related objects, the present invention provides a traffic detection system, comprising: the mobile intelligent terminal sends sensor real-time data of the mobile intelligent terminal to the vehicle machine; the vehicle machine is in communication connection with at least one mobile intelligent terminal and receives sensor real-time data of the mobile intelligent terminal; calculating a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the real-time data of the sensor of the mobile intelligent terminal; obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal; and displaying the road surface condition on the display module.
In an embodiment of the present invention, an implementation process of the car machine calculating a periodic variation difference of a coordinate point of the mobile intelligent terminal includes: setting a periodic variation difference value of a coordinate point in a preset period of a mobile intelligent terminal as { x, y, z }, wherein components of the acceleration data in an x axis, a y axis and a z axis are respectively ax、ay、azPresetting the sampling time as t; (lateraln-1))/n; (longitudinal n-longitudinal n-1))/n; z ═ ((vertical 2-vertical 1) + (vertical 3-vertical 2) +. (vertical n-vertical n-1))/n; a is the average nx×t2；longitudinal n＝ay×t2；vertical n＝az×t2(ii) a The sampling method comprises the steps that n represents sampling times in a preset period, n is preset period duration/preset sampling duration, lateraln represents x-axis displacement data during nth sampling, longitudinal n represents y-axis displacement data during nth sampling, vertical n represents z-axis displacement data during nth sampling, lateraln-1 represents a displacement data change difference value between nth sampling and an x-axis of (n-1) th sampling, longitudinal n-longitudinal n-1 represents a displacement data change difference value between nth sampling and a y-axis of (n-1) th sampling, and vertical n-vertical n-1 represents a displacement data change difference value between nth sampling and a z-axis of (n-1) th sampling.
In an embodiment of the present invention, an implementation process of the car machine obtaining a road surface condition of a road section covered by the at least one mobile intelligent terminal according to a periodic variation difference of the coordinate point of the at least one mobile intelligent terminal includes: the vehicle machine judges whether the periodic variation difference values of the coordinate points of the one or more mobile intelligent terminals are all smaller than a preset threshold value; if yes, judging the road condition of the corresponding road section to be flat; otherwise, judging the road condition of the corresponding road section as bumpiness.
To achieve the above and other related objects, the present invention also provides a storage medium characterized in that: the storage medium stores a computer program; the computer program executes the road condition detection method according to the present invention when being called by the processor.
In order to achieve the above and other related objects, the present invention further provides a car machine communicatively connected to at least one mobile intelligent terminal, wherein the car machine comprises: the communication module is used for receiving the real-time data of the sensor of the mobile intelligent terminal; the processor is in communication connection with the communication module and calculates the periodic variation difference value of the coordinate point of the mobile intelligent terminal according to the real-time data of the sensor of the mobile intelligent terminal; and obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal. And the display module is in communication connection with the processor and displays the road surface condition.
As described above, the road condition detection method, system, storage medium and vehicle device of the present invention have the following beneficial effects: the invention solves the problems that the vehicle can not detect the road condition information, the vehicle owner can only judge the road condition information according to the degree of bumping by experience in the prior art, the vehicle runs on the bumpy road condition with high danger, the vehicle owner needs to adjust the running speed in time according to the road condition information, and the vehicle owner judges that the road condition information has certain error and hysteresis according to the experience of the vehicle owner and is not beneficial to the running safety. The mobile phones on the vehicle are creatively utilized to realize the monitoring of the road condition in the driving process of the vehicle, and the more the number of the mobile phones are accessed, the more real the monitored road condition is.
Drawings
Fig. 1 is a schematic flow chart illustrating an implementation of the road condition detection method according to the embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating an implementation process of determining a road surface condition according to a periodically varying difference of coordinate points of a mobile intelligent terminal according to an embodiment of the present invention.
Fig. 3A is a schematic structural diagram of a road condition detecting system according to an embodiment of the invention.
Fig. 3B is a schematic structural diagram of a vehicle machine according to an embodiment of the present invention.
Fig. 4 is a schematic diagram illustrating a calculation of a period variation difference of a coordinate point of a mobile intelligent terminal according to an embodiment of the present invention.
Description of the element reference numerals
300 road condition detection system
310 mobile intelligent terminal
320 vehicle machine
321 communication module
322 processor
323 display module
S101 to S104
S201 to S204
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the drawings only show the components related to the present invention rather than the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
Referring to fig. 1, an embodiment of the present invention provides a road condition detection method, where the road condition detection method includes:
and S101, the vehicle machine is in communication connection with at least one mobile intelligent terminal. Specifically, the communicatively coupling includes: bluetooth connection, or/and AP hotspot connection.
S102, receiving sensor real-time data sent by the mobile intelligent terminal; the real-time data includes acceleration data. Specifically, the acceleration data includes: acceleration component a in x-axis, y-axis, and z-axis directionsx、ay、az。
And S103, calculating a periodic variation difference value of the coordinate point of the mobile intelligent terminal according to the real-time data.
And S104, acquiring the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal.
In an embodiment of the present invention, an implementation process of calculating the period variation difference of the coordinate point of the mobile intelligent terminal in step S103 includes:
setting a periodic variation difference value of a coordinate point in a preset period of a mobile intelligent terminal as { x, y, z }, wherein components of the acceleration data in an x axis, a y axis and a z axis are respectively ax、ay、azPresetting the sampling time as t;
x＝((lateral 2-lateral 1)+(lateral 3-lateral 2)+...(lateral n-lateral n-1))/n；y＝((longitudinal 2-longitudinal 1)+(longitudinal 3-longitudinal 2)+...(longitudinal n-longitudinal n-1))/n；z＝((vertical 2-vertical 1)+(vertical 3-vertical 2)+...(vertical n-vertical n-1))/n；lateral n＝ax×t2；longitudinal n＝ay×t2；vertical n＝az×t2；
the sampling method comprises the steps that n represents sampling times in a preset period, n is preset period duration/preset sampling duration, lateraln represents x-axis displacement data during nth sampling, longitudinal n represents y-axis displacement data during nth sampling, vertical n represents z-axis displacement data during nth sampling, lateraln-1 represents a displacement data change difference value between nth sampling and an x-axis of (n-1) th sampling, longitudinal n-longitudinal n-1 represents a displacement data change difference value between nth sampling and a y-axis of (n-1) th sampling, and vertical n-vertical n-1 represents a displacement data change difference value between nth sampling and a z-axis of (n-1) th sampling.
Referring to fig. 2, an implementation process of obtaining a road condition of a road segment covered by at least one mobile intelligent terminal according to a periodic variation difference of a coordinate point of the at least one mobile intelligent terminal in step S104 includes:
s201, judging the road surface condition according to the periodic variation difference value of the coordinate points of the mobile intelligent terminal.
And S202, judging whether the periodic variation difference values of the coordinate points of the one or more mobile intelligent terminals are all smaller than a preset threshold value. Specifically, the preset threshold may be set to { x1, y1, z1}, and when x < x1, y < y1, and z < z1, the periodic variation difference { x, y, z } of the coordinate points of the mobile intelligent terminal is smaller than the preset threshold { x1, y1, z1 }.
And S203, if yes, judging the road condition of the corresponding road section to be flat.
And S204, otherwise, judging the road condition of the corresponding road section to be bumpy.
The protection scope of the road condition detection method of the present invention is not limited to the execution sequence of the steps listed in this embodiment, and all schemes of increasing or decreasing steps and replacing steps in the prior art according to the principle of the present invention are included in the protection scope of the present invention.
The invention also provides a road condition detection system, which can realize the road condition detection method of the invention, but the realization device of the road condition detection method of the invention includes but is not limited to the structure of the road condition detection system listed in the embodiment, and all structural modifications and replacements in the prior art according to the principle of the invention are included in the protection scope of the invention.
Referring to fig. 3, an embodiment of the present invention further provides a road condition detecting system, where the road condition detecting system 300 includes: at least one mobile intelligent terminal 310 and a vehicle machine 320.
And the mobile intelligent terminal 310 sends the sensor real-time data of the mobile intelligent terminal to the vehicle machine.
The car machine 320 is in communication connection with at least one mobile intelligent terminal and receives sensor real-time data of the mobile intelligent terminal; calculating a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the real-time data of the sensor of the mobile intelligent terminal; obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal; and displaying the road surface condition on the display module.
In an embodiment of the present invention, an implementation process of the car machine calculating a periodic variation difference of a coordinate point of the mobile intelligent terminal includes:
setting a periodic variation difference value of a coordinate point in a preset period of a mobile intelligent terminal as { x, y, z }, wherein components of the acceleration data in an x axis, a y axis and a z axis are respectively ax、ay、azPresetting the sampling time as t;
x＝((lateral 2-lateral 1)+(lateral 3-lateral 2)+...(lateral n-lateral n-1))/n；y＝((longitudinal 2-longitudinal 1)+(longitudinal 3-longitudinal 2)+...(longitudinal n-longitudinal n-1))/n；z＝((vertical 2-vertical 1)+(vertical 3-vertical 2)+...(vertical n-vertical n-1))/n；lateral n＝ax×t2；longitudinal n＝ay×t2；vertical n＝az×t2；
the sampling method comprises the steps that n represents sampling times in a preset period, n is preset period duration/preset sampling duration, lateraln represents x-axis displacement data during nth sampling, longitudinal n represents y-axis displacement data during nth sampling, vertical n represents z-axis displacement data during nth sampling, lateraln-1 represents a displacement data change difference value between nth sampling and an x-axis of (n-1) th sampling, longitudinal n-longitudinal n-1 represents a displacement data change difference value between nth sampling and a y-axis of (n-1) th sampling, and vertical n-vertical n-1 represents a displacement data change difference value between nth sampling and a z-axis of (n-1) th sampling.
In an embodiment of the present invention, an implementation process of obtaining, by the car machine, a road surface condition of a road segment covered by the at least one mobile intelligent terminal according to a periodic variation difference of the coordinate point of the at least one mobile intelligent terminal includes: judging whether the periodic variation difference values of the coordinate points of the one or more mobile intelligent terminals are all smaller than a preset threshold value; if yes, judging the road condition of the corresponding road section to be flat; otherwise, judging the road condition of the corresponding road section as bumpiness.
To achieve the above and other related objects, the present invention also provides a storage medium characterized in that: the storage medium stores a computer program; the computer program executes the road condition detection method according to the present invention when being called by the processor.
Referring to fig. 3B, to achieve the above and other related objects, the present invention further provides a car machine 320 communicatively connected to at least one mobile intelligent terminal, wherein the car machine includes: a display module 321, a communication module 322, and a processor 323.
The communication module 322 receives the real-time sensor data of the mobile intelligent terminal.
The processor 323 is in communication connection with the communication module, and calculates a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the real-time data of the sensor of the mobile intelligent terminal; and obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal.
The display module 321 is communicatively coupled to the processor and displays the road condition.
Please refer to fig. 4, which is a diagram illustrating a period variation difference of a coordinate point of a mobile intelligent terminal according to an embodiment of the present invention, wherein a numerical value "average" represents an x-axis displacement value generated within a sampling duration, a numerical value "longitudinal" represents a y-axis displacement value generated within the sampling duration, and a numerical value "vertical" represents a y-axis displacement value generated within the sampling duration.
As described above, the road condition detection method and system of the present invention have the following beneficial effects: the mobile phones on the vehicle are creatively utilized to realize the monitoring of the road condition in the driving process of the vehicle, and the more the number of the mobile phones are accessed, the more real the monitored road condition is.
The invention solves the problems that the vehicle can not detect the road condition information in the prior art, the vehicle owner can only judge the road condition information according to the degree of jounce by experience, the vehicle runs on the bumpy road condition with high danger, the vehicle owner needs to adjust the running speed according to the road condition information in time, and the vehicle owner judges the road condition information according to the experience and has certain error and hysteresis, which are not beneficial to the running safety, thereby effectively overcoming various defects in the prior art and having high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A road condition detection method is characterized by comprising the following steps:
the vehicle machine is in communication connection with at least one mobile intelligent terminal;
receiving sensor real-time data sent by a mobile intelligent terminal; the real-time data comprises acceleration data;
calculating a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the real-time data;
and obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal.
2. The traffic condition detection method according to claim 1, wherein the communication connection comprises: bluetooth connection, or/and AP hotspot connection.
3. The traffic condition detection method according to claim 1, wherein the acceleration data includes: acceleration components a in x-axis, y-axis and z-axis directions, respectivelyx、ay、az。
4. The traffic condition detection method according to claim 2, wherein one implementation process of calculating the periodic variation difference of the coordinate points of the mobile intelligent terminal comprises:
setting a periodic variation difference value of a coordinate point in a preset period of a mobile intelligent terminal as { x, y, z }, and setting a preset sampling time length as t;
x＝((lateral 2-lateral 1)+(lateral 3-lateral 2)+...(lateral n-lateral n-1))/n；y＝((longitudinal 2-longitudinal 1)+(longitudinal 3-longitudinal 2)+...(longitudinal n-longitudinal n-1))/n；
z＝((vertical 2-vertical 1)+(vertical 3-vertical 2)+...(vertical n-vertical n-1))/n；
lateral n＝ax×t2；
longitudinal n＝ay×t2；
vertical n＝az×t2；
the sampling method comprises the steps that n represents sampling times in a preset period, n is preset period duration/preset sampling duration, lateraln represents x-axis displacement data during nth sampling, longitudinal n represents y-axis displacement data during nth sampling, vertical n represents z-axis displacement data during nth sampling, lateraln-1 represents a displacement data change difference value between nth sampling and an x-axis of (n-1) th sampling, longitudinal n-longitudinal n-1 represents a displacement data change difference value between nth sampling and a y-axis of (n-1) th sampling, and vertical n-vertical n-1 represents a displacement data change difference value between nth sampling and a z-axis of (n-1) th sampling.
5. The road condition detecting method as claimed in claim 3, wherein one implementation process of obtaining the road condition of the road segment covered by the at least one mobile intelligent terminal according to the periodically varying difference of the coordinate points of the at least one mobile intelligent terminal comprises:
judging whether the periodic variation difference values of the coordinate points of the one or more mobile intelligent terminals are all smaller than a preset threshold value;
if yes, judging the road condition of the corresponding road section to be flat;
otherwise, judging the road condition of the corresponding road section as bumpiness.
6. A road condition detecting system, comprising:
the mobile intelligent terminal sends sensor real-time data of the mobile intelligent terminal to the vehicle machine;
the vehicle machine is in communication connection with at least one mobile intelligent terminal and receives sensor real-time data of the mobile intelligent terminal; calculating a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the real-time data of the sensor of the mobile intelligent terminal; obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal; and displaying the road surface condition on the display module.
7. The traffic condition detecting system according to claim 6, wherein the vehicle machine calculates a periodic variation difference of the coordinate points of the mobile intelligent terminal according to an implementation process of the vehicle machine including:
setting a periodic variation difference value of a coordinate point in a preset period of a mobile intelligent terminal as { x, y, z }, wherein components of the acceleration data in an x axis, a y axis and a z axis are respectively ax、ay、azPresetting the sampling time as t;
x＝((lateral 2-lateral 1)+(lateral 3-lateral 2)+...(lateral n-lateral n-1))/n；y＝((longitudinal 2-longitudinal 1)+(longitudinal 3-longitudinal 2)+...(longitudinal n-longitudinal n-1))/n；
z＝((vertical 2-vertical 1)+(vertical 3-vertical 2)+...(vertical n-vertical n-1))/n；
lateral n＝ax×t2；
longitudinal n＝ay×t2；
vertical n＝az×t2；
the sampling method comprises the steps that n represents sampling times in a preset period, n is preset period duration/preset sampling duration, lateraln represents x-axis displacement data during nth sampling, longitudinal n represents y-axis displacement data during nth sampling, vertical n represents z-axis displacement data during nth sampling, lateraln-1 represents a displacement data change difference value between nth sampling and an x-axis of (n-1) th sampling, longitudinal n-longitudinal n-1 represents a displacement data change difference value between nth sampling and a y-axis of (n-1) th sampling, and vertical n-vertical n-1 represents a displacement data change difference value between nth sampling and a z-axis of (n-1) th sampling.
8. The system according to claim 6, wherein the obtaining the road condition of the road segment covered by the at least one mobile intelligent terminal according to the periodic variation difference of the coordinate points of the at least one mobile intelligent terminal comprises:
judging whether the periodic variation difference values of the coordinate points of the one or more mobile intelligent terminals are all smaller than a preset threshold value;
if yes, judging the road condition of the corresponding road section to be flat;
otherwise, judging the road condition of the corresponding road section as bumpiness.
9. A storage medium, characterized by: the storage medium stores a computer program; the computer program, when being invoked by a processor, executes the road condition detection method according to any one of claims 1 to 4.
10. The utility model provides a car machine, links to each other with an at least mobile intelligent terminal communication, its characterized in that, the car machine includes:
the communication module is used for receiving the real-time data of the sensor of the mobile intelligent terminal;
the processor is in communication connection with the communication module and calculates the periodic variation difference value of the coordinate point of the mobile intelligent terminal according to the real-time data of the sensor of the mobile intelligent terminal; and obtaining the road surface condition of the road section covered by the at least one mobile intelligent terminal according to the periodic variation difference value of the coordinate point of the at least one mobile intelligent terminal.
And the display module is in communication connection with the processor and displays the road surface condition.
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Cited By (3)
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| CN111619543A (en) * | 2020-06-09 | 2020-09-04 | 三一重机有限公司 | Travel control method and travel control system for wheel excavator, and wheel excavator |
| CN117349677A (en) * | 2023-12-05 | 2024-01-05 | 腾讯科技（深圳）有限公司 | Training method, device, equipment, medium and program product of pavement recognition model |
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| CN111627237A (en) * | 2020-05-21 | 2020-09-04 | 北京骑胜科技有限公司 | Road condition detection method, road condition detection device, server and computer readable storage medium |
| CN111627237B (en) * | 2020-05-21 | 2022-12-09 | 北京骑胜科技有限公司 | Road condition detection method, device, server and computer readable storage medium |
| CN111619543A (en) * | 2020-06-09 | 2020-09-04 | 三一重机有限公司 | Travel control method and travel control system for wheel excavator, and wheel excavator |
| CN117349677A (en) * | 2023-12-05 | 2024-01-05 | 腾讯科技（深圳）有限公司 | Training method, device, equipment, medium and program product of pavement recognition model |
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