CN110636468B - 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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- CN110636468B CN110636468B CN201810649817.XA CN201810649817A CN110636468B CN 110636468 B CN110636468 B CN 110636468B CN 201810649817 A CN201810649817 A CN 201810649817A CN 110636468 B CN110636468 B CN 110636468B
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- 238000004891 communication Methods 0.000 claims abstract description 24
- 230000001133 acceleration Effects 0.000 claims abstract description 17
- 238000000034 method Methods 0.000 claims abstract description 15
- 238000005070 sampling Methods 0.000 claims description 87
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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
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
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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 includes 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 in the prior art cannot detect road condition information, and the vehicle owner can judge the road condition information only by experience according to the jolt degree. The mobile phones on the vehicle are utilized to monitor road conditions in the running process of the vehicle, and the more the number of the mobile phones are connected, the more the monitored road conditions are true.
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.
Background
In the prior art, the vehicle cannot detect road condition information, the vehicle owner can only judge the road condition information by experience according to the jolt degree, the risk of running on jolt road conditions is high, the vehicle owner is required to adjust the running speed according to the road condition information in time, 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 running safety is not facilitated.
In the prior art, a road surface flatness detection method exists, the method utilizes an accelerator to detect the relative displacement generated by a laser ranging device due to road surface bump, then utilizes a three-way gyroscope to detect the inclined angle of the laser ranging device due to road surface bump, calculates the vertical distance between the laser ranging device and the road surface, obtains each vertical distance according to detection density, obtains the difference value between the vertical distance and a standard reference distance, and obtains the flatness of a vertical section curve and the road surface, but the method needs three high-precision sensors, has a complex structure and is easy to be interfered, needs highly professional personnel to finish road surface detection, greatly increases detection cost, and is not suitable for common vehicles.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the present invention is directed to a road condition detection method, system, storage medium and vehicle machine, which are used for solving the problems that in the prior art, a vehicle cannot detect road condition information, a vehicle owner can only judge road condition information according to jolting degree through experience, the risk of running on jolting road conditions is high, the vehicle owner is required to adjust running speed according to the road condition information in time, and the vehicle owner judges that the road condition information has certain error and hysteresis according to self experience, which is unfavorable for running safety.
To achieve the above and other related objects, the present invention provides a road condition detection 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 includes 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 one embodiment of the invention, the communication link comprises: bluetooth connection, or/and AP hotspot connection.
In an embodiment of the invention, the acceleration data includes: acceleration component a in x-axis, y-axis, z-axis directions x 、a y 、a z 。
In an embodiment of the present invention, the computing mobile intelligent terminal sitsOne implementation of the periodically varying difference values for punctuation includes: setting the periodic variation difference value of coordinate points in a preset period of a mobile intelligent terminal as { x, y, z }, wherein the components of the acceleration data in the x axis, the y axis and the z axis are respectively a x 、a y 、a z Presetting the sampling time length as t; x= ((laboratory 2-laboratory 1) + (laboratory 3-laboratory 2) + to (laboratory n-1))/n; y= ((longitudinal 2-longitudinal 1) + (longitudinal 3-longitudinal 2) + i.e. (longitudinal n-longitudinal n-1))/n; z= ((vertical 2-vertical 1) + (vertical 3-vertical 2) + to (vertical n-vertical n-1))/n; labal n=a x ×t 2 ；longitudinal n＝a y ×t 2 ；vertical n＝a z ×t 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein n represents the sampling times in a preset period, n=preset period duration/preset sampling duration, laser n represents x-axis displacement data at the time of n-th sampling, longitudinal n represents y-axis displacement data at the time of n-th sampling, vertical n represents z-axis displacement data at the time of n-th sampling, laser n-laser-1 represents displacement data change difference values of x-axis of n-th sampling and n-1-th sampling, longitudinal n-longitudinal n-1 represents displacement data change difference values of y-axis of n-th sampling and n-1-th sampling, and vertical n-vertical n-1 represents displacement data change difference values of z-axis of n-th sampling and n-1-th sampling.
In an embodiment of the present invention, the 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 includes: judging whether the periodical change difference values of the coordinate points of the one or more mobile intelligent terminals are smaller than a preset threshold value; if yes, judging that the road condition of the corresponding road section is flat; otherwise, judging that the road condition of the corresponding road section is bumpy.
To achieve the above and other related objects, the present invention provides a road condition detection system, comprising: at least one mobile intelligent terminal, which sends real-time data of a sensor of the mobile intelligent terminal to the car 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 sensor real-time data 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; the road surface condition is displayed on the display module.
In an embodiment of the present invention, an implementation process of calculating a periodic variation difference value of a coordinate point of a mobile intelligent terminal by the vehicle comprises: setting the periodic variation difference value of coordinate points in a preset period of a mobile intelligent terminal as { x, y, z }, wherein the components of the acceleration data in the x axis, the y axis and the z axis are respectively a x 、a y 、a z Presetting the sampling time length as t; x= ((laboratory 2-laboratory 1) + (laboratory 3-laboratory 2) + to (laboratory n-1))/n; y= ((longitudinal 2-longitudinal 1) + (longitudinal 3-longitudinal 2) + i.e. (longitudinal n-longitudinal n-1))/n; z= ((vertical 2-vertical 1) + (vertical 3-vertical 2) + to (vertical n-vertical n-1))/n; labal n=a x ×t 2 ；longitudinal n＝a y ×t 2 ；vertical n＝a z ×t 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein n represents the sampling times in a preset period, n=preset period duration/preset sampling duration, laser n represents x-axis displacement data at the time of n-th sampling, longitudinal n represents y-axis displacement data at the time of n-th sampling, vertical n represents z-axis displacement data at the time of n-th sampling, laser n-laser-1 represents displacement data change difference values of x-axis of n-th sampling and n-1-th sampling, longitudinal n-longitudinal n-1 represents displacement data change difference values of y-axis of n-th sampling and n-1-th sampling, and vertical n-vertical n-1 represents displacement data change difference values of z-axis of n-th sampling and n-1-th sampling.
In an embodiment of the present invention, the vehicle obtains 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, which includes: the vehicle machine judges whether the periodical change difference values of the coordinate points of the one or more mobile intelligent terminals are smaller than a preset threshold value; if yes, judging that the road condition of the corresponding road section is flat; otherwise, judging that the road condition of the corresponding road section is bumpy.
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 when invoked by the processor performs the road condition detection method according to the invention.
To achieve the above and other related objects, the present invention also provides a vehicle, which is communicatively connected to at least one mobile intelligent terminal, and is characterized in that the vehicle includes: the communication module is used for receiving real-time data of a sensor of the mobile intelligent terminal; the processor 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. 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 machine of the invention have the following beneficial effects: the invention solves the problems that in the prior art, the vehicle cannot detect road condition information, the vehicle owner can only judge the road condition information by virtue of experience according to the jolt degree, the risk of running on the jolt road condition is high, the vehicle owner is required to adjust the running speed according to the road condition information in time, and the vehicle owner judges the road condition information to have certain error and hysteresis according to the experience of the vehicle owner, so that the running safety is not facilitated. The mobile phones on the vehicle are creatively utilized to realize the monitoring of road conditions in the running process of the vehicle, and the more the number of the mobile phones are connected, the more the monitored road conditions are true.
Drawings
Fig. 1 is a schematic flow chart of an implementation of a road condition detection method according to an embodiment of the invention.
Fig. 2 is a schematic diagram of an implementation flow of determining a road surface condition according to a periodic variation difference of a coordinate point of a mobile intelligent terminal according to an embodiment of the present invention.
Fig. 3A is a schematic structural diagram of a road condition detection system according to an embodiment of the invention.
Fig. 3B is a schematic structural diagram of a vehicle according to an embodiment of the invention.
Fig. 4 is a schematic diagram illustrating calculation of a periodic variation difference of a coordinate point of a mobile intelligent terminal according to an embodiment of the present invention.
Description of element reference numerals
300. Road condition detecting system
310. Mobile intelligent terminal
320. Car machine
321. Communication module
322. Processor and method for controlling the same
323. Display module
S101-S104 steps
S201 to S204 steps
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present invention by way of illustration, and only the components related to the present invention are shown in the illustrations, not according to the number, shape and size of the components in actual implementation, and the form, number and proportion of each component in actual implementation may be arbitrarily changed, and the layout of the components may be more complex.
Referring to fig. 1, an embodiment of the present invention provides a road condition detection method, which includes:
s101, the vehicle is in communication connection with at least one mobile intelligent terminal. Specifically, the communication connection includes: bluetooth connection, or/and AP hotspot connection.
S102, receiving sensor real-time data sent by a mobile intelligent terminal; the real-time data includes acceleration data. Specifically, the acceleration data includes: acceleration component a in x-axis, y-axis, z-axis directions x 、a y 、a z 。
And S103, calculating the periodic variation difference value of the coordinate point of the mobile intelligent terminal according to the real-time data.
And S104, 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, a process for calculating the periodic variation difference of the coordinate point of the mobile intelligent terminal in step S103 includes:
setting the periodic variation difference value of coordinate points in a preset period of a mobile intelligent terminal as { x, y, z }, wherein the components of the acceleration data in the x axis, the y axis and the z axis are respectively a x 、a y 、a z Presetting the 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＝a x ×t 2 ；longitudinal n＝a y ×t 2 ；vertical n＝a z ×t 2 ；
wherein n represents the sampling times in a preset period, n=preset period duration/preset sampling duration, laser n represents x-axis displacement data at the time of n-th sampling, longitudinal n represents y-axis displacement data at the time of n-th sampling, vertical n represents z-axis displacement data at the time of n-th sampling, laser n-laser-1 represents displacement data change difference values of x-axis of n-th sampling and n-1-th sampling, longitudinal n-longitudinal n-1 represents displacement data change difference values of y-axis of n-th sampling and n-1-th sampling, and vertical n-vertical n-1 represents displacement data change difference values of z-axis of n-th sampling and n-1-th sampling.
Referring to fig. 2, an implementation process of obtaining a road condition of a road section covered by the at least one mobile intelligent terminal according to a periodic variation difference value of coordinate points 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.
S202, judging whether the periodical change difference values of the coordinate points of the one or more mobile intelligent terminals are smaller than a preset threshold value. Specifically, the preset threshold may be { x1, y1, z1}, and when x < x1, y < y1, 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 that the road condition of the corresponding road section is flat.
S204, if not, judging that the road condition of the corresponding road section is 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 the present embodiment, and all the schemes implemented by the steps of increasing or decreasing and step replacing in the prior art according to the principles 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 device for realizing the road condition detection method of the invention comprises but is not limited to the structure of the road condition detection system listed in the embodiment, and all structural modifications and substitutions of the prior art according to the principles 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 detection system, where the road condition detection system 300 includes: at least one mobile intelligent terminal 310, a vehicle machine 320.
The mobile intelligent terminal 310 transmits sensor real-time data of the mobile intelligent terminal to the car 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 sensor real-time data 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; the road surface condition is displayed on the display module.
In an embodiment of the present invention, an implementation process of calculating a periodic variation difference value of a coordinate point of a mobile intelligent terminal by the vehicle comprises:
setting the periodic variation difference value of coordinate points in a preset period of a mobile intelligent terminal as { x, y, z }, wherein the components of the acceleration data in the x axis, the y axis and the z axis are respectively a x 、a y 、a z Presetting the 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＝a x ×t 2 ；longitudinal n＝a y ×t 2 ；vertical n＝a z ×t 2 ；
wherein n represents the sampling times in a preset period, n=preset period duration/preset sampling duration, laser n represents x-axis displacement data at the time of n-th sampling, longitudinal n represents y-axis displacement data at the time of n-th sampling, vertical n represents z-axis displacement data at the time of n-th sampling, laser n-laser-1 represents displacement data change difference values of x-axis of n-th sampling and n-1-th sampling, longitudinal n-longitudinal n-1 represents displacement data change difference values of y-axis of n-th sampling and n-1-th sampling, and vertical n-vertical n-1 represents displacement data change difference values of z-axis of n-th sampling and n-1-th sampling.
In an embodiment of the present invention, the vehicle machine obtains a road surface condition of a road section covered by the at least one mobile intelligent terminal according to a periodic variation difference value of a coordinate point of the at least one mobile intelligent terminal, which includes: judging whether the periodical change difference values of the coordinate points of the one or more mobile intelligent terminals are smaller than a preset threshold value; if yes, judging that the road condition of the corresponding road section is flat; otherwise, judging that the road condition of the corresponding road section is bumpy.
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 when invoked by the processor performs the road condition detection method according to the invention.
Referring to fig. 3B, in order to achieve the above and other related objects, the present invention further provides a vehicle 320 communicatively connected to at least one mobile intelligent terminal, wherein the vehicle includes: a display module 321, a communication module 322, and a processor 323.
The communication module 322 receives sensor real-time data of the mobile intelligent terminal.
The processor 323 communication module is in communication connection, and calculates a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the sensor real-time data 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 surface condition.
Referring to fig. 4, a schematic diagram of calculating a periodic variation difference value of a coordinate point of a mobile intelligent terminal according to an embodiment of the present invention is shown, a numeric value laboratory is shown to represent an x-axis displacement value generated in a sampling period, a numeric value longitudinal is shown to represent a y-axis displacement value generated in the sampling period, and a numeric value vertical is shown to represent a y-axis displacement value generated in the sampling period.
As described above, the road condition detection method and system of the invention have the following beneficial effects: the mobile phones on the vehicle are creatively utilized to realize the monitoring of road conditions in the running process of the vehicle, and the more the number of the mobile phones are connected, the more the monitored road conditions are true.
The invention solves the problems that the vehicle in the prior art cannot detect road condition information, the vehicle owner can only judge the road condition information by virtue of experience according to the jolt degree, the risk of running on the jolt road condition is high, the vehicle owner is required to adjust the running speed according to the road condition information in time, the vehicle owner judges the road condition information according to the experience of the vehicle owner to have certain error and hysteresis, and the running safety is not facilitated, and various defects in the prior art are effectively overcome, so that the invention has high industrial utilization value.
The above embodiments are merely illustrative of the principles of the present invention and its effectiveness, and are not intended to limit the invention. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the invention. Accordingly, it is intended that all equivalent modifications and variations of the invention be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (5)
1. The 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 includes acceleration data;
calculating a periodic variation difference value of a coordinate point of the mobile intelligent terminal according to the real-time data;
judging whether the periodical change difference values of the coordinate points of one or more mobile intelligent terminals are smaller than a preset threshold value or not; if yes, judging that the road condition of the corresponding road section is flat; otherwise, judging that the road condition of the corresponding road section is bumpy;
the implementation process for calculating the periodic variation difference value of the coordinate point of the mobile intelligent terminal comprises the following steps:
setting the periodic variation difference value of coordinate points in a preset period of a mobile intelligent terminal as { x, y, z }, whereThe components of the acceleration data in the x axis, the y axis and the z axis are respectively a x 、a y 、a z Presetting the 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=a x ×t 2 ；
longitudinal n= a y ×t 2 ；
vertical n= a z ×t 2 ；
wherein n represents the sampling times in a preset period, n=preset period duration/preset sampling duration, laser n represents x-axis displacement data at the time of n-th sampling, longitudinal n represents y-axis displacement data at the time of n-th sampling, vertical n represents z-axis displacement data at the time of n-th sampling, laser n-laser-1 represents displacement data change difference values of x-axis of n-th sampling and n-1-th sampling, longitudinal n-longitudinal n-1 represents displacement data change difference values of y-axis of n-th sampling and n-1-th sampling, and vertical n-vertical n-1 represents displacement data change difference values of z-axis of n-th sampling and n-1-th sampling.
2. The road condition detection method as set forth in claim 1, wherein the communication connection comprises: bluetooth connection, or/and AP hotspot connection.
3. A road condition detection system, characterized in that the road condition detection system comprises:
the mobile intelligent terminal sends real-time data of a sensor of the mobile intelligent terminal to the vehicle machine; the real-time data includes acceleration data;
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 sensor real-time data of the mobile intelligent terminal; judging whether the periodical change difference values of the coordinate points of one or more mobile intelligent terminals are smaller than a preset threshold value or not; if yes, judging that the road condition of the corresponding road section is flat; otherwise, judging that the road condition of the corresponding road section is bumpy; displaying the road surface condition on the display module;
the implementation process of calculating the periodic variation difference value of the coordinate point of the mobile intelligent terminal by the vehicle comprises the following steps:
setting the periodic variation difference value of coordinate points in a preset period of a mobile intelligent terminal as { x, y, z }, wherein the components of the acceleration data in the x axis, the y axis and the z axis are respectively a x 、a y 、a z Presetting the 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=a x ×t 2 ；
longitudinal n= a y ×t 2 ；
vertical n= a z ×t 2 ；
wherein n represents the sampling times in a preset period, n=preset period duration/preset sampling duration, laser n represents x-axis displacement data at the time of n-th sampling, longitudinal n represents y-axis displacement data at the time of n-th sampling, vertical n represents z-axis displacement data at the time of n-th sampling, laser n-laser-1 represents displacement data change difference values of x-axis of n-th sampling and n-1-th sampling, longitudinal n-longitudinal n-1 represents displacement data change difference values of y-axis of n-th sampling and n-1-th sampling, and vertical n-vertical n-1 represents displacement data change difference values of z-axis of n-th sampling and n-1-th sampling.
4. A storage medium, characterized by: the storage medium stores a computer program; a computer program when invoked by a processor performs a road condition detection method as claimed in any one of claims 1 to 2.
5. A vehicle in communication with at least one mobile intelligent terminal, the vehicle comprising:
the communication module is used for receiving real-time data of a sensor of the mobile intelligent terminal; the real-time data includes acceleration data;
the processor 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; judging whether the periodical change difference values of the coordinate points of one or more mobile intelligent terminals are smaller than a preset threshold value or not; if yes, judging that the road condition of the corresponding road section is flat; otherwise, judging that the road condition of the corresponding road section is bumpy;
the display module is in communication connection with the processor and displays the road surface condition;
the implementation process for calculating the periodic variation difference value of the coordinate point of the mobile intelligent terminal comprises the following steps:
setting the periodic variation difference value of coordinate points in a preset period of a mobile intelligent terminal as { x, y, z }, wherein the components of the acceleration data in the x axis, the y axis and the z axis are respectively a x 、a y 、a z Presetting the 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=a x ×t 2 ；
longitudinal n= a y ×t 2 ；
vertical n= a z ×t 2 ；
wherein n represents the sampling times in a preset period, n=preset period duration/preset sampling duration, laser n represents x-axis displacement data at the time of n-th sampling, longitudinal n represents y-axis displacement data at the time of n-th sampling, vertical n represents z-axis displacement data at the time of n-th sampling, laser n-laser-1 represents displacement data change difference values of x-axis of n-th sampling and n-1-th sampling, longitudinal n-longitudinal n-1 represents displacement data change difference values of y-axis of n-th sampling and n-1-th sampling, and vertical n-vertical n-1 represents displacement data change difference values of z-axis of n-th sampling and n-1-th sampling.
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