CN115331430B - Intelligent network-connected vehicle road spectrum acquisition and analysis method and system - Google Patents
Intelligent network-connected vehicle road spectrum acquisition and analysis method and system Download PDFInfo
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
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- G08G1/0125—Traffic data processing
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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Abstract
The invention discloses a method and a system for collecting and analyzing a road spectrum of an intelligent network coupling vehicle, wherein the method comprises the following steps: acquiring road condition information, wherein the road condition information comprises longitude, latitude, direction angle, altitude and driving mileage; determining an acquisition track according to the longitude, latitude and direction angle, and correcting the acquisition track to obtain an actual track coordinate; obtaining a gradient situation according to the actual track coordinates, and merging adjacent coordinates with the same gradient situation to obtain an ascending track, a flat road track and a descending track; and obtaining the gradient of each track according to the altitude difference, and obtaining the duty ratio of each track according to the driving mileage. The road condition information is collected in real time, and the processing such as filtering, processing and analyzing is carried out, so that the problem that the traditional road spectrum collection is difficult is solved.
Description
Technical Field
The invention relates to the technical field of road spectrum acquisition and analysis, in particular to an intelligent network-connected vehicle road spectrum acquisition and analysis method and system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Because the road quality levels of all the levels in all the areas are uneven, the requirements on the dynamic property and durability of the vehicle are different, the vehicle is required to be designed and developed in a targeted manner, road spectrum data plays a vital role in the test development and verification of the whole vehicle, and the test period can be shortened. Only if accurate road spectrum data is obtained, vehicle design developers can design and develop vehicles in a targeted manner, so that an optimal dynamic scheme is achieved, vehicle energy consumption is reduced, and vehicle life is prolonged.
The traditional road spectrum collection needs to be carried by means of professional collection equipment, the professional equipment is heavy and inconvenient to carry, meanwhile, requirements on collection personnel are high, professional equipment operation capability is required, the collection period is long, analysis data are slow, and the like, so that the research and development requirements cannot be met.
Disclosure of Invention
In order to solve the problems, the invention provides an intelligent network vehicle-connected road spectrum acquisition and analysis method and system, which are used for acquiring road condition information in real time and processing such as filtering, processing and analyzing, so as to solve the problem of difficult acquisition of the traditional road spectrum.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
in a first aspect, the present invention provides a method for collecting and analyzing a road spectrum of an intelligent network, including:
acquiring road condition information, wherein the road condition information comprises longitude, latitude, direction angle, altitude and driving mileage;
determining an acquisition track according to the longitude, latitude and direction angle, and correcting the acquisition track to obtain an actual track coordinate;
obtaining a gradient situation according to the actual track coordinates, and merging adjacent coordinates with the same gradient situation to obtain an ascending track, a flat road track and a descending track;
and obtaining the gradient of each track according to the altitude difference, and obtaining the duty ratio of each track according to the driving mileage.
In an alternative embodiment, the process of correcting the acquired track includes: acquiring a coordinate set of a starting point and a terminal point in an acquisition track; calculating the distance between the coordinate point to be judged and the adjacent coordinate point; and carrying out abnormal judgment on the coordinate points according to the theoretical maximum distance, and if the theoretical maximum distance is exceeded, judging that the coordinate points are abnormal.
As an alternative implementation manner, the road condition information further comprises a running speed and a collection time; and obtaining a theoretical maximum distance according to the acquisition time of the coordinate points to be judged and the corresponding running speed.
Alternatively, the process of obtaining the gradient situation according to the actual track coordinates includes: calculating the distance difference value of the adjacent coordinate points in the horizontal direction, and if the distance difference value is greater than zero, determining an ascending situation; if the distance difference is smaller than zero, the situation is a downhill situation; and if the distance difference value is equal to zero, the road situation is a flat road situation.
As an alternative embodiment, correcting the altitude includes: and estimating the elevation estimated value of the current moment according to the elevation estimated value of the previous moment, and correcting the elevation estimated value of the current moment according to the elevation measured value of the current moment to obtain the actual elevation value of the current moment.
As an alternative embodiment, the altitude difference is obtained according to the corrected altitude, and the gradient is obtained according to the altitude difference for each track; slope= (altitude difference/horizontal distance) 100%.
As an alternative implementation mode, the duty ratio of each track is obtained according to the total mileage and the total driving mileage of each track; and obtaining a gradient range according to the gradient maximum value in the uphill situation and the gradient maximum value in the downhill situation.
In a second aspect, the present invention provides an intelligent network-coupled vehicle road spectrum collection and analysis system, including:
the data acquisition module is configured to acquire road condition information, wherein the road condition information comprises longitude, latitude, direction angle, altitude and driving mileage;
the track deviation correcting module is configured to determine an acquisition track according to longitude, latitude and direction angles, and correct the acquisition track to obtain an actual track coordinate;
the slope situation determining module is configured to obtain a slope situation according to the actual track coordinates, and obtain an ascending track, a flat road track and a descending track after combining adjacent coordinates with the same slope situation;
and the gradient data statistics module is configured to obtain the gradient of each track according to the altitude difference and obtain the duty ratio of each track according to the driving mileage.
In a third aspect, the invention provides an electronic device comprising a memory and a processor and computer instructions stored on the memory and running on the processor, which when executed by the processor, perform the method of the first aspect.
In a fourth aspect, the present invention provides a computer readable storage medium storing computer instructions which, when executed by a processor, perform the method of the first aspect.
Compared with the prior art, the invention has the beneficial effects that:
the intelligent network vehicle-connected road spectrum acquisition and analysis method and system provided by the invention can adopt the intelligent mobile phone to acquire road spectrum data, are convenient to carry and are convenient for the operation of acquisition personnel, and do not need to rely on heavy professional acquisition equipment; no special equipment operation capability is required for the acquisition personnel.
According to the intelligent network vehicle-connected road spectrum acquisition and analysis method and system, the road spectrum data are analyzed and processed, so that the visualized road spectrum report is analyzed, the acquisition cost is lower, the acquisition period is short, the analysis data are fast, the flow is more standard, and the operation is more standard.
Additional aspects 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 accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
Fig. 1 is a flowchart of a method for collecting and analyzing a road spectrum of an intelligent network connected vehicle provided in embodiment 1 of the present invention;
FIG. 2 is a diagram of the filtering result provided in embodiment 1 of the present invention;
FIG. 3 is a graph of correction of abnormal data according to embodiment 1 of the present invention;
fig. 4 is a schematic diagram of different road condition distribution provided in embodiment 1 of the present invention.
Detailed Description
The invention is further described below with reference to the drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular forms also are intended to include the plural forms, and furthermore, it is to be understood that the terms "comprises" and "comprising" and any variations thereof are intended to cover non-exclusive inclusions, such as, for example, processes, methods, systems, products or devices that comprise a series of steps or units, are not necessarily limited to those steps or units that are expressly listed, but may include other steps or units that are not expressly listed or inherent to such processes, methods, products or devices.
Embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Example 1
The embodiment provides an intelligent network vehicle-connected road spectrum acquisition and analysis method, which solves the problem of difficult acquisition of the traditional road spectrum, acquires road condition information in real time, and uploads the acquired road condition information to a road spectrum analysis platform for filtering, processing, analyzing, processing and the like.
As shown in fig. 1, the method specifically includes:
acquiring road condition information, wherein the road condition information comprises longitude, latitude, direction angle, running speed, altitude, acquisition time and running mileage;
determining an acquisition track according to the longitude, latitude and direction angle, and correcting the acquisition track to obtain an actual track coordinate;
obtaining a gradient situation according to the actual track coordinates, and merging adjacent coordinates with the same gradient situation to obtain an ascending track, a flat road track and a descending track;
and obtaining the gradient of each track according to the altitude difference, and obtaining the duty ratio of each track according to the driving mileage.
In this embodiment, road condition information is collected at intervals of T seconds and uploaded to a road spectrum analysis platform.
As an alternative implementation mode, the intelligent mobile phone is used for collecting road condition information in real time, so that the operation of a collector is facilitated, and heavy professional equipment is not needed.
Furthermore, the smart phone should be fixed in the middle of the front end of the vehicle, and the vehicle should be kept to travel at a constant speed as much as possible.
In this embodiment, when the coordinate point is acquired by the GPS, since the coordinate point is abnormal due to the instability of the GPS signal, etc., it is necessary to perform the abnormal point processing to correct the trajectory.
Specifically, according to longitude, latitude and direction angle, determining an acquisition track, correcting the acquisition track to correct the deviation to an actual road, and obtaining actual track coordinates of the actual road;
specifically, setting a starting point and an end point for an acquisition track, and acquiring a coordinate set of the acquisition track between the starting point and the end point;
calculating the Distance between the coordinate point to be judged and the adjacent coordinate point;
obtaining a theoretical maximum distance MaxDistance according to the acquisition time T of the coordinate point to be judged and the corresponding running speed; wherein maxdistance=t×s;
and judging the coordinate point abnormality according to the theoretical maximum Distance, and removing the coordinate point if the Distance is greater than the MaxDistance, which indicates that the coordinate point to be judged is abnormal.
In the embodiment, after the track is rectified, adopting a Kalman filtering algorithm to correct the altitude data and correct the erroneous altitude data; as shown in fig. 2;
specifically, the predicted altitude is: x (k) =ax (k-1) +bv (k) +w (k);
wherein X (k) is the elevation estimation value of the current k moment, and X (k-1) is the elevation estimation value of the last moment (k-1 moment); a is a state transition matrix, B is a control input matrix, and W (k) is process noise.
Estimating an elevation estimated value of the current moment according to an elevation estimated value of the previous moment, and correcting the elevation estimated value of the current moment according to an elevation measured value of the current moment to obtain an actual elevation value of the current moment;
Z(k)＝H X(k)+V(k)
wherein Z (k) is an altitude actual value, H is a state observation matrix, and V (k) is measurement noise.
In the embodiment, judging a gradient situation according to the actual track coordinates;
specifically, adjacent coordinate points C (x) and C (x+1) in an actual track are obtained, D=C (x) -C (x+1) is calculated, and if D >0, an uphill situation is obtained; if D <0, the system is in a downhill situation; if d=0, then it is a flat road situation;
and merging adjacent coordinates with the same gradient situation to obtain an ascending track, a flat road track and a descending track.
Specifically, setting a threshold value of the horizontal distance between the head and the tail of each track, if the threshold value is exceeded, determining that the track is effective in gradient, otherwise, continuing to merge the data; and obtaining the longitude and latitude data of final uphill, flat road and downhill situations.
In the embodiment, the altitude difference is obtained according to the corrected altitude, and the gradient is obtained for each track according to the altitude difference;
wherein, gradient= (elevation difference/horizontal distance) 100%.
In this embodiment, if the gradient is greater than the maximum gradient P of each road, determining as an abnormal data point, and filtering the gradient; as shown in fig. 3.
In this embodiment, according to the relationship between the travel distance and the gradient, statistical information such as the duty ratio of the ascending track, the flat road track, and the descending track, the gradient range, and the fastest vehicle speed is calculated.
Specifically, as shown in fig. 4;
uphill duty cycle: (total mileage on uphill/total mileage) ×100%;
flat road duty cycle: (road total mileage/total mileage) ×100%;
downhill duty cycle: (downhill total mileage/total mileage) ×100%;
gradient range: (gradient maximum in uphill situation-gradient maximum in downhill situation);
the fastest vehicle speed: maximum of the travel speeds.
Example 2
The embodiment provides an intelligent network vehicle-connected road spectrum acquisition and analysis system, which comprises the following steps:
the data acquisition module is configured to acquire road condition information, wherein the road condition information comprises longitude, latitude, direction angle, altitude and driving mileage;
the track deviation correcting module is configured to determine an acquisition track according to longitude, latitude and direction angles, and correct the acquisition track to obtain an actual track coordinate;
the slope situation determining module is configured to obtain a slope situation according to the actual track coordinates, and obtain an ascending track, a flat road track and a descending track after combining adjacent coordinates with the same slope situation;
and the gradient data statistics module is configured to obtain the gradient of each track according to the altitude difference and obtain the duty ratio of each track according to the driving mileage.
It should be noted that the above modules correspond to the steps described in embodiment 1, and the above modules are the same as examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in embodiment 1. It should be noted that the modules described above may be implemented as part of a system in a computer system, such as a set of computer-executable instructions.
In further embodiments, there is also provided:
an electronic device comprising a memory and a processor and computer instructions stored on the memory and running on the processor, which when executed by the processor, perform the method described in embodiment 1. For brevity, the description is omitted here.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic device, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include read only memory and random access memory and provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store information of the device type.
A computer readable storage medium storing computer instructions which, when executed by a processor, perform the method described in embodiment 1.
The method in embodiment 1 may be directly embodied as a hardware processor executing or executed with a combination of hardware and software modules in the processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method. To avoid repetition, a detailed description is not provided herein.
Those of ordinary skill in the art will appreciate that the elements of the various examples described in connection with the present embodiments, i.e., the algorithm steps, can be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
While the foregoing description of the embodiments of the present invention has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the invention, but rather, it is intended to cover all modifications or variations within the scope of the invention as defined by the claims of the present invention.
Claims (5)
1. The intelligent network-connected vehicle road spectrum acquisition and analysis method is characterized by comprising the following steps of:
acquiring road condition information, wherein the road condition information comprises longitude, latitude, direction angle, altitude and driving mileage;
the road condition information also comprises running speed and acquisition time; obtaining a theoretical maximum distance according to the acquisition time of the coordinate points to be judged and the corresponding running speed;
determining an acquisition track according to the longitude, latitude and direction angle, and correcting the acquisition track to obtain an actual track coordinate;
obtaining a gradient situation according to actual track coordinates, merging adjacent coordinates with the same gradient situation to obtain an ascending track, a flat road track and a descending track, specifically setting a threshold value of a horizontal distance between the head and the tail of each track, if the threshold value is exceeded, determining an effective gradient, otherwise, continuing merging data to obtain longitude and latitude data of the final ascending, flat road and descending situation;
obtaining the gradient of each track according to the altitude difference, and obtaining the duty ratio of each track according to the driving mileage;
the process for obtaining the gradient situation according to the actual track coordinates comprises the following steps: calculating the distance difference value of the adjacent coordinate points in the horizontal direction, and if the distance difference value is greater than zero, determining an ascending situation; if the distance difference is smaller than zero, the situation is a downhill situation; if the distance difference is equal to zero, the road situation is a flat road situation;
the method for correcting the altitude by adopting the Kalman filtering algorithm comprises the following steps: estimating an elevation estimated value of the current moment according to an elevation estimated value of the previous moment, and correcting the elevation estimated value of the current moment according to an elevation measured value of the current moment to obtain an actual elevation value of the current moment;
obtaining altitude difference according to the corrected altitude, and obtaining gradient according to the altitude difference for each track;
obtaining the duty ratio of each track according to the total mileage and the total driving mileage of each track;
and obtaining a gradient range according to the gradient maximum value in the uphill situation and the gradient maximum value in the downhill situation.
2. The intelligent network-coupled vehicle spectrum acquisition and analysis method as set forth in claim 1, wherein the process of correcting the acquisition track comprises: acquiring a coordinate set of a starting point and a terminal point in an acquisition track; calculating the distance between the coordinate point to be judged and the adjacent coordinate point; and carrying out abnormal judgment on the coordinate points according to the theoretical maximum distance, and if the theoretical maximum distance is exceeded, judging that the coordinate points are abnormal.
3. An intelligent network-coupled vehicle spectrum acquisition and analysis system for implementing the method according to any one of claims 1-2, comprising:
the data acquisition module is configured to acquire road condition information, wherein the road condition information comprises longitude, latitude, direction angle, altitude and driving mileage;
the track deviation correcting module is configured to determine an acquisition track according to longitude, latitude and direction angles, and correct the acquisition track to obtain an actual track coordinate;
the slope situation determining module is configured to obtain a slope situation according to actual track coordinates, obtain an ascending track, a flat road track and a descending track after combining adjacent coordinates with the same slope situation, specifically set a threshold value of a horizontal distance between the head and the tail of each track, and identify the effective slope if the threshold value is exceeded, and otherwise, continue to combine data to obtain longitude and latitude data of the final ascending track, flat road and descending track;
and the gradient data statistics module is configured to obtain the gradient of each track according to the altitude difference and obtain the duty ratio of each track according to the driving mileage.
4. An electronic device comprising a memory and a processor and computer instructions stored on the memory and running on the processor, which when executed by the processor, perform the method of any of claims 1-2.
5. A computer readable storage medium storing computer instructions which, when executed by a processor, perform the method of any of claims 1-2.
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| CN116450705B (en) * | 2023-04-04 | 2023-12-29 | 瑞修得信息科技(无锡)有限公司 | Method and system for identifying ascending and descending slopes based on vehicle-mounted data acquisition equipment |
| CN116578891B (en) * | 2023-07-14 | 2023-10-03 | 天津所托瑞安汽车科技有限公司 | Road information reconstruction method, terminal and storage medium |
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