CN114485560A - Road slope rapid detection method for off-highway tourist and sightseeing vehicle - Google Patents

Road slope rapid detection method for off-highway tourist and sightseeing vehicle Download PDF

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CN114485560A
CN114485560A CN202111581847.XA CN202111581847A CN114485560A CN 114485560 A CN114485560 A CN 114485560A CN 202111581847 A CN202111581847 A CN 202111581847A CN 114485560 A CN114485560 A CN 114485560A
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gradient
slope
route
sightseeing
curve
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余焕伟
唐艳同
陈仙凤
陈松
宋剑华
林仁波
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SHAOXING SPECIAL EQUIPMENT TESTING INSTITUTE
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C9/00—Measuring inclination, e.g. by clinometers, by levels
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/04—Interpretation of pictures
    • G01C11/30—Interpretation of pictures by triangulation
    • G01C11/34—Aerial triangulation

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Abstract

A road gradient rapid detection method for an off-highway tourist and sightseeing vehicle belongs to the technical field of special equipment detection. The invention utilizes the oblique photography technology of the unmanned aerial vehicle to shoot the ground image of the driving route of the sightseeing vehicle, carries out three-dimensional modeling on the ground image, extracts coordinates on the three-dimensional model to generate a slope-slope length curve of the sightseeing vehicle, and can quickly detect the slope of the driving route of the sightseeing vehicle by optimizing the slope-slope length curve.

Description

Road gradient rapid detection method for off-highway tourism vehicle
Technical Field
The invention belongs to the technical field of special equipment inspection and detection, and particularly relates to a method for quickly detecting the road gradient of an off-highway tourist and sightseeing vehicle.
Background
The off-road tourism vehicle (sightseeing vehicle for short) is used as a vehicle running in factories, tourist attractions and amusement parks, is open, has running road conditions and surrounding running environments far lower than national standard roads, and has certain dangers of collision, vehicle sliding, overturning and the like when running on roads with larger slopes. In order to ensure the running safety of the sightseeing vehicle and reduce the accident rate, the TSG N0001-2017 'safety technology supervision regulation for special motor vehicles in the field (factory)' issued by the original State quality supervision, inspection and quarantine Bureau in 2017 stipulates the gradient of the running route of the sightseeing vehicle: the maximum driving gradient of the sightseeing train is not more than 10% (except for short slopes with the slope length less than 20m), and the maximum driving gradient of the sightseeing train is not more than 4% (except for short slopes with the slope length less than 20 m). According to the requirement, the gradient of the driving route of the sightseeing vehicle is required to be measured when the scenic spot is used for developing and planning the route of the sightseeing vehicle or when a special equipment inspection mechanism is used for inspecting. The total station can be used for accurately measuring the gradient of the route, but the effective distance of single measurement is generally about 20m, the positions of monitoring points of the long-distance route need to be frequently changed for measuring section by section, the task amount is large, and the investment cost is high. For the GPS base station measuring method, base stations also need to be frequently built, and the problem of high investment cost also exists. In order to ensure the driving safety of the tour and sightseeing vehicle and meet the exemption requirement of 'short slope with the slope length less than 20 m' and the relation between the 'local detail slope' and the 'integral average slope' needs to be processed when the slope is measured, thereby further increasing the measurement cost of the traditional method.
Disclosure of Invention
The invention mainly solves the technical problems in the prior art and provides a method for quickly detecting the road gradient of an off-highway tourist and sightseeing vehicle.
The technical problem of the invention is mainly solved by the following technical scheme: a road gradient rapid detection method of an off-highway tourist and sightseeing vehicle comprises the following steps:
step 1, shooting a ground image of a sightseeing bus route by adopting an oblique photography technology based on an unmanned aerial vehicle platform;
step 2, performing three-dimensional modeling on the shot ground image of the sightseeing bus route;
step 3, extracting a three-dimensional space coordinate set of ground points along the advancing direction of the sightseeing vehicle route on the three-dimensional model;
step 4, calculating the distance and the elevation difference between two adjacent points according to the three-dimensional space coordinate data to generate a 'gradient-slope length' curve of the sightseeing vehicle;
step 5, performing interpolation fitting on the gradient-slope length curve, expanding the number of ground points and increasing gradient detail data;
step 6, carrying out smooth filtering on the interpolation fitting curve;
and 7, performing sliding average on the interpolation fitting curve after smoothing and filtering to confirm the condition that the slope of the route of the sightseeing bus meets the standard.
Preferably, step 1 specifically comprises the following steps:
step S1, planning the flight route of the unmanned aerial vehicle according to the environment information along the route of the sightseeing vehicle;
step S2, setting flight parameters and photographing parameters of the unmanned aerial vehicle to enable the unmanned aerial vehicle to carry out oblique photography;
and step S3, setting necessary ground control points and standard size models.
Preferably, the step 2 specifically comprises the following steps:
step S1, the shot ground image is subjected to aerial triangulation calculation, and the manufactured markers or natural markers with obvious characteristics can be used as control points;
and step S2, performing three-dimensional model reconstruction on the ground image after the aerial triangulation calculation.
Preferably, in step 5, the interpolation fitting adopts a 'piecewise cubic Hermite interpolation' method.
Preferably, in step 6, the interpolation fitting curve employs sliding median filtering.
Preferably, step 7 specifically comprises the following steps:
step S1, marking the curve of 'gradient-slope length' after smooth filtering as the gradient exceeding threshold GradthThe section S of (1);
step S2, confirming the gradient of the road section S; if the gradient Grad of the road section S is smaller than the gradient threshold GradthIf the road section S meets the requirement, the detection is finished, otherwise, the measurement is continued to exceed the gradient threshold GradthThe slope length of (d);
step S3, on the curve of 'gradient-slope length' after smooth filtering, calculating the sliding average value GradM of the gradient Grad according to the following formula, wherein the width W of the sliding window corresponds to the threshold value L of the slope lengththDrawing an Ln-GradM curve;
Figure BDA0003426337300000031
step S4, if the sliding average GradM is less than the gradient threshold GradthIf so, the route of the sightseeing bus meets the requirement; if at the length of the slope LmThe sliding average value GradM exceeds the gradient threshold GradthThen, it represents a road section [ L ]m-Lth，Lm]The gradient at (b) may exceed the requirement, and the process proceeds to step S5;
and step S5, performing on-site confirmation on the road section with the overproof route.
Preferably, in step S2, the method for confirming the gradient of the link S is: selecting P spaced far from each other on three-dimensional model map of road section S1、P2、P3Three points, P1Elevation h of1And P2Elevation h of2Equal, P1And P2Is L from each other12，P3Is lower than P1And P2，P3Has an elevation of h3，P1、P2And P3The area of the enclosed triangle is S123Calculating P3To P1And P2The vertical distance L of the connecting line is 2S123/L12And the gradient Grad of the road section S is as follows:
Figure BDA0003426337300000032
preferably, in step S2, the road segment S is subjected to slope confirmation by a total station or a gradiometer.
The invention has the following beneficial effects: the invention utilizes the oblique photography technology of the unmanned aerial vehicle to shoot the ground image of the driving route of the sightseeing vehicle, carries out three-dimensional modeling on the ground image, extracts coordinates on the three-dimensional model to generate a slope-slope length curve of the sightseeing vehicle, and can quickly detect the slope of the driving route of the sightseeing vehicle by optimizing the slope-slope length curve.
Drawings
FIG. 1 is a three-dimensional model of a ramp according to the present invention;
FIG. 2 is a sample point plot of a three-dimensional model of a ramp of the present invention;
FIG. 3 is a slope-slope length graph of the present invention;
FIG. 4 is a graph of an interpolation fit of the present invention;
FIG. 5 is a graph of an interpolation fit of the present invention after sliding median filtering;
FIG. 6 is a diagram of a measurement point selected from the upper part of a slope on a three-dimensional model according to the invention;
FIG. 7 is a graph of the slope of the invention after the sliding average process;
fig. 8 is a partial three-dimensional measurement diagram of the present invention on a three-dimensional model.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
A road gradient rapid detection method of an off-highway tourist and sightseeing vehicle comprises the following steps:
step 1, shooting a ground image of a sightseeing bus route by adopting an oblique photography technology based on an unmanned aerial vehicle platform;
step 2, performing three-dimensional modeling on the shot ground image of the sightseeing bus route;
step 3, extracting a three-dimensional space coordinate set of ground points along the advancing direction of the sightseeing bus route on the three-dimensional model;
step 4, calculating the distance and the elevation difference between two adjacent points according to the three-dimensional space coordinate data to generate a 'gradient-slope length' curve of the sightseeing vehicle;
step 5, performing interpolation fitting on the gradient-slope length curve, expanding the number of ground points and increasing gradient detail data; preferably, the interpolation fitting adopts a 'piecewise thrice Hermite interpolation' method;
step 6, performing smooth filtering on the interpolation fitting curve to reduce slope abnormity caused by uneven local micro-area of the sightseeing bus route and jitter of the unmanned aerial vehicle; preferably, the interpolation fitting curve adopts sliding median filtering;
step 7, the gradient threshold value is GradthGrade exceeding GradthHas a road section slope length threshold value of LthAnd performing sliding average on the interpolation fitting curve after the smoothing filtering to confirm the condition that the slope of the route of the sightseeing bus meets the standard.
Wherein, the step 1 specifically comprises the following steps:
step S1, planning the flight route of the unmanned aerial vehicle according to the environment information along the route of the sightseeing vehicle;
step S2, setting flight parameters and photographing parameters of the unmanned aerial vehicle to enable the unmanned aerial vehicle to carry out oblique photography;
and step S3, setting necessary ground control points and standard size models.
Wherein, the step 2 specifically comprises the following steps:
step S1, the shot ground image is subjected to aerial triangulation calculation, and the manufactured markers or natural markers with obvious characteristics can be used as control points;
and step S2, performing three-dimensional model reconstruction on the ground image after the aerial triangulation calculation.
Wherein, the step 7 specifically comprises the following steps:
step S1, marking the curve of 'gradient-slope length' after smooth filtering as the gradient exceeding threshold GradthThe section S of (1);
step S2, confirming the gradient of the road section S; if the gradient Grad of the road section S is smaller than the gradient threshold GradthIf the road section S meets the requirement, the detection is finished, otherwise, the measurement is continued to exceed the gradient threshold GradthThe slope length of (d);
step S3, on the curve of 'gradient-slope length' after smooth filtering, calculating the sliding average value GradM of the gradient Grad according to the following formula, wherein the width W of the sliding window corresponds to the threshold value L of the slope lengththDrawing an Ln-GradM curve;
Figure BDA0003426337300000051
step S4, if the sliding average values GradM are all smaller than the gradient threshold GradthIf so, the route of the sightseeing bus meets the requirement; if at the length of the slope LmThe sliding average value GradM exceeds the gradient threshold GradthThen, it represents a road section [ L ]m-Lth，Lm]The gradient may exceed the requirement, and the process proceeds to step S5;
and step S5, performing on-site confirmation on the road section with the exceeding standard route.
In step S2, the road segment S may be subjected to slope confirmation by an instrument such as a total station or a gradiometer, or may be subjected to slope confirmation by the following method: the method for confirming the S gradient of the road section comprises the following steps: selecting P spaced far from each other on three-dimensional model map of road section S1、P2、P3Three points, P1Elevation h of1And P2Elevation h of2Equal, P1And P2Is L from each other12，P3Is lower than P1And P2，P3Has an elevation of h3，P1、P2And P3The area of the enclosed triangle is S123Calculating P3To P1And P2The vertical distance L of the connecting line is 2S123/L12And the gradient Grad of the road section S is as follows:
Figure BDA0003426337300000052
in step S5, the road section with the exceeding standard route can be confirmed by the total station, or by the gradient confirmation method in step S2.
The embodiment is as follows: the test site is selected at a sightseeing vehicle test base, the ramp consists of an uphill section, a horizontal section and a downhill section, and the nominal gradient is 10%. The Xintom 4RTK unmanned plane is adopted to carry out oblique photography, the flying height of the unmanned plane is set to be 25 meters, the average ground resolution of an image is 6.70mm/pixel, the inclination angle of a lens is 45 degrees, the flying speed is 5m/s, and the transverse overlapping is 80 percent. The unmanned aerial vehicle executes the shooting task according to the preset parameters, a total of 216 images are obtained, and 196 images which can be used for three-dimensional reconstruction are calculated through aerial triangulation. Table 1 shows the statistical results of the position uncertainty of the photographs processed by the aerial triangulation, the average position uncertainty in both X, Y and Z directions did not exceed 3 mm.
TABLE 1
Location uncertainty statistics X direction (m) Y direction (m) Z direction (m)
Minimum value 0.00041 0.00048 0.00051
Mean value of 0.00282 0.00215 0.00204
Maximum value 0.07953 0.07055 0.07103
The three-dimensional model of the ramp is shown in fig. 1, and three-dimensional coordinates of physical points on the ramp are extracted along the path shown by the arrow in the figure and plotted as a spatial graph, as shown in fig. 2.
Two adjacent physical points P on the driving path of the sightseeing vehiclem、PnHas the coordinates of (x)m，ym，zm) And (x)n，yn，zn) The elevation difference is equal to the difference Z between the Z-direction coordinatesn-zmThe path length of which is approximately equal to the spatial distance L of two pointsmnPath PmPnThe slope of the segment is (z)n-zm)/LmnThe gradient of the path between each two adjacent points is sequentially obtained, as shown in fig. 3.
When the driving path of the sightseeing vehicle is calculated, the slope data points shown in the figure 3 are processed by adopting the combination of 'interpolation fitting + sliding median filtering':
(1) expanding the number of slope calculation points on the path by adopting a 'three-time Hermite interpolation by segmentation' method, wherein the interpolation interval in the slope length direction is 0.1m, and a curve after interpolation fitting is shown in FIG. 4;
(2) the slope curve is smoothly filtered by adopting a 'sliding median filtering' method, the width of a sliding window is 7 (equivalent to the slope length of 0.7 m), and slope abnormity caused by unevenness of a micro-area of a sightseeing bus route and shaking of an unmanned aerial vehicle is reduced, as shown in fig. 5.
And (3) carrying out secondary confirmation on the gradient of the slope section of 6m-12m, and comparing by adopting three measurement methods:
(1) oblique photography three-dimensional model measurement: as shown in FIG. 6, P is selected at the upper part of the slope on the three-dimensional model1、P2Two points, P1And P2Is L from each other12，P1Elevation h of1And P2Elevation h of2Equal and height difference H 120, then pick P at the bottom of the ramp3A point, P1、P2And P3The area of the enclosed triangle is S123From this, P can be obtained3To P1And P2The vertical distance LH and the gradient i of the connecting line;
(2) single-point measurement of gradiometer: selecting A, B, C three points on a section of artificial ramp, and measuring the gradient of A, B, C three points by using a gradiometer;
(3) and (3) continuously measuring by using a total station: and selecting A, B, C, D four points on a section of artificial ramp, and directly measuring the gradient of the A-B, A-C, A-D by using a total station under the condition of not moving the instrument.
Table 2 shows the comparison of the total station, the gradiometer and the oblique photogrammetry results of the unmanned aerial vehicle, from which it can be seen that the oblique photogrammetry results of the unmanned aerial vehicle are closer to the measurement results of the total station, while the error of the gradiometer measurement is larger and the data is more dispersed.
TABLE 2
Measuring method Measured value 1 Measured value 2 Measured value 3 Mean value of Standard value
Total station 9.48％ 9.36％ 9.40％ 9.41％ 0.04％
Gradiometer 9.98％ 11.58％ 10.50％ 10.69％ 0.67％
Unmanned aerial vehicle oblique photography 9.19％ 9.33％ 9.13％ 9.22％％ 0.08％
In fig. 5, the driving route of the sightseeing vehicle is about 35 meters, and assuming that the longest slope length of the exceeding slope is 2m (actually 20m), the slope curve is subjected to the sliding average processing, the width of the sliding average window is 20(2m/0.1m), corresponding to the slope length of 2m, and as a result, as shown in fig. 7, it can be seen that slope sections with the slope length exceeding 2m and the slope exceeding 10% exist at two positions of 8m-10m and 28m-30 m.
The first overproof slope section in fig. 7 was confirmed, and local three-dimensional measurements were performed on a three-dimensional model of the 8m-10m slope section, as shown in fig. 8, with a slope of 10.42% being obtained.
In summary, the invention uses the oblique photography technology of the unmanned aerial vehicle to shoot the ground image of the sightseeing vehicle driving route, carries out three-dimensional modeling on the ground image, extracts coordinates on the three-dimensional model to generate the slope-slope length curve of the sightseeing vehicle, and can quickly detect the slope of the sightseeing vehicle driving route by optimizing the slope-slope length curve.
Finally, it should be noted that the above embodiments are merely representative examples of the present invention. It is obvious that the invention is not limited to the above-described embodiments, but that many variations are possible. Any simple modification, equivalent change and modification made to the above embodiments in accordance with the technical spirit of the present invention should be considered to be within the scope of the present invention.

Claims (8)

1. A road gradient rapid detection method of an off-highway tourist and sightseeing vehicle is characterized by comprising the following steps:
step 1, shooting a ground image of a sightseeing bus route by adopting an oblique photography technology based on an unmanned aerial vehicle platform;
step 2, performing three-dimensional modeling on the shot ground image of the sightseeing bus route;
step 3, extracting a three-dimensional space coordinate set of ground points along the advancing direction of the sightseeing vehicle route on the three-dimensional model;
step 4, calculating the distance and the elevation difference between two adjacent points according to the three-dimensional space coordinate data to generate a 'gradient-slope length' curve of the sightseeing vehicle;
step 5, performing interpolation fitting on the gradient-slope length curve, expanding the number of ground points and increasing gradient detail data;
step 6, carrying out smooth filtering on the interpolation fitting curve;
and 7, performing sliding average on the interpolation fitting curve after smoothing and filtering to confirm the condition that the slope of the route of the sightseeing bus meets the standard.
2. The method as claimed in claim 1, wherein the step 1 comprises the steps of:
step S1, planning the flight route of the unmanned aerial vehicle according to the environment information along the route of the sightseeing vehicle;
step S2, setting flight parameters and photographing parameters of the unmanned aerial vehicle to enable the unmanned aerial vehicle to carry out oblique photography;
and step S3, setting necessary ground control points and standard size models.
3. The method as claimed in claim 1, wherein the step 2 comprises the steps of:
step S1, the shot ground image is subjected to aerial triangulation calculation, and the manufactured markers or natural markers with obvious characteristics can be used as control points;
and step S2, performing three-dimensional model reconstruction on the ground image after the aerial triangulation calculation.
4. The method as claimed in claim 1, wherein the interpolation fitting is performed by a "piecewise cubic Hermite interpolation" method in step 5.
5. The method as claimed in claim 1, wherein the interpolation fitting curve is filtered by a sliding median in step 6.
6. The method as claimed in claim 1, wherein the step 7 comprises the steps of:
step S1, marking the curve of 'gradient-slope length' after smooth filtering as the gradient exceeding threshold GradthThe section S of (1);
step S2, confirming the gradient of the road section S; if the gradient Grad of the road section S is smaller than the gradient threshold GradthIf the road section S meets the requirement, the detection is finished, otherwise, the measurement is continued to exceed the gradient threshold GradthThe slope length of (d);
step S3, on the curve of 'gradient-slope length' after smooth filtering, calculating the sliding average value GradM of the gradient Grad according to the following formula, wherein the width W of the sliding window corresponds to the threshold value L of the slope lengththDrawing an Ln-GradM curve;
Figure FDA0003426337290000021
step S4, if the sliding average values GradM are all smaller than the gradient threshold GradthIf so, the route of the sightseeing bus meets the requirement; if at the length of the slope LmThe sliding average value GradM exceeds the gradient threshold GradthThen, it represents a road section [ L ]m-Lth，Lm]The gradient of the position may exceed the requirement, and the step S is entered5；
And step S5, performing on-site confirmation on the road section with the overproof route.
7. The method as claimed in claim 6, wherein the step of confirming the S-slope of the section of road at step S2 comprises: selecting P spaced far from each other on three-dimensional model map of road section S1、P2、P3Three points, P1Elevation h of1And P2Elevation h of2Equal, P1And P2Is a distance L between12，P3Is lower than P1And P2，P3Has an elevation of h3，P1、P2And P3The area of the enclosed triangle is S123Calculating P3To P1And P2The vertical distance L of the connecting line is 2S123/L12And the gradient Grad of the road section S is as follows:
Figure FDA0003426337290000022
8. the method as claimed in claim 6, wherein the section S is subjected to grade confirmation by a total station or a gradiometer in step S2.
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