CN112529361A - Road survey route selection method based on smart phone and digital topographic map - Google Patents
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Abstract
The invention provides a road survey route selection method based on a smart phone and a digital topographic map. Calculating the feasibility of road repair of each pixel point in each direction according to an elevation map of the investigation area, and merging feasible points which are smaller than a certain distance and have the same feasible direction into a feasible point to obtain a pre-planned point; and setting a starting point and an end point, obtaining a first path by using an algorithm, and screening according to the first path and the feasible direction of the pre-planned point on the path to obtain the pre-planned path. And setting road grades and outputting a pre-planned highway shade. And detecting the impassable area in the top view to obtain an impassable area mask, and outputting a disaster high-incidence area mask according to the acquired information. And performing enforceability scoring on the pre-planned road according to a road mask, a non-passable region mask and a disaster high-incidence region mask, screening to obtain an enforceable road map, and finally visualizing the enforceable road map and other information in the smart phone through a WebGIS technology.
Description
Technical Field
The application relates to the technical field of investigation, in particular to a road investigation route selection method based on a smart phone and a digital topographic map.
Background
The conventional road survey line selection method is mainly characterized in that a starting point and an end point are set, a path on an elevation map of a survey area is calculated by using an algorithm according to the elevation difference between the starting point and the end point, and the principle of calculating the path is that contour lines are crossed as little as possible and sparse positions of the contour lines are selected when the contour lines are crossed.
"a navigation method and device for mountain field investigation, reconnaissance and search work", published in 2016, 8, 1, discloses a navigation method, which utilizes remote sensing images and topographic maps to jointly construct a route in areas without road network coverage, so as to provide a route for reconnaissance work of reconnaissance personnel. However, when the route is calculated, only the gradient of the midpoint of the investigation region in the direction perpendicular to the two adjacent contour lines is considered, the gradient of each point in other directions is not considered, and the disaster-prone region is not considered to be avoided, so that the route provided by the method does not necessarily have the feasibility of constructing roads.
Disclosure of Invention
Aiming at the problems, the invention provides a road survey route selection method based on a smart phone and a digital topographic map. Calculating the feasibility of road repair of each pixel point in each direction according to an elevation map of the investigation area, and merging feasible points which are smaller than a certain distance and have the same feasible direction into a feasible point to obtain a pre-planned point; and setting a starting point and an end point, obtaining a first path by using an algorithm, and screening according to the first path and the feasible direction of the pre-planned point on the path to obtain the pre-planned path. And setting road grades and outputting a pre-planned highway shade. And detecting the impassable area in the top view to obtain an impassable area mask, and outputting a disaster high-incidence area mask according to the acquired information. And performing enforceability scoring on the pre-planned road according to a road mask, a non-passable region mask and a disaster high-incidence region mask, screening to obtain an enforceable road map, and finally visualizing the enforceable road map and other information in the smart phone through a WebGIS technology.
A road survey route selection method based on a smart phone and a digital topographic map is characterized by comprising the following steps:
obtaining an elevation map and a top view of a survey area through a digital map;
calculating the elevation difference between each pixel point in the elevation map and a plurality of adjacent pixel points in the direction through the template;
judging the feasibility of repairing the road from each pixel to each direction according to the elevation difference between each pixel and the pixel in each direction nearby, and outputting feasible points and feasible directions of the feasible points;
merging feasible points with the distance smaller than the empirical distance threshold and the same feasible direction to one of the feasible points, and outputting a pre-planning point and the direction of the pre-planning point;
setting a starting point, a terminal point and a road grade in an investigation region;
obtaining a path from a starting point to a destination point and passing through a preplanned point through an algorithm, and outputting a plurality of first paths;
connecting the preplanned point with the adjacent preplanned point in the first pathLine is marked as1Calculating l1A straight line l corresponding to the feasible direction of the preplanned point2According to the minimum included angle alpha, screening a first path according to the size relation between alpha and an empirical included angle threshold value, and outputting a pre-planned path;
setting a width for the pre-planned path according to the road grade, and outputting a pre-planned road mask;
detecting an unviable area in a top view by using an unviable area detection network to generate an unviable area mask;
marking out a disaster high-incidence area in the investigation area according to the collected disaster high-incidence area information to generate a disaster high-incidence area mask;
scoring the enforceability of each pre-planned road according to a pre-planned road mask, an impassable area mask and a disaster high-incidence area mask, screening out the pre-planned roads with the enforceability score larger than an experience enforceability threshold value, and outputting an enforceable road map;
and transmitting the top view of the implementable road map and the survey area to the smart phone through the WebGIS and visualizing the top view.
The method for calculating the elevation difference between each pixel point in the elevation map and the pixel points nearby in a plurality of directions through the template comprises the following steps:
calculating through a first template to obtain a first elevation difference between each pixel point on the elevation map and a pixel point in the east direction of the pixel, clockwise rotating the first template by taking the center of the first template as a rotation center, and sequentially calculating to obtain the first elevation differences between each pixel point on the elevation map and pixel points in the south, west and north directions of the pixel point, so as to obtain the feasibility of each pixel point in the south, north, east and west directions;
calculating a second height difference between each pixel point on the elevation map and a pixel in the northeast direction of the pixel through a second template, clockwise rotating the second template by taking the center of the second template as a rotation center, and sequentially calculating to obtain the second height differences between each pixel point on the elevation map and the pixel points in the southeast, southwest and northwest directions of the pixel point, so as to obtain the feasibility of each pixel point in the southeast, northwest, southwest and northeast directions;
if one direction of the past pixel point is not feasible, the pixel point is also not feasible in the direction opposite to the infeasible direction;
screening out pixel points with feasible directions, and outputting a plurality of first feasible points and the feasible directions of the first feasible points; and expanding the first template and the second template for a plurality of times, calculating the feasibility of each direction of the first feasible point, and screening and outputting the feasible points and the feasible directions of the feasible points.
The method for obtaining the path from the starting point to the end point and passing through the pre-planned point through the algorithm comprises the following steps: setting a search radius r, connecting all pre-planned points in a circle with the radius r as the center of the circle from a starting point to the starting point, then searching the pre-planned points in the circle with the radius r as the center of the circle from each pre-planned point connected with the starting point, connecting the searched pre-planned points to the searched center of the circle, repeating the searching and connecting processes, and stopping searching until an end point is searched; each preplanned point in a first path can only occur once.
The training method of the impassable area detection network comprises the following steps: adopting a plurality of top views as a training data set; manually marking an impassable area in a top view to generate marking data; the training of the network is performed using a mean square error loss function.
The method for scoring the feasibility of each pre-planned road comprises the following steps:
calculating the number x of pixel points on a pre-planned highway shade, the number y of pixel points at the intersection of the pre-planned highway shade and a blind area shade, and the number z of pixel points at the intersection of the pre-planned highway shade and a disaster high-incidence area shade;
calculating enforceable rating of the pre-planned road according to a formula
Compared with the prior art, the invention has the following beneficial effects:
(1) the feasibility of the path repair of each pixel point in all directions is calculated by using the first template, the second template and the expansion template, so that the feasibility of the first path can be more accurately evaluated.
(2) The invention uses the neural network to detect the impassable area, obtains the information of the impassable area more quickly and accurately, and can better perform the implementability scoring on the pre-planned road.
(3) The method combines the highway shade, the impassable area shade and the disaster high-incidence area shade to carry out implementability scoring on the pre-planned highway, the consideration is more comprehensive, and the planned highway has stronger implementability.
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FIG. 1 is a process flow diagram.
Fig. 2 is a first template.
Fig. 3 is a second template.
Fig. 4 is the expanded first template.
Fig. 5 is an expanded second template.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The first embodiment is as follows:
the invention mainly aims to obtain the feasible direction of each pixel point in a survey area according to an elevation map and a top view and generate a pre-planned highway shade. And the feasibility of the pre-planned highway is judged by combining the impassable region mask and the disaster high-incidence region mask.
In order to realize the content of the invention, the invention designs a road survey route selection method based on a smart phone and a digital topographic map, and the flow chart of the method is shown in figure 1.
And obtaining an elevation map and a top view of the survey area through the digital map. In order to realize the highway survey route selection method, firstly, a digital map of a survey area is needed. The digital map is a digital representation of a paper map, and is discrete data of ground elements and phenomena having specific coordinates and attributes in a certain coordinate system. The digital map can combine and splice elements of any form of the contents of the common map to form a new map. The digital map can be output in any scale and any range. An elevation map may be generated using the contour lines and elevation points of the digital map. The invention aims to survey and select lines, so that the scale is not suitable to be too large. The top view of the survey area is an RGB image. It should be noted that, the method for obtaining the elevation map and the overhead view of the survey area through the digital map is well known, and the method for obtaining the elevation map and the overhead view is not limited in the present invention.
And carrying out subsequent processing on the elevation map and the top view of the survey area.
And calculating the height difference between each pixel point in the elevation map and the pixel points nearby in a plurality of directions through the template. The first template contains 3 × 3 cells, as shown in fig. 2.
In the invention, the cell right to the right of each template center cell corresponds to the east direction of the center cell, and the cell right above each template center cell corresponds to the north direction of the center cell.
And multiplying the elevation value of the pixel point in each cell by the value in the corresponding cell in the first template by using a 3 multiplied by 3 pixel template taking one pixel point as the center, and adding 9 multiplied results, wherein the result is the first elevation difference between the center pixel point of the current pixel template and the pixel point in the east direction. And sliding the first template to calculate a first elevation difference between each pixel point in the elevation map and the pixel point in the east direction.
The first template is rotated 90 degrees, 180 degrees and 270 degrees clockwise respectively, the elevation values of pixel points in corresponding cells in each 3 x 3 pixel template are multiplied by the values in corresponding cells in the rotated first template, the multiplication results of the 9 pixel points are added to obtain first elevation differences of the central pixel point of the current pixel template and south-direction, west-direction and north-direction pixel points respectively, the rotated first template is slid, and the first elevation differences of each pixel point in the elevation map and the south-direction, west-direction and north-direction pixel points are obtained through calculation.
The second template is a 3 × 3 pixel template with one pixel point as the center, as shown in fig. 3, the elevation values of the pixel points in the corresponding cells in each 3 × 3 pixel template are multiplied by the values in the corresponding cells in the rotated second template, and then the multiplied 9 results are added, and the result is the first elevation difference between the center pixel point of the current pixel template and the pixel point in the northeast direction. And sliding the second template to calculate a first elevation difference between each pixel point in the elevation map and the pixel point in the northeast direction.
And rotating the second template by 90 degrees, 180 degrees and 270 degrees clockwise respectively, multiplying the value in each cell of the rotated second template by the height value of the pixel in the corresponding cell in the 3 multiplied by 3 pixel template, adding the 9 multiplied results to obtain first height differences of the central pixel point of the current pixel template and the pixel points in the southeast, northwest and southwest directions, sliding the rotated second template and calculating to obtain the first height differences of each pixel point in the elevation map and the pixel points in the southeast, southwest and northwest directions.
Setting an empirical height difference threshold m1If the elevation difference between one pixel point and one pixel point in a certain direction is larger than m1Then it is determined that the pixel is not feasible in the direction and the opposite direction. For example: if a pixel point is not feasible in the east direction, no matter whether the height difference between the pixel point and the pixel point in the west direction is more than m or not1This pixel is not feasible in the west direction. It should be noted that different surveys are aimed atChecking the region, and adjusting the empirical threshold m according to the actual condition1The value of (a). The calculated height difference and m of one pixel point and a plurality of direction pixel points1Comparing, screening out the elevation difference value larger than m1The direction of (1) and the opposite direction thereof, the pixel points with feasible directions are reserved. And outputting the first feasible point and the feasible direction of the first feasible point.
The first template and the second template are respectively expanded, the expanded first template is shown in fig. 4, and the expanded second template is shown in fig. 5 and both are templates containing 5 × 5 cells. And calculating the second height difference between the first feasible point and the pixel point in each direction by using the expanded first template and the expanded second template, and screening the first feasible point without feasible direction. And continuously expanding the first template and the second template, repeating the screening process, and finally outputting a plurality of feasible points and feasible directions of the feasible points after multiple screening. The specific template expansion to which size stops should be determined according to the scale of the selected digital topographic map, suggesting at least an expansion to 9 x 9 template.
After the feasible points and the feasible directions of the feasible points are obtained, screening is needed again, and an empirical distance threshold value m is set2，m2Is selected based on the digital topographic map scale. When the distance between two feasible points is less than or equal to m2And when the feasible directions are the same, combining the two feasible points into one point. Repeating the process of merging the feasible points until the distances between every two feasible points with the same feasible direction are greater than m2And stopping merging and outputting the pre-planning points.
And setting a starting point, a terminal point and a road grade in the investigation region. And selecting and sequencing the preplanned points by using an algorithm according to the starting point and the end point to obtain a path from the starting point to the end point and passing through the preplanned points. It should be noted that the algorithms for planning the path are various and well-known, and the invention does not limit the selected algorithms. In this embodiment, a heuristic search algorithm is used. Setting a search radius r, firstly searching out all pre-planned points in a circle with a starting point as a circle center and the radius r, and connecting the searched pre-planned points with the starting point; and then, taking the pre-planned points connected with the starting point as the circle center, searching all the pre-planned points in the circle with the radius of r, connecting the searched pre-planned points with the searched circle center, repeating the searching and connecting processes until the end point is searched and connected with the end point, and outputting a plurality of first paths.
It should be noted that the set search radius r1Should not be too large to avoid including a non-passable point in the first path. And each preplanned point in each first path can only appear once, so that endless loops are avoided.
And screening the first path based on the feasible direction of the pre-planned point for the obtained first path. The connecting line of the pre-planning point on the first path and the adjacent pre-planning point is set as l1The straight line of the feasible direction of the preplanned point is l2Calculating l1And l2The minimum included angle value alpha is taken, and an empirical included angle threshold value m is set3If alpha of a pre-planned point is greater than or equal to m3And judging that the first path corresponding to the pre-planning point is not feasible. And screening out the infeasible first paths, and finally outputting a plurality of preplanned paths.
And setting the width of the pre-planned path according to the set road grade, and generating a pre-planned road mask which is based on the pre-planned path and has the width of the set road grade width.
And training a detection network in an unviable area, wherein the unviable area comprises rivers, buildings, swamps and the like. The method comprises the following specific steps: adopting a plurality of top views as a training data set; manually marking out the pixels of each impassable area in the top view to generate marking data; the training of the network is performed using a mean square error loss function.
And inputting the top view into a trained unvaryable area detection network, detecting an unvaryable area, and outputting an unvaryable area mask.
And acquiring disaster high-occurrence area information of the investigation area, marking the disaster high-occurrence area in a plan view of the investigation area, and generating a disaster high-occurrence area mask through certain post-processing.
Calculating the implementability of each pre-planned road, taking one pre-planned road as an example, and calculating the implementability score in the following way: the method comprises the steps of calculating the number x of pixel points on a pre-planned road mask, calculating the number y of pixel points of intersection of the pre-planned road mask and a non-passable region mask, calculating the number z of pixel points of intersection of the pre-planned road mask and a disaster high-incidence region mask, and calculating the enforceability score of each pre-planned road according to an enforceability scoring formula.
Setting an empirically implementable threshold m4When the score of the pre-planned road is greater than or equal to m4Then, it is determined that the pre-planned road is practicable. And calculating the score of all the pre-planned roads, and outputting a plurality of implementable road maps after screening.
The actual length of each implementable road is calculated by various and well-known calculation methods, and the method for calculating the implementable road length is not limited by the invention. The road maps will be ranked by length, with shorter lengths ranked higher.
And transmitting implementable road ranking information, implementable road map and survey area top view to the smart phone through a WebGIS technology. The reconnaissance personnel can check own position information on the smart phone, and can carry out reconnaissance work better by combining with an implementable road map.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (5)
1. A road survey route selection method based on a smart phone and a digital topographic map is characterized by comprising the following steps:
obtaining an elevation map and a top view of a survey area through a digital map;
calculating the elevation difference between each pixel point in the elevation map and a plurality of adjacent pixel points in the direction through the template;
judging the feasibility of repairing the road from each pixel to each direction according to the elevation difference between each pixel and the pixel in each direction nearby, and outputting feasible points and feasible directions of the feasible points;
merging feasible points with the distance smaller than the empirical distance threshold and the same feasible direction to one of the feasible points, and outputting a pre-planning point and the direction of the pre-planning point;
setting a starting point, a terminal point and a road grade in an investigation region;
obtaining a path from a starting point to a destination point and passing through a preplanned point through an algorithm, and outputting a plurality of first paths;
marking the connecting line of the preplanned point and the adjacent preplanned point on the first path as l1Calculating l1A straight line l corresponding to the feasible direction of the preplanned point2According to the minimum included angle alpha, screening a first path according to the size relation between alpha and an empirical included angle threshold value, and outputting a pre-planned path;
setting a width for the pre-planned path according to the road grade, and outputting a pre-planned road mask;
detecting an unviable area in a top view by using an unviable area detection network to generate an unviable area mask;
marking out a disaster high-incidence area in the investigation area according to the collected disaster high-incidence area information to generate a disaster high-incidence area mask;
scoring the enforceability of each pre-planned road according to a pre-planned road mask, an impassable area mask and a disaster high-incidence area mask, screening out the pre-planned roads with the enforceability score larger than an experience enforceability threshold value, and outputting an enforceable road map;
and transmitting the top view of the implementable road map and the survey area to the smart phone through the WebGIS and visualizing the top view.
2. The method according to claim 1, wherein the step of calculating the elevation difference between each pixel point in the elevation map and the pixel points in the plurality of directions nearby by using the template comprises:
calculating through a first template to obtain a first elevation difference between each pixel point on the elevation map and a pixel point in the east direction of the pixel, clockwise rotating the first template by taking the center of the first template as a rotation center, and sequentially calculating to obtain the first elevation differences between each pixel point on the elevation map and pixel points in the south, west and north directions of the pixel point, so as to obtain the feasibility of each pixel point in the south, north, east and west directions;
calculating a second height difference between each pixel point on the elevation map and a pixel in the northeast direction of the pixel through a second template, clockwise rotating the second template by taking the center of the second template as a rotation center, and sequentially calculating to obtain the second height differences between each pixel point on the elevation map and the pixel points in the southeast, southwest and northwest directions of the pixel point, so as to obtain the feasibility of each pixel point in the southeast, northwest, southwest and northeast directions;
if one direction of the past pixel point is not feasible, the pixel point is also not feasible in the direction opposite to the infeasible direction;
screening out pixel points with feasible directions, and outputting a plurality of first feasible points and the feasible directions of the first feasible points;
and expanding the first template and the second template for a plurality of times, calculating the feasibility of each direction of the first feasible point, and screening and outputting the feasible points and the feasible directions of the feasible points.
3. The method of claim 1, wherein the algorithmically deriving the path from the start point to the end point and through the pre-planned point is by: setting a search radius r, connecting all pre-planned points in a circle with the radius r as the center of the circle from a starting point to the starting point, then searching the pre-planned points in the circle with the radius r as the center of the circle from each pre-planned point connected with the starting point, connecting the searched pre-planned points to the searched center of the circle, repeating the searching and connecting processes, and stopping searching until an end point is searched;
each preplanned point in a first path can only occur once.
4. The method of claim 1, further characterized in that the method of training the unvarying area detection network is:
adopting a plurality of top views as a training data set;
manually marking an impassable area in a top view to generate marking data;
the training of the network is performed using a mean square error loss function.
5. The method of claim 1, wherein scoring the enforceability of each pre-planned road comprises:
calculating the number x of pixel points on a pre-planned highway shade, the number y of pixel points at the intersection of the pre-planned highway shade and a blind area shade, and the number z of pixel points at the intersection of the pre-planned highway shade and a disaster high-incidence area shade;
calculating enforceable rating of the pre-planned road according to a formula
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