CN110132297B - Recycled material clearing and transporting navigation method - Google Patents

Recycled material clearing and transporting navigation method Download PDF

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CN110132297B
CN110132297B CN201910462811.6A CN201910462811A CN110132297B CN 110132297 B CN110132297 B CN 110132297B CN 201910462811 A CN201910462811 A CN 201910462811A CN 110132297 B CN110132297 B CN 110132297B
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path
cruise
alternative
cruising
intersection point
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CN110132297A (en
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廖荠野
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Hangzhou Li'ao Information Technology Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3407—Route searching; Route guidance specially adapted for specific applications
    • G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical

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  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
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Abstract

The invention discloses a method for navigating the collection of objects, which can intelligently and efficiently generate a corresponding path for the cruising of a fixed area of a garbage collection and transportation vehicle according to the actual condition of a road, and can overcome the technical problems that the cruising of the garbage collection and transportation vehicle is not particularly optimized, the better dynamic navigation cannot be realized at the same time, and the method is not suitable for the cruising of the garbage collection and transportation vehicle in the prior art.

Description

Recycled material clearing and transporting navigation method
Technical Field
The invention belongs to the field of intelligent navigation, and particularly relates to a recycled object clearing navigation method.
Background
Along with the improvement of living standard of people, more and more families select cars as transportation tools, so that the automobile ownership is increased rapidly, especially in the city of the second line and the third line, the cars are already brought into the automobile society, and although road facilities are simultaneously and massively built, along with the increase of vehicles, the traffic jam and road accidents happen frequently, and the road jam condition is already common. The capacity of the road is seriously insufficient, and meanwhile, the management measures are not synchronous and even are delayed, so that the situations that a vehicle drives and the road does not run appear. The urban road traffic jam seriously reduces the driving speed and the road traffic capacity, causes the increase of vehicle fuel consumption and the huge waste of time of people, causes huge social cost, economic cost and environmental cost loss, and becomes a common disease which is difficult to get rid of in domestic large and medium-sized cities.
With the improvement of the environmental protection consciousness of people, at present, various domestic garbage in most cities are automatically or semi-automatically collected by adopting a garbage collection vehicle and treated at fixed points, however, the domestic garbage collection vehicle is generally managed according to areas, the garbage is generally collected along a fixed cruising path, and the garbage collection vehicle is generally stranded when a road is congested and has low efficiency. The existing garbage collection vehicle is generally not equipped with or adopts an intelligent traffic path prediction device algorithm to perform road obstacle avoidance, road condition prediction and the like, and even if the existing garbage collection vehicle is provided with the intelligent traffic path prediction device algorithm, the existing navigation software or system is only used for judging road conditions or planning paths, but the existing navigation software or system can only display real-time road conditions and plan corresponding paths generally, and cannot realize short-time prediction or analysis of roads. That is, the conventional static navigation cannot meet the requirement of the conventional urban garbage truck cruise, and is rather incapable of coping with the current situation of frequent occurrence of road traffic emergencies, and in the conventional vehicle navigation, the conventional path planning generally provides the shortest distance path and the shortest time path, without considering the influence of path complexity from a dynamic point of view.
Disclosure of Invention
In view of the above analysis, the main object of the present invention is to provide a method for overcoming the technical problems that the cruise of the garbage collection vehicle is not optimized, and the dynamic navigation cannot be realized, and is not suitable for the cruise of the existing garbage collection vehicle.
The purpose of the invention is realized by the following technical scheme.
A recycling object cleaning navigation method for cruising a cruising path including at least 15 intersections to recycle and clean garbage, said cruising path being composed of a plurality of sections of sub-paths each including at least two garbage cans, wherein the method comprises the steps of:
(1) signal acquisition;
(2) predicting and analyzing roads;
(3) a cruise path is generated.
Further, the signal acquisition specifically includes:
collecting GPS signals by using GPS equipment, and filtering the collected signals;
the average speed of the refuse collection vehicle is recorded and accumulated to generate a historical average speed value.
Further, the road prediction and analysis comprises the following steps:
a. determining a circular area by taking a geometric straight-line section between the current position and the target position of the garbage cleaning and transporting vehicle as a radius, and enabling the area to be a cruising area;
b. selecting a road path T from the current position of the garbage collection and transportation vehicle to a target position in the cruising area, and enabling the position of each intersection in the path to be a positioning point Pi, wherein T is P1- > … - > Pn, i is 1, …, n, n is a natural number which is larger than 1 and represents the total number of intersections in the path T; dividing every three positioning points on the path T into a group according to the sequence on the path T, and calculating the geometric straight-line distance between the first positioning point and the last positioning point in the sequence on the path T in each group of positioning points as a preset radius value; using the position of the garbage can, which is closest to the middle positioning point in each group of 3 positioning points, as a circle center and the preset radius value as a radius, performing circular grid division in the cruising area so as to divide the cruising area into a plurality of cruising alternative grids, wherein crossed points exist among the cruising alternative grids, the crossed points are made to be crossed points, and the crossed points form a crossed point set; the calculated value of the meshing factor is obtained by the following iteration:
Figure BDA0002078554920000031
Figure BDA0002078554920000032
Figure BDA0002078554920000033
wherein Q is defined as a grid partitioning factor, dijRepresenting the path weights starting at intersection point i and ending at intersection point j, m represents the sum of the weights of the paths in the entire path network,
Figure BDA0002078554920000034
representing the sum of the weights of all paths starting from intersection point i,
Figure BDA0002078554920000035
representing the sum of the weights of all paths ending at the intersection point j, CiRepresenting the cruise alternative grid into which the intersection point i is divided, CjRepresenting the cruise alternative mesh into which intersection point j is divided, if intersection point i and intersection point j are divided into the same cruise alternative mesh, δ (C)i，Cj) Is taken to be 1, otherwise δ (C)i，Cj) The value of (d) is 0.
Further, after the step b, the method further comprises:
c. if the calculated value of the obtained grid division factor is larger than the upper integer of the ratio of (n/m), moving the circle center of each cruise alternative grid determined in the step b to the position of the garbage can which is the next closest to the original circle center along the path T to the target position direction, so as to divide the cruise alternative grids again, and repeating the iteration of the step b until the calculated value of the obtained grid division factor is smaller than or equal to the calculated value of the obtained grid division factor
Figure BDA0002078554920000036
The upper integer of the ratio of (a);
d. obtaining the travel time limit of the garbage collection vehicle according to the average value of the areas of the cruise alternative grids and the historical average speed value of the garbage collection vehicle, and deleting a certain intersection point from the set of intersection points to be searched if the time from the intersection point to the starting point exceeds the time limit;
e. repeating steps b, c and d until no such deletions occur;
f. sequencing each cruise alternative grid according to the sequence of the number of the intersection points in the intersection point set corresponding to the cruise alternative grid from large to small, determining the cruise alternative grids which can cover the cruise alternative grids from the current position of the garbage collection truck to the target position and have priority in the sequencing, and taking the cruise alternative grids determined here as ideal cruise alternative grids;
g. determining whether a path exists between positioning points in the ideal cruise alternative grid, and if so, determining the path as a cruise path;
h. if the path does not exist in step g, the path T is altered and steps b to g are repeated until a cruise path is determined.
The technical scheme of the invention has the following advantages:
the existing dependence on navigation signals is reduced, and path planning can be realized only by means of speed detection equipment arranged by the existing speed detection equipment and an electronic map marked with the position of the garbage can. The applicant innovatively provides a cruising method aiming at the practical cruising characteristic of the garbage clearing truck, the problem that the navigation depends on GPS signals or other navigation system signals in the traditional navigation is greatly reduced, and meanwhile, the problem that the street of a garbage can to be cleared must be moved is taken into consideration, the defect that the navigation method in the prior art cannot selectively reserve and set for a plurality of specific road sections is overcome, the automation degree of the garbage clearing process is enhanced, and the effect of intelligently and dynamically planning the path in the garbage clearing process is achieved.
Drawings
FIG. 1 is a flow chart of the method for guidance of the recyclate clearance of the present invention.
Detailed Description
A recycling object cleaning navigation method for cruising a cruising path including at least 15 intersections to recycle and clean garbage, said cruising path being composed of a plurality of sections of sub-paths each including at least two garbage cans, wherein the method comprises the steps of:
(1) signal acquisition;
(2) predicting and analyzing roads;
(3) a cruise path is generated.
Preferably, the signal acquisition specifically comprises:
collecting GPS signals by using GPS equipment, and filtering the collected signals;
the average speed of the refuse collection vehicle is recorded and accumulated to generate a historical average speed value.
Preferably, the road prediction and analysis comprises the steps of:
a. determining a circular area by taking a geometric straight-line section between the current position and the target position of the garbage cleaning and transporting vehicle as a radius, and enabling the area to be a cruising area;
b. selecting a road path T from the current position of the garbage collection and transportation vehicle to a target position in the cruising area, and enabling the position of each intersection in the path to be a positioning point Pi, wherein T is P1- > … - > Pn, i is 1, …, n, n is a natural number which is larger than 1 and represents the total number of intersections in the path T; dividing every three positioning points on the path T into a group according to the sequence on the path T, and calculating the geometric straight-line distance between the first positioning point and the last positioning point in the sequence on the path T in each group of positioning points as a preset radius value; using the position of the garbage can, which is closest to the middle positioning point in each group of 3 positioning points, as a circle center and the preset radius value as a radius, performing circular grid division in the cruising area so as to divide the cruising area into a plurality of cruising alternative grids, wherein crossed points exist among the cruising alternative grids, the crossed points are made to be crossed points, and the crossed points form a crossed point set; the calculated value of the meshing factor is obtained by the following iteration:
Figure BDA0002078554920000051
Figure BDA0002078554920000052
Figure BDA0002078554920000053
wherein Q is defined as a grid partitioning factor, dijRepresenting the path weights starting at intersection point i and ending at intersection point j, m represents the sum of the weights of the paths in the entire path network,
Figure BDA0002078554920000061
representing the sum of the weights of all paths starting from intersection point i,
Figure BDA0002078554920000062
representing the sum of the weights of all paths ending at the intersection point j, CiRepresenting the cruise alternative grid into which the intersection point i is divided, CjRepresenting the cruise alternative mesh into which intersection point j is divided, if intersection points i andthe intersection point j is divided into the same cruise alternative grid, δ (C)i，Cj) Is taken to be 1, otherwise δ (C)i，Cj) The value of (d) is 0.
Preferably, after the step b, the method further comprises:
c. if the calculated value of the obtained grid division factor is larger than the upper integer of the ratio of (n/m), moving the circle center of each cruise alternative grid determined in the step b to the position of the garbage can which is the next closest to the original circle center along the path T to the target position direction, so as to divide the cruise alternative grids again, and repeating the iteration of the step b until the calculated value of the obtained grid division factor is smaller than or equal to the calculated value of the obtained grid division factor
Figure BDA0002078554920000063
The upper integer of the ratio of (a);
d. obtaining the travel time limit of the garbage collection vehicle according to the average value of the areas of the cruise alternative grids and the historical average speed value of the garbage collection vehicle, and deleting a certain intersection point from the set of intersection points to be searched if the time from the intersection point to the starting point exceeds the time limit;
e. repeating steps b, c and d until no such deletions occur;
f. sequencing each cruise alternative grid according to the sequence of the number of the intersection points in the intersection point set corresponding to the cruise alternative grid from large to small, determining the cruise alternative grids which can cover the cruise alternative grids from the current position of the garbage collection truck to the target position and have priority in the sequencing, and taking the cruise alternative grids determined here as ideal cruise alternative grids;
g. determining whether a path exists between positioning points in the ideal cruise alternative grid, and if so, determining the path as a cruise path;
h. if the path does not exist in step g, the path T is altered and steps b to g are repeated until a cruise path is determined.
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 (1)

1. A recycling object cleaning navigation method for cruising a cruising path including at least 15 intersections to recycle and clean garbage, said cruising path being composed of a plurality of sections of sub-paths each including at least two garbage cans, wherein the method comprises the steps of:
(1) signal acquisition;
(2) predicting and analyzing roads;
(3) generating a cruise path;
the signal acquisition specifically comprises:
collecting GPS signals by using GPS equipment, and filtering the collected signals;
recording the average speed of the garbage truck and accumulating to generate a historical average speed value;
the method is characterized in that the road prediction and analysis comprises the following steps:
a. determining a circular area by taking a geometric straight-line section between the current position and the target position of the garbage cleaning and transporting vehicle as a radius, and enabling the area to be a cruising area;
b. selecting a road path T from the current position of the garbage collection and transportation vehicle to a target position in the cruising area, and enabling the position of each intersection in the path to be a positioning point Pi, wherein T is P1- > … - > Pn, i is 1, …, n, n is a natural number which is larger than 1 and represents the total number of intersections in the path T; dividing every three positioning points on the path T into a group according to the sequence on the path T, and calculating the geometric straight-line distance between the first positioning point and the last positioning point in the sequence on the path T in each group of positioning points as a preset radius value; using the position of the garbage can, which is closest to the middle positioning point in each group of 3 positioning points, as a circle center and the preset radius value as a radius, performing circular grid division in the cruising area so as to divide the cruising area into a plurality of cruising alternative grids, wherein crossed points exist among the cruising alternative grids, the crossed points are made to be crossed points, and the crossed points form a crossed point set; the calculated value of the meshing factor is obtained by the following iteration:
Figure FDA0002901109550000021
Figure FDA0002901109550000022
Figure FDA0002901109550000023
wherein Q is defined as a grid partitioning factor, dijRepresenting the path weights starting at intersection point i and ending at intersection point j, m represents the sum of the weights of the paths in the entire path network,
Figure FDA0002901109550000024
representing the sum of the weights of all paths starting from intersection point i,
Figure FDA0002901109550000025
representing the sum of the weights of all paths ending at the intersection point j, CiRepresenting the cruise alternative grid into which the intersection point i is divided, CjRepresenting the cruise alternative mesh into which intersection point j is divided, if intersection point i and intersection point j are divided into the same cruise alternative mesh, δ (C)i，Cj) Is taken to be 1, otherwise δ (C)i，Cj) Is 0;
after the step b, the method further comprises the following steps:
c. if the calculated value of the obtained grid division factor is larger than the upper integer of the n/m ratio, the circle center of each cruise alternative grid determined in the step b is moved to the position of the garbage can which is next closest to the original circle center along the path T to the target position direction, and therefore the distance between the circle center of each cruise alternative grid and the original circle center is increasedDividing the cruise alternative grid again, and repeating the iteration of the step b until the calculated value of the obtained grid division factor is less than or equal to
Figure FDA0002901109550000026
The upper integer of the ratio of (a);
d. obtaining the travel time limit of the garbage collection vehicle according to the average value of the areas of the cruise alternative grids and the historical average speed value of the garbage collection vehicle, and deleting a certain intersection point from the set of intersection points to be searched if the time from the intersection point to the starting point exceeds the time limit;
e. repeating steps b, c and d until no such deletions occur;
f. sequencing each cruise alternative grid according to the sequence of the number of the intersection points in the intersection point set corresponding to the cruise alternative grid from large to small, determining the cruise alternative grids which can cover the cruise alternative grids from the current position of the garbage collection truck to the target position and have priority in the sequencing, and taking the cruise alternative grids determined here as ideal cruise alternative grids;
g. determining whether a path exists between positioning points in the ideal cruise alternative grid, and if so, determining the path as a cruise path;
h. if the path does not exist in step g, the path T is altered and steps b to g are repeated until a cruise path is determined.
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CN106115104A (en) * 2016-06-27 2016-11-16 湖南现代环境科技股份有限公司 Categorized consumer waste collecting and transferring system based on Internet of Things, devices and methods therefor
CN106327902A (en) * 2016-11-16 2017-01-11 安徽省光阴碎片智能科技有限公司 Environmental sanitation management method based on jamming road condition
CN109324552A (en) * 2018-10-12 2019-02-12 上海顺舟智能科技股份有限公司 Smart city waste management system

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EP2973494A4 (en) * 2013-03-15 2016-11-23 Caliper Corp Lane-level vehicle navigation for vehicle routing and traffic management

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Publication number Priority date Publication date Assignee Title
CN106115104A (en) * 2016-06-27 2016-11-16 湖南现代环境科技股份有限公司 Categorized consumer waste collecting and transferring system based on Internet of Things, devices and methods therefor
CN106327902A (en) * 2016-11-16 2017-01-11 安徽省光阴碎片智能科技有限公司 Environmental sanitation management method based on jamming road condition
CN109324552A (en) * 2018-10-12 2019-02-12 上海顺舟智能科技股份有限公司 Smart city waste management system

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