CN105547310B - A kind of path planning apparatus and method based on the trip of PM2.5 health - Google Patents
A kind of path planning apparatus and method based on the trip of PM2.5 health Download PDFInfo
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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
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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
- G01C21/3453—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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Abstract
The invention discloses a kind of path planning apparatus and method based on the trip of PM2.5 health, including vehicle-mounted PM2.5 detection devices, information transmission modular and server terminal three parts, wherein, information transmission modular includes GPS module and GPRS module, server terminal includes path planning module, PM2.5 detection devices are installed in Floating Car, and it is connected with information transmission modular, information transmission modular is connected with server terminal, and the mobile device of user only can need to easily access the data in server terminal by browser.The present invention uses modified dijkstra's algorithm, and mainly using PM2.5 integrated concentrations as impedance, with the minimum target of total concentration, healthy path planning is followed with PM2.5 optimal path objective optimization functions.
Description
Technical Field
The invention belongs to a path planning navigation system under big data, and particularly relates to a device and a method capable of detecting a PM2.5 value and realizing healthy trip path planning.
Background
With the gradual improvement of a road network, the automobile holding capacity is larger and larger, the traffic condition is more and more tense due to the high-density urbanization process, and the atmospheric pollution is more and more serious. Because the components of the atmospheric particulates are complex, the carried components such as heavy metal elements, cyclic hydrocarbon organic matters and the like enter human bodies along with respiratory tracts, and the human health is seriously harmed. And among them, PM2.5 is the most harmful, and has small particle size, large specific surface area and easy enrichment of toxic substances. Through research, PM2.5 pollution and adult respiratory system disease rate are in positive correlation.
Therefore, when people go out, how to accurately obtain a large amount of PM2.5 concentration values, and a convenient and healthy appearing route is planned according to the overall condition of the concentration values, so that the problem that a large amount of harmful gas is prevented from being directly inhaled under the condition that the existing PM2.5 value is too high, and healthy outgoing which is damaged to the minimum extent is mainly considered is solved.
In the current research at home and abroad, the path planning is mainly the optimal path planning based on traffic information according to the user requirements, and the criteria of the optimal path include: the current path planning algorithm is a navigation process from a starting point to a terminal point by using a criterion of distance, time or cost as the lowest cost, and the requirement on health is not involved; the air pollution treatment is mainly carried out by people who have passive actions such as mask or weather reduction and exit at PM2.5 value. Therefore, it is necessary to invent a healthy trip navigation system and a path planning method for the PM2.5 value.
Disclosure of Invention
The invention aims to place the PM2.5 value into big data, provide a new navigation method for travel and enable the travel process to be more convenient, faster and healthier.
The technical solution for realizing the purpose of the invention is as follows:
a route planning device based on PM2.5 healthy travel comprises three major parts, namely vehicle-mounted PM2.5 detection equipment, an information transmission module and a server terminal, wherein the information transmission module comprises a GPS module and a GPRS module; the PM2.5 detection equipment can directly acquire PM2.5 values of paths through which the floating vehicles pass, the GPS module acquires geographic position information of the floating vehicles, the GPRS module transmits the acquired PM2.5 values and the geographic position information to the path planning module of the server terminal, and the path planning module realizes final path planning. The information transmission module transmits the detected PM2.5 value, the geographic coordinate and the detection time; recording and detecting the passing position of the PM2.5 floating vehicle by the geographic coordinates, and adopting standard longitude and latitude coordinates; the route planning module plans a healthy travel route by adopting an improved Dijkstra algorithm, positions a start point and an end point on the basis of an original road network structure, forms a network topological graph with weight according to a PM2.5 detection value and simplifies the network topological graph into a directed weighting connected graph, takes the optimal PM2.5 concentration as a target traversal node, reduces a traversal area according to a search limiting condition, performs local layer search work by taking the node as a unit when the search area meets a rectangular limiting search condition, and can improve a search level until the highest level of a road network is reached after the distance is greater than a certain value R; when the search area does not meet the rectangular limited search condition, changing the search area into rectangular search, and repeating the shortest path search process which takes the minimum PM2.5 concentration value as the target again, and gradually perfecting the planned path along with the rise of the search level; the PM2.5 detection values of the same place at different times acquired by the vehicle-mounted PM2.5 detection equipment need to be recorded repeatedly.
The path planning method based on PM2.5 healthy trip comprises the following specific processes:
the method comprises the following steps: determining single-section floating car sample size
Statistical time period TpWithin, the average PM2.5 estimate isComprises the following steps:
in the formula, PiPM2.5 value of the ith floating car; i is the floating car serial number; n is a radical ofpThe total number of floating cars passing through the road section in the time period is counted.
The distribution frequency of the PM2.5 daily average concentration measured by the floating car is close to the lognormal distribution, M is the logarithm of the PM2.5 concentration value P, namely M is In (P), and M is subjected to standardization treatment so as to obtain the PM2.5 daily average concentrationthe calculation model of the number of the floating cars on the single road section is as follows:
in the formula,is the upper α quantile and sigmapIs the standard deviation; epsilonpTo allow for concentration error values.
Considering the influence of the line length on the number of floating cars, for NpThe revision is carried out as follows:
in the formula, l is the length of the target road section; t ispThe statistical time is obtained.
Step two: determining road network floating car sample volume
Because the floating car line is not fixed, in order to ensure the target precision, the frequency can be described by the traffic flow density. Probability P of floating car appearing on any roadiComprises the following steps:
in the formula, a is the number of road grades and is a constant; n is a radical ofiThe total number of the roads is type i; rhoiI road traffic flow density; li,jIs the jth section r of the type i roadi,jLength of (d).
The floating car is on the j section r of the type i roadi,jProbability of occurrence Pi,jComprises the following steps:
revising P considering the stop time and error times of the floating cari,jComprises the following steps:
P′i,j＝Pi,j(1-Ps)(1-Pc)
in the formula, PsThe floating car stop rate is obtained; pcThe error rate of the floating car.
The number calculation model of the floating cars under the whole road network is as follows:
in the formula, Nz,iThe number of floating cars required by the i-shaped road can be obtained by the first step; ziFor the influence factors of different types of roads, the calculation method comprises the following steps:
step three: planning according to PM2.5 concentration value sequence path
At the starting point (x)1,y1) End point (x)2,y2) After determination, an elliptical area for search restriction is established:
in the formula,
partial derivatives are calculated for x and y to obtain extreme values x of x and ymin、xmax、ymin、ymaxPolar coordinate (x)max,ymax)、(xmin,ymin)、(xmax,ymin)、(xmin,ymax) Four points constitute a rectangular area that limits the search.
Wherein,
applying an improved Dijkstra algorithm based on PM2.5 density value path planning in a rectangular area limited for searching, namely an environment optimal path objective optimization function:
in the formula, gij(t) is a sequence of PM2.5 concentration values from node i to j at time t; f. ofiAnd (t) is an optimal PM2.5 concentration value sequence from the moment i to the end point at the time t, and N is a node at the end point.
Compared with the prior art, the invention has the following remarkable advantages:
(1) obtaining PM2.5 concentration value and planning health path
Most of the existing navigation systems perform path search aiming at shortest time, shortest distance or shortest cost in the aspect of path planning, and a travel route design scheme considering the health condition of pedestrians is rare. The invention utilizes vehicle-mounted PM2.5 detection equipment arranged on floating vehicles to detect the air quality of each road section on a road network, and forms a network topological graph taking the PM2.5 value as the weight according to the PM2.5 concentration value acquired by each floating vehicle, thereby providing a healthy travel route for travelers.
(2) Hierarchical, efficient path planning for road networks
In the existing path planning method, for pursuing the best line, the algorithm is often more complex, which greatly affects the efficiency of the whole path planning process. The invention provides a thought of road network layering in the aspect of a path planning algorithm, combines preprocessing and layering search by adopting an improved Dijkstra algorithm of area restriction search, converts an original road network plane into a multilayer road network, and continuously converts search among layers.
(3) Real-time data processing, dynamic path planning
Most path planning algorithms are based on the shortest-path algorithm based on the road side weights, namely, the static shortest-path algorithm. Due to the large scale of the traffic network, the efficiency of the static path solving process is low, and the service response speed is slow. The invention utilizes the GPS module and the GPRS module to acquire and transmit data in real time, realizes dynamic path planning, and improves the efficiency and the accuracy of the whole path planning process.
(4) Multi-element path planning combined with user requirements
Compared with other patents and the existing navigation equipment, the invention adds the function of 'healthy trip' route planning on the basis of navigation, and if the healthy trip is combined with factors such as time, distance, cost and the like, the route planning under the condition of optimal comprehensive factors can be realized.
Drawings
Fig. 1 is a flow chart of a path planning algorithm of the present invention.
Fig. 2 is a schematic diagram of a matrix region for limiting search.
FIG. 3 is a diagram showing the relationship between the components of the present invention.
Detailed Description
The invention will be further described with reference to the following figures and specific examples:
as shown in fig. 1, the path planning device for PM2.5 healthy trip according to the present invention obtains a PM2.5 concentration value through a vehicle-mounted PM2.5 detection device and establishes a traffic database by combining with traffic flow parameters. When a user inputs start and end point information for navigation, traffic data are imported into a GIS database, line matching is carried out by using an improved Dijkstra algorithm, the matched line enters a cloud end and is transmitted to a webpage server, and finally the matched line is displayed on a user terminal computer or a mobile phone.
As shown in fig. 2, the path planning method based on PM2.5 healthy travel of the present invention is an improved Dijkstra algorithm, and after a user inputs a start point and an end point, a network topology graph is loaded, and a hierarchical operation is performed on a complex topology graph, that is, a road network is subjected to a hierarchical division to obtain a plurality of road network levels with different densities and numbers of road segments, and a data structure of the complex road network is simplified based on sparse different layers, and the specific operation steps are as follows:
step 1: according to the road grade, the road network is divided into a road network layers with different grades.
Step 2: initializing the road network and simplifying the complex road network. And recording the road network information of two nodes by using a data structure (S, T, L and P), wherein S is a node 1, T is a node 2, L is the shortest between the two nodes, and P is the shortest between the two nodes under the condition of optimal PM2.5 concentration.
And step 3: traversing the road network nodes, if L is smaller than a certain fixed threshold (X), defaulting that two nodes are close, removing one node, generating two nodes with a virtual road section connected and the point close to the removed point, and updating to generate a new road network simplified structure, wherein the virtual edge creating process is as shown in the following figure 2.
And 4, step 4: and merging the split a road networks with different levels aiming at the same node.
Establishing an adjacency matrix M according to the positions of a starting point and an ending point in a topological graph, reordering the adjacency matrix M according to side weights (PM 2.5 concentration values of each road section) to construct an adjacency list T, and directly acquiring a healthy travel path with the minimum PM2.5 concentration value by using a Dijkstra algorithm if the T meets a rectangular restriction search condition Lmax, namely L is not more than Lmax, wherein the specific Dijkstra algorithm is as follows:
in the formula, gij(t) is a sequence of PM2.5 concentration values from node i to j at time t; f. ofi(t) is the optimal PM2.5 concentration value sequence from time t to the end point.
If L < Lmax, then start with (x)1,y1) End point (x)2,y2) Constructing an ellipse equation:
in the formula,
then, the offset derivative is calculated for x and y to obtain the pole coordinate (x)max,ymax)、(xmin,ymin)、(xmax,ymin)、(xmin,ymax) The rectangular area is searched for by the restriction of (3), as shown in fig. 3.
Wherein,
and finally, calculating an optimal path in the rectangular area by using an improved Dijkstra algorithm based on PM2.5 density value path planning, namely:
in the formula, gij(t) is a sequence of PM2.5 concentration values from node i to j at time t; f. ofiAnd (t) is an optimal PM2.5 concentration value sequence from the moment i to the end point at the time t, and N is a node at the end point.
Claims (1)
1. A path planning method based on PM2.5 healthy trips is characterized by comprising the following specific steps:
the method comprises the following steps: determining single-section floating car sample size
Statistical time period TpInner, mean PM2.5 estimate
In the formula, PiPM2.5 value of the ith floating car; i is the floating car serial number; n is a radical ofpCounting the total number of floating cars passing through a road section in a time period;
let M be the logarithm of the PM2.5 concentration value P, i.e., M ═ In (P), and M is normalized tothe calculation model of the number of the floating cars on the single road section is as follows:
in the formula,is the upper α quantile and sigmapIs the standard deviation; epsilonpTo allow for concentration error values;
to NpThe revision is carried out as follows:
in the formula, l is the length of the target road section; t ispCounting time;
step two: determining road network floating car sample volume
Probability P of floating car appearing on any roadiComprises the following steps:
in the formula, a is the number of road grades and is a constant; n is a radical ofiThe total number of the roads is type i; rhoiI road traffic flow density; li,jIs the jth section r of the type i roadi,jLength of (d);
the floating car is on the j section r of the type i roadi,jProbability of occurrence Pi,jComprises the following steps:
revision Pi,jComprises the following steps:
P′i,j＝Pi,j(1-Ps)(1-Pc)
in the formula, PsThe floating car stop rate is obtained; pcIn order to achieve the error rate of the floating car,
the number calculation model of the floating cars under the whole road network is as follows:
in the formula, Nz,iThe number of floating cars required by the i-shaped road can be obtained by the first step; ziFor the influence factors of different types of roads, the calculation method comprises the following steps:
step three: planning according to PM2.5 concentration value sequence path
At the starting point (x)1,y1) Endpoint (x)2,y2) After determination, a rectangular area for limiting search is established:
in the formula,
partial derivatives are calculated for x and y to obtain extreme values x of x and ymin、xmax、ymin、ymaxPolar coordinate (x)max,ymax)、(xmin,ymin)、(xmax,ymin)、(xmin,ymax) Four points form a rectangular area for limiting search;
wherein,
traversing network topology nodes by taking PM2.5 optimal as a target in a limited search rectangular area to obtain an optimal path, namely constructing an environment optimal path target optimization function:
in the formula, gij(t) the value of PM2.5 concentration from node i to j at time t; f. ofi(t) is the optimal PM2.5 concentration value from i to the end point at time t, and N is the node at the end point.
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| DE202017104953U1 (en) * | 2016-08-18 | 2017-12-04 | Google Inc. | Processing fundus images using machine learning models |
| CN107560632A (en) * | 2017-09-21 | 2018-01-09 | 上海泽罗电子科技有限公司 | A kind of application process based on smart electronicses mouth mask cloud service big data |
| CN108020237A (en) * | 2017-11-28 | 2018-05-11 | 浙江树人大学 | It is a kind of to suck the minimum pedestrian's paths planning method of pollutant of vehicle exhaust |
| CN108827842A (en) * | 2018-04-13 | 2018-11-16 | 安徽新华学院 | A kind of air quality optimum path planning method and system based on PM2.5 |
| CN108845076A (en) * | 2018-04-25 | 2018-11-20 | 北京市电话工程有限公司 | A kind of air-quality monitoring system of cell |
| CN112378414A (en) * | 2020-11-20 | 2021-02-19 | 深圳信息职业技术学院 | Route planning device and method based on PM2.5 healthy trip |
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| CN105043401A (en) * | 2015-07-14 | 2015-11-11 | 南京理工大学 | Urban healthy trip planning method and system based on floating car method |
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| CN105043401A (en) * | 2015-07-14 | 2015-11-11 | 南京理工大学 | Urban healthy trip planning method and system based on floating car method |
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Inventor after: Guo Tangyi Inventor after: Jiang Xuejiao Inventor after: Zhu Yunxia Inventor after: Ge Xuting Inventor after: Fan Wei Inventor after: Liu Kang Inventor after: Zou Cheng Inventor after: Wu Zhongshan Inventor before: Guo Tangyi Inventor before: Jiang Xuejiao Inventor before: Zhu Yunxia Inventor before: Ge Xuting Inventor before: Fan Wei Inventor before: Shao Fei Inventor before: Liu Kang Inventor before: Zou Cheng Inventor before: Wu Zhongshan |