CN105547310A - Apparatus and method for route planning based on PM2.5 healthy trip - Google Patents

Abstract

The invention discloses an apparatus and method for route planning based on a PM2.5 healthy trip. The apparatus comprises three parts of a vehicle-mounted PM2.5 detector, an information transmission module, and a server terminal, wherein the information transmission module includes a GPS module and a GPRS module; the server terminal includes a route planning module; and the PM2.5 detector is mounted on a floating vehicle and is connected to the information transmission module, which is connected to the server terminal. A mobile device of a user can easily access data in the server terminal by means of a browser. According to the method, an improved Dijkstra algorithm is adopted, an integrated PM2.5 concentration is mainly taken as impedance, and a minimum total concentration is taken as a target. A healthy trip is planned according to an optimized function taking a PM2.5 optimal route as the target.

Description

A kind of path planning apparatus based on the trip of PM2.5 health and method

Technical field

The invention belongs to the path planning navigational system under large data, specifically one can detect PM2.5 value, realizes the device and method of healthy trip route planning.

Background technology

Along with the gradual perfection of network of highways, automobile pollution is increasing, and high density settling pond process makes traffic growing tension, and atmospheric pollution is day by day serious.Due to Atmospheric particulates complicated component, the compositions such as the heavy metal element entrained by it, cyclic hydrocarbon organism enter human body with respiratory tract, serious harm health.And wherein the harmfulness of PM2.5 is the most serious, its particle diameter is little, specific surface area large, easier enrichment noxious material.After deliberation, PM2.5 pollutes and is proportionate with the illness rate of adult respiratory system.

Therefore, when people go on a journey, the how a large amount of PM2.5 concentration value of Obtaining Accurate, cooking up convenient, a healthy appearance circuit according to concentration value overall condition is avoid when there is PM2.5 value and being too high directly sucking a large amount of harmful gas, and the health that minimum degree comes to harm is gone on a journey the problem of answering emphasis to consider.

In current research both domestic and external, path planning aspect is mainly according to the optimum path planning based on transport information that user's request is carried out, the criterion of optimal path has: cost is minimum, section is evaded, by specific region etc., current path planning algorithm is all with distance, time or spends as cost minimum criteria is by the navigation procedure of origin-to-destination, does not relate to the demand of healthy aspect; Reply atmospheric pollution aspect mainly the masses from hair band mouth mask or the personal behavior reducing negative and positive coping style such as going out at the quick-fried table weather of PM2.5 value.Therefore, invent a kind of health for PM2.5 value trip navigational system and paths planning method be very necessary.

Summary of the invention

The object of the invention is to PM2.5 value to put into large data, for trip provides a kind of new air navigation aid, enable trip process more convenient, healthy.

The technical solution realizing the object of the invention is:

A kind of path planning apparatus based on the trip of PM2.5 health, comprise vehicle-mounted PM2.5 checkout equipment, information transmission modular and server terminal three parts, wherein, information transmission modular comprises GPS module and GPRS module, server terminal comprises path planning module, PM2.5 checkout equipment is installed in Floating Car, and is connected with information transmission modular, and information transmission modular is connected with server terminal; PM2.5 checkout equipment directly can gather Floating Car institute through path PM2.5 value, GPS module obtains Floating Car geographical location information, acquisition PM2.5 value and geographical location information are transferred to the path planning module of server terminal by GPRS module, and path planning module realizes final path planning.PM2.5 value detected by information transmission modular transmission, geographic coordinate and detection time; Geographic coordinate record detects the Floating Car institute of PM2.5 through position, adopts standard latitude and longitude coordinates; Path planning module adopts modified dijkstra's algorithm to plan healthy traffic path, start, end are located based on former road network structure, form the network topological diagram of Weight according to PM2.5 detected value and be reduced to oriented tax power connected graph, optimum for target traverse node with PM2.5 concentration, traversal region reduces according to search restrictive condition, when region of search meets rectangle restriction search condition, this layer of search work is carried out in units of node, after distance is greater than certain value R, search level can be improved, until it is highest to arrive road network; When region of search does not meet rectangle restriction search condition, change region of search is rectangular search, and again repeats with the minimum shortest path search process for target of PM2.5 concentration value, along with search level raises, and gradual perfection path planning; Wherein vehicle-mounted PM2.5 checkout equipment obtain not same place in the same time PM2.5 detected value need repeat record.

Based on the paths planning method of PM2.5 health trip, detailed process is:

Step one: determine single channel section Floating Car sample size

Timing statistics section T _pin, mean P M2.5 estimated value is for:

In formula, P _iit is the PM2.5 value of i-th Floating Car; I is Floating Car sequence number; N _pfor the Floating Car sum through section in timing statistics section.

The distribution frequency of the PM2.5 daily mean of concentration measured by Floating Car is close to lognormal distribution, and make M be the logarithm of PM2.5 concentration value P, namely M=In (P), carries out standardization to M, with for the upper α quantile of standard profile, then the Floating Car quantity computation model in single channel section is:

In formula, for upper α quantile; σ _pfor standard deviation; ε _pfor safe level error amount.

Consider that line length is on the impact of Floating Car quantity, to N _pcarry out revising:

In formula, l is target road section length; T _pfor timing statistics.

Step 2: determine road network Floating Car sample size

Because Floating Car circuit is not fixed, for ensureing aimed at precision, available traffic flow density describes frequency.The probability P that Floating Car occurs on any road _ifor:

In formula, a is category of roads number, is constant; N _ifor type i road sum; ρ _ifor i road traffic current density; l _i,jfor jth section section r in type i road _i,jlength.

Floating Car is jth section section r in type i road _i,jthe probability P of upper appearance _i,jfor:

$P_{i,j}=\frac{P_i\·l_{i,j}}{\underset{j=1}{\overset{N_i}{\Σ}}{l}_{i,j}}$

Consider down time and the errors number of Floating Car itself, revision P _i,jfor:

P′ _i,j＝P _i,j(1-P _s)(1-P _c)

In formula, P _sfor Floating Car unoperating rate; P _cfor Floating Car error rate.

Floating Car quantity computation model under whole road network is:

$N_z=\underset{i=1}{\overset{a}{\Σ}}(Z_i\·N_{z,i})$

In formula, N _z,ifloating Car number needed for i type road, can utilize step one to try to achieve; Z _ifor the factor of influence of different types of road, computing method are:

$Z_i=\frac{\underset{j=1}{\overset{N_i}{\Σ}}{l}_{i,j}}{\underset{i=1}{\overset{a}{\Σ}}\underset{j=1}{\overset{N_i}{\Σ}}{l}_{i,j}}$

Step 3: according to PM2.5 concentration value sequence path planning

At starting point (x ₁, y ₁), terminal (x ₂, y ₂) determine after, set up restriction search elliptic region:

$\frac{{\[cos\mathrm{\θ}(x-a)+sin\mathrm{\θ}(y-b)\]}^2}{A^2}+\frac{{\[-sin\mathrm{\θ}(x-a)+cos\mathrm{\θ}(y-b)\]}^2}{B^2}=1$

In formula,

$\mathrm{\θ}=arctg\left(\frac{y_2-y_1}{x_2-x_1}\right);$

$a=\frac{x_1+x_2}{2};$

$b=\frac{y_1+y_2}{2};$

$A=\frac{\mathrm{\τ}}{2}\sqrt{{(y_2-y_1)}^2+{(x_2-x_1)}^2};$

$B=\sqrt{A^2-\frac{{(y_2-y_1)}^2+{(x_2-x_1)}^2}{4}}$

Local derviation is asked to x, y, the extreme value x of x, y can be obtained _min, x _max, y _min, y _max, limit coordinate (x _max, y _max), (x _min, y _min), (x _max, y _min), (x _min, y _max) rectangular area of 4 composition restriction search.

Wherein,

$x_{max}=a+\sqrt{A^2{\cos }^2\mathrm{\θ}+B^2{\sin }^2\mathrm{\θ}}$

$x_{min}=a-\sqrt{A^2{\cos }^2\mathrm{\θ}+B^2{\sin }^2\mathrm{\θ}}$

$y_{max}=b+\sqrt{A^2{\cos }^2\mathrm{\θ}+B^2{\sin }^2\mathrm{\θ}}$

$y_{min}=b-\sqrt{A^2{\cos }^2\mathrm{\θ}+B^2{\sin }^2\mathrm{\θ}}$

The improvement dijkstra's algorithm based on PM2.5 concentration value path planning is applied, i.e. environment optimal path objective optimization function in the rectangular area of restriction search:

$\{\begin{array}{c}{f}_i\left(t\right)=\underset{j\≠i}{\min }\left(g_{ij}\right(t)+f_j(t+g_{ij}\left(t\right)\left)\right)\\ f_N\left(t\right)=0\end{array},i=1,2,\mathrm{...},N-1$

In formula, g _ijt () is the PM2.5 concentration value sequence of t from node i to j; f _it () is the optimum PM2.5 concentration value sequence of t from i to terminal, N is destination county node.

Compared with prior art, its remarkable advantage is in the present invention:

(1) PM2.5 concentration value is obtained, healthy path planning

Existing navigational system great majority in path planning are all the shortest for shortest time, distance or the shortest route searching carried out of cost, rarely have the travel route design proposal considering pedestrian's health status.The present invention utilizes and in Floating Car, installs the satisfy the need air quality in online each section of vehicle-mounted PM2.5 checkout equipment detect, according to the PM2.5 concentration value that each Floating Car obtains, form the network topological diagram that is weight with PM2.5 value, thus provide a kind of travel route of health for traveler.

(2) hierarchy of road network, efficient path planning

Present paths planning method is best for pursuing circuit, and often algorithm is comparatively complicated, and this have impact on the efficiency of whole path planning process greatly.The present invention proposes the thought of hierarchy of road network in path planning algorithm, the modified version dijkstra's algorithm of region limits search is adopted pre-service to be combined with hierarchical search, be multilayer road network by original road network plane conversion, constantly search is changed between each level, this method has saved search volume greatly, provides circuit search efficiency.

(3) real time data processing, active path planning

The basis of present most path planning algorithm is the shortest path algorithm based on roadside, fixing road power, is also static shortest path algorithm.Because traffic network scale is large, the efficiency of static path solution procedure is low, and service response speed is slower.The present invention utilizes GPS module and GPRS module to carry out real-time data acquisition and transmission, realizes active path planning, improves efficiency and the accuracy of whole path planning process.

(4) combine with user's request, path diversity is planned

Relative to other patents and existing navigator, the present invention according to function point adding " healthy trip " layout of roads, if the factors such as health trip and time, distance, expense combined, can realize the path planning under composite factor optimum in navigation.

Accompanying drawing explanation

Fig. 1 is path planning algorithm process flow diagram of the present invention.

Fig. 2 is the matrix area schematic diagram of restriction search.

Fig. 3 is each ingredient associated diagram of the present invention.

Embodiment

Below in conjunction with the drawings and specific embodiments, the invention will be further described:

As shown in Figure 1, the path planning apparatus that the present invention is based on the trip of PM2.5 health obtains PM2.5 concentration value by vehicle-mounted PM2.5 checkout equipment and sets up traffic database in conjunction with traffic flow parameter.When user input terminus information navigate time, traffic data imports in GIS database, and utilize the dijkstra's algorithm improved to carry out line matching, the circuit mated was entered high in the clouds and was transferred to web page server, be finally shown in user terminal computer or on mobile phone.

As shown in Figure 2, the paths planning method that the present invention is based on the trip of PM2.5 health is the dijkstra's algorithm improved, after user inputs terminus, load networks topological diagram, and hierarchical operations is carried out to complex topology figure, namely grade classification is carried out to road network, obtain the road network aspect of multiple different densities and section number, carry out data structure simplification based on sparse different aspects to complicated road network, concrete operation steps is as follows:

Step 1: according to category of roads, is split as the road network aspect of a different brackets by road network.

Step 2: initialization road network, simplifies complicated road network.Record two node road network informations with data structure (S, T, L, P), wherein S is node 1, T be node 2, L is shortest path between two nodes, and P is two node shortest paths under PM2.5 concentration optimum.

Step 3: traversal road-net node, if when L is less than certain fixed threshold (X), then give tacit consent to two nodes close, one of reject, and generating virtual section connects and rejects close two nodes of point, more newly-generated new Railway network simplification structure, fictitious line constructive process is illustrated in fig. 2 shown below.

Step 4: for same node, merges a split out a different brackets road network.

According to the position of start, end in topological diagram, set up adjacency matrix M, adjacency matrix M is reordered according to limit weight (the PM2.5 concentration value in each section) and builds adjacency list T, if T meets rectangle restriction search condition Lmax, i.e. L≤Lmax, then directly utilize dijkstra's algorithm to obtain the minimum healthy trip route of PM2.5 concentration value, concrete dijkstra's algorithm is:

$\{\begin{array}{c}{f}_i\left(t\right)=\underset{j\≠i}{\min }\left(g_{ij}\right(t)+f_j(t+g_{ij}\left(t\right)\left)\right)\\ f_N\left(t\right)=0\end{array},i=1,2,\mathrm{...},N-1$

In formula, g _ijt () is the PM2.5 concentration value sequence of t from node i to j; f _it () is the optimum PM2.5 concentration value sequence of t from i to terminal.

If L < is Lmax, then first with starting point (x ₁, y ₁), terminal (x ₂, y ₂) build elliptic equation:

$\frac{{\&lsqb;cos\mathrm{\&theta;}(x-a)+sin\mathrm{\&theta;}(y-b)\&rsqb;}^2}{A^2}+\frac{{\&lsqb;-sin\mathrm{\&theta;}(x-a)+cos\mathrm{\&theta;}(y-b)\&rsqb;}^2}{B^2}=1$

In formula,

$\mathrm{\&theta;}=arctg\left(\frac{y_2-y_1}{x_2-x_1}\right);$

$a=\frac{x_1+x_2}{2};$

$b=\frac{y_1+y_2}{2};$

$A=\frac{\mathrm{\&tau;}}{2}\sqrt{{(y_2-y_1)}^2+{(x_2-x_1)}^2};$

$B=\sqrt{A^2-\frac{{(y_2-y_1)}^2+{(x_2-x_1)}^2}{4}}$

Ask local derviation to x, y again, obtaining coordinate is to the extreme (x _max, y _max), (x _min, y _min), (x _max, y _min), (x _min, y _max) restriction search rectangular region, as shown in Figure 3.

Wherein,

$x_{max}=a+\sqrt{A^2{\cos }^2\mathrm{\&theta;}+B^2{\sin }^2\mathrm{\&theta;}}$

$x_{min}=a-\sqrt{A^2{\cos }^2\mathrm{\&theta;}+B^2{\sin }^2\mathrm{\&theta;}}$

$y_{max}=b+\sqrt{A^2{\cos }^2\mathrm{\&theta;}+B^2{\sin }^2\mathrm{\&theta;}}$

$y_{min}=b-\sqrt{A^2{\cos }^2\mathrm{\&theta;}+B^2{\sin }^2\mathrm{\&theta;}}$

The last improvement dijkstra's algorithm calculating optimal path utilized in rectangular area based on PM2.5 concentration value path planning, that is:

$\{\begin{array}{c}{f}_i\left(t\right)=\underset{j\&NotEqual;i}{\min }\left(g_{ij}\right(t)+f_j(t+g_{ij}\left(t\right)\left)\right)\\ f_N\left(t\right)=0\end{array},i=1,2,\mathrm{...},N-1$

In formula, g _ijt () is the PM2.5 concentration value sequence of t from node i to j; f _it () is the optimum PM2.5 concentration value sequence of t from i to terminal, N is destination county node.

Claims (5)

1., based on a path planning apparatus for PM2.5 health trip, it is characterized in that: comprise vehicle-mounted PM2.5 checkout equipment, information transmission modular and server terminal; Wherein, information transmission modular comprises GPS module and GPRS module, and server terminal comprises path planning module, and PM2.5 checkout equipment is installed in Floating Car, and is connected with information transmission modular, and information transmission modular is connected with server terminal; PM2.5 checkout equipment Real-time Collection also records Floating Car institute through path PM2.5 value, GPS module obtains Floating Car geographical location information, the PM2.5 value of acquisition and geographical location information are transferred to the path planning module of server terminal by GPRS module, and path planning module realizes final path planning.

2. the path planning apparatus based on the trip of PM2.5 health according to claim 1, is characterized in that: the PM2.5 value detected by described information transmission modular transmission, geographic coordinate and detection time; Geographic coordinate record detect the Floating Car of PM2.5 the position of process, adopt standard latitude and longitude coordinates.

3. the path planning apparatus based on the trip of PM2.5 health according to claim 1, it is characterized in that: described path planning module adopts modified dijkstra's algorithm to realize the planning of healthy traffic path, start, end are located based on former road network structure, form the network topological diagram of Weight according to PM2.5 detected value and be reduced to oriented tax power connected graph, optimum for target traverse node with PM2.5 concentration, traversal region reduces according to search restrictive condition; When region of search meets rectangle restriction search condition, in units of node, carry out this layer of search work, after distance is greater than certain value R, improve search level, until it is highest to arrive road network; When region of search does not meet rectangle restriction search condition, change region of search is rectangular search, and again repeats with the minimum shortest path search process for target of PM2.5 concentration value, along with search level raises, and gradual perfection path planning.

4. the path planning apparatus based on the trip of PM2.5 health according to claim 1 and 2, is characterized in that: the PM2.5 value that same place does not detect in the same time need repeat record.

5., based on a paths planning method for PM2.5 health trip, it is characterized in that concrete steps are:

Step one: determine single channel section Floating Car sample size

Timing statistics section T _pin, mean P M2.5 estimated value

$\stackrel{\&OverBar;}{P}=\frac{1}{N_p}\underset{i=1}{\overset{N_p}{\&Sigma;}}{P}_i$

In formula, P _iit is the PM2.5 value of i-th Floating Car; I is Floating Car sequence number; N _pfor the Floating Car sum through section in timing statistics section;

Make M be the logarithm of PM2.5 concentration value P, namely M=In (P), carries out standardization to M, with for the upper α quantile of standard profile, then the Floating Car quantity computation model in single channel section is:

$N_p\&GreaterEqual;{\left(\frac{{\mathrm{\&sigma;}}_p}{{\mathrm{\&epsiv;}}_p}{Z}_{{\mathrm{\&alpha;}}_p/2}\right)}^2$

In formula, for upper α quantile; σ _pfor standard deviation; ε _pfor safe level error amount;

To N _pcarry out revising:

${N^{\&prime;}}_p=\frac{N_p\&CenterDot;l}{\stackrel{\&OverBar;}{M}\&CenterDot;T_p}=\frac{N_p\&CenterDot;l}{\stackrel{\&OverBar;}{In\left(P\right)}\&CenterDot;T_p}$

In formula, l is target road section length; T _pfor timing statistics;

Step 2: determine road network Floating Car sample size

The probability P that Floating Car occurs on any road _ifor:

$P_i=\frac{\underset{j=1}{\overset{N_i}{\&Sigma;}}({\mathrm{\&rho;}}_i\&CenterDot;l_{i,j})}{\underset{i=1}{\overset{a}{\&Sigma;}}\underset{j=1}{\overset{N_i}{\&Sigma;}}({\mathrm{\&rho;}}_i\&CenterDot;l_{i,j})},(i=1,2,\mathrm{...},a)$

In formula, a is category of roads number, is constant; N _ifor type i road sum; ρ _ifor i road traffic current density; l _i,jfor jth section section r in type i road _i,jlength;

Floating Car is jth section section r in type i road _i,jthe probability P of upper appearance _i,jfor:

$P_{i,j}=\frac{P_i\&CenterDot;l_{i,j}}{\underset{j=1}{\overset{N_i}{\&Sigma;}}{l}_{i,j}}$

Revision P _i,jfor:

P′ _i，j＝P _i,j(1-P _s)(1-P _c)

In formula, P _sfor Floating Car unoperating rate; P _cfor Floating Car error rate,

Floating Car quantity computation model under whole road network is:

$N_z=\underset{i=1}{\overset{a}{\&Sigma;}}(Z_i\&CenterDot;N_{z,i})$

In formula, N _z,ifloating Car number needed for i type road, can utilize step one to try to achieve; Z _ifor the factor of influence of different types of road, computing method are:

$Z_i=\frac{\underset{j=1}{\overset{N_i}{\&Sigma;}}{l}_{i,j}}{\underset{i=1}{\overset{a}{\&Sigma;}}\underset{j=1}{\overset{N_i}{\&Sigma;}}{l}_{i,j}}$

Step 3: according to PM2.5 concentration value sequence path planning

At starting point (x ₁, y ₁), terminal (x ₂, y ₂) determine after, set up restriction search rectangular area:

$\frac{{\&lsqb;cos\mathrm{\&theta;}(x-a)+sin\mathrm{\&theta;}(y-b)\&rsqb;}^2}{A^2}+\frac{{\&lsqb;-sin\mathrm{\&theta;}(x-a)+cos\mathrm{\&theta;}(y-b)\&rsqb;}^2}{B^2}=1$

In formula,

$\mathrm{\&theta;}=arctg\left(\frac{y_2-y_1}{x_2-x_1}\right);$

$a=\frac{x_1+x_2}{2};$

$b=\frac{y_1+y_2}{2};$

$A=\frac{\mathrm{\&tau;}}{2}\sqrt{{(y_2-y_1)}^2+{(x_2-x_1)}^2};$

$B=\sqrt{A^2-\frac{{(y_2-y_1)}^2+{(x_2-x_1)}^2}{4}}$

Local derviation is asked to x, y, obtains the extreme value x of x, y _min, x _max, y _min, y _max, limit coordinate (x _max, y _max), (x _min, y _min), (x _max, y _min), (x _min, y _max) rectangular area of 4 composition restriction search;

Wherein,

$x_{max}=a+\sqrt{A^2{\cos }^2\mathrm{\&theta;}+B^2{\sin }^2\mathrm{\&theta;}}$

$x_{min}=a-\sqrt{A^2{\cos }^2\mathrm{\&theta;}+B^2{\sin }^2\mathrm{\&theta;}}$

$y_{max}=b+\sqrt{A^2{\cos }^2\mathrm{\&theta;}+B^2{\sin }^2\mathrm{\&theta;}}$

$y_{min}=b-\sqrt{A^2{\cos }^2\mathrm{\&theta;}+B^2{\sin }^2\mathrm{\&theta;}}$

Optimum for target traverses network topological node with PM2.5 in restriction search rectangular region, obtain optimal path, i.e. constructing environment optimal path objective optimization function:

$\left\{\begin{array}{c}f\left(t\right)=\underset{j\&NotEqual;i}{\min }\left(g_{ij}\right(t)+f_j(t+g_{ij}\left(t\right)\left)\right)\\ f_N\left(t\right)=0\end{array}\right.,i=1,2,\mathrm{...},N-1$

In formula, g _ijt () is the PM2.5 concentration value of t from node i to j; f _it () is the optimum PM2.5 concentration value of t from i to terminal, N is destination county node.