CN104537229A - Road network building and evolving method improving travel efficiency - Google Patents

Abstract

The invention relates to a road network building and evolving method improving travel efficiency. The method includes the following steps that 1, an initial road network is built with the connection degree between nodes serves as a standard; 2, an update scheme is selected for the built road network, the road network is updated according to the selected scheme, and it is guaranteed that all roads in the updated road network meet the requirements of the three-grade service level. According to the method, travel behaviors of travelers are fully considered, a road network structure and a grade configuration method are disclosed with meeting travel requirements and improving travel efficiency as driving force,, effective road resources can be fully used, and travel time can be shortened to the largest extent.

Description

A kind of road network line efficiency that improves builds evolution method

Technical field

The invention belongs to highway network planning field, be specifically related to a kind of road network line efficiency that improves and build evolution method.

Background technology

Whether rationally distributed road net structure is, directly affects the performance of road network allomeric function.Therefore, being necessary the factor from affecting transportation supplies root, inquiring into rational road net structure layout.City road traffic system is as a kind of Dissipative Structure System, and System Development is the evolution of self-organization and hetero-organization compound action, is irregular, the accidental process caused by specific economy, society or political strength.

At present about the research of road network structure, wherein a class is inquired into from the angle setting up Optimized model mostly, as set up the road network structure layout optimization model minimum with the quantity delivered of urban road area resource, the travel time is the shortest, road network Maximum Traffic Capacity is target.Another kind of research thinks that certain mechanism of Evolution is followed in the formation of road net, there is the development that a kind of invisible strength dominates system, but its driving factors are angularly considered from economic benefit, operation cost mostly, do not consider that traveler is to the requirement going out line efficiency.

Summary of the invention

The change procedure of actual road network is paid close attention in the research of existing road network structure, take time shaft as research direction, carry out trend comparative analysis, the internal mechanism that road network structure develops is not proposed, the developing direction in road network future cannot be inferred, for defect of the prior art and deficiency, the present invention aims to provide a kind of road network and builds and evolution method, from traveler angle, to meet trip requirements for focus, that effectively can improve traveler goes out line efficiency, for administrative authority carry out road network structure adjustment and grade provide a kind of effective method.

" node " described in the present invention represents city, is called between two nodes " road " without the connection of the 3rd node, is called between two nodes in " section " through the road of the 3rd node, and the set of all roads is " road network "; Category of roads of the present invention is divided into highway, one-level road, second grade highway, tertiary road and level Four road, and the grade of highway is the highest, and be then one-level road, second grade highway, tertiary road successively, the grade on level Four road is minimum;

For achieving the above object, the technical scheme that the present invention takes is:

Improve the road network line efficiency and build an evolution method, to obtain the minimum travel time for starting point, build intercity road network and plan, node represents city, total N number of node, N be more than or equal to 2 natural number, with K _iand K _jrepresent arbitrary node, i=1,2,3 ... N, j=1,2,3 ... N, and i ≠ j, the method comprises the following steps:

Step one: build road network

The trip data of the N number of node of 1.1 collection, computing node K _iwith node K _jbetween Connected degree , select and node K _ithe node K that Connected degree is maximum _i.max, connected node K _iwith node K _i.maxobtain road ;

The trip data of described node comprises:

E _g: the equal total output value of node g people, hundred million yuan;

M _g: node g population, ten thousand people;

B _g: node g daily goes on a journey number of times, times/day;

α _g: node g motor bus trip proportion;

β _g: node g car trip ratio;

conversion coefficient between motor bus and car,

R: the average seating capacity of motor bus, r=35;

μ _g: the trans-city trip proportion of node g resident;

F: wagon flow peak hour factor, F=0.1;

G _g: node g goes on a journey generation, people/sky;

P _g: node g trip attraction amount, people/sky;

D _gg': the length of road between node g and node g', km;

θ＝-0.3026；

τ ₁represent trip generation weight, τ ₁=0.2;

τ ₂represent trip traffic attraction weight, τ ₂=0.2;

τ ₃indicate line efficiency weight, τ ₃=0.6;

G=K _ior K _j, g'=K _ior K _j, and g ≠ g';

Described node K _iwith node K _jbetween Connected degree be formulated as:

${\mathrm{\λ}}_{K_i.K_j}=\frac{\exp \left({\mathrm{\δ}}_{K_i}\right)}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\exp \left({\mathrm{\δ}}_{K_i}\right)}\·\frac{\exp \left({\mathrm{\δ}}_{K_j}\right)}{\underset{j=1}{\overset{N}{\mathrm{\Σ}}}\exp \left({\mathrm{\δ}}_{K_j}\right)}$ Formula (1)

In formula (1):

represent node K _iglamour degree, ${\mathrm{\δ}}_{K_i}=\ln \underset{j=1}{\overset{N}{\mathrm{\Σ}}}\exp \left[\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(w_{K_i{K}_j}-w_{K_j{K}_i})\right],$

represent node K _jglamour degree, ${\mathrm{\δ}}_{K_j}=\ln \underset{i=1}{\overset{N}{\mathrm{\Σ}}}\exp \left[\frac{1}{N}\underset{j=1}{\overset{N}{\mathrm{\Σ}}}(w_{K_j{K}_i}-w_{K_i{K}_j})\right],$

represent node K _iwith node K _jbetween effectiveness, $W_{K_i.K_j}={\mathrm{\τ}}_1{G}_{K_i}^{\′}+{\mathrm{\τ}}_2{P}_{K_j}^{\′}+{\mathrm{\τ}}_3{d}_{K_i.K_j}^{\′},$

represent node K _jwith node K _ibetween effectiveness, $W_{K_j.K_i}={\mathrm{\τ}}_1{G}_{K_j}^{\′}+{\mathrm{\τ}}_2{P}_{K_i}^{\′}+{\mathrm{\τ}}_3{d}_{K_j.K_i}^{\′};$

G ' _kirepresent node K _itrip generation nondimensionalization,

G' _kjrepresent node K _jtrip generation nondimensionalization,

$G_{K_j}=M_{K_j}\·b_{K_j}\·({\mathrm{\α}}_{K_j}\·\frac{\mathrm{\φ}}{r}+{\mathrm{\β}}_{K_j})\·{\mathrm{\μ}}_{K_j}\·F,$

represent node K _jtrip attraction amount nondimensionalization;

$P_{K_j}=\frac{E_{K_j}\·M_{K_j}}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{E}_{K_i}\·M_{K_i}}\·\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{G}_{K_i};$

represent node K _itrip attraction amount nondimensionalization;

$P_{K_i}=\frac{E_{K_i}\·M_{K_i}}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{E}_{K_i}\·M_{K_i}}\·\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{G}_{K_i};$

represent node K _iwith node K _jbetween road go out line efficiency,

$d_{K_i.K_j}^{\′}={d^{\′}}_{K_j.K_i};$

1.2 judge and node K _ithe road number connected:

When with node K _iwhen the road connected has more than two, carry out step 2;

When with node K _iwhen the road connected has and only has one, then connect and node K again _ithe secondary large node K of Connected degree _i.sedobtain road , carry out step 2;

Road network is formed by the road set obtained in step 1.1 and step 1.2;

Step 2: select update scheme to upgrade road network

2.1 select update scheme:

2.1.1 the whole roads in the road network obtained step one carry out Stochastic Equilibrium traffic assignation, are obtained the saturation degree of every bar road in road network by Monte Carlo method, represent the road that saturation degree is maximum, road the node connected is respectively node K _max.1with node K _max.2;

2.1.2 parameter represent road the road network total travel time obtained when promoting one-level category of roads, parameter T _max.1represent increase by and node K _max.1total travel time of road network during the road connected, parameter T _max.2represent increase by and node K _max.2total travel time of road network during the road connected, total travel time of road network is the summation of the travel time of every bar road in road network, represent road travel time,

$t_{K_{\max }}=\frac{d_{A_{K_{\max }}}}{V_{A_{K_{\max }}}^0}(1+0.15*{Y_{A_{K_{\max }}}}^4)$ Formula (2)

In formula (2): represent road design rate, km/h, represent road saturation degree, represent road length, km;

Work as road category of roads when being highest, then parameter do not exist, otherwise parameter exist; When do not exist in road network not with node K _max.1during the node connected, parameter T _max.1do not exist, otherwise parameter T _max.1exist; When do not exist in road network not with node K _max.2during the node connected, parameter T _max.2do not exist, otherwise parameter T _max.2exist;

Work as existence , T _max.1and T _max.2in a parameter time, perform exist parameter corresponding 2.2 in update scheme;

Work as existence , T _max.1and T _max.2in plural parameter, perform minimum parameter corresponding 2.2 in update scheme;

When minimum parameter has two or more, road minimum number or update scheme corresponding to the minimum parameter of category of roads is selected to upgrade road network;

2.2 pairs of road networks upgrade

2.2.1 parameter corresponding update scheme is by road category of roads promote one-level;

Parameter T _max.1corresponding update scheme is: in road network not with node K _max.1the node connected is K _1.n, n=1,2,3 ... N-2, connected node K _max.1with node K _1.n, obtain road ;

Parameter T _max.2corresponding update scheme is: in road network not with node K _max.2the node connected is K _2.n, n=1,2,3 ... N-2, connected node K _max.2with node K _2.nobtain road ;

2.2.2 calculated the saturation degree of every bar road in the road network after upgrading by Monte Carlo method, the saturation degree of every bar road is carried out to the judgement of service level;

For highways all in road network, when the saturation degree wherein having highway is greater than 0.88, return 2.1 and 2.2.1 continue road network is upgraded;

For one-level roads all in road network, when the saturation degree wherein having one-level road is greater than 0.8, return 2.1 and 2.2.1 continue road network is upgraded;

For second grade highway all in road network, tertiary road or level Four road, when wherein there being second grade highway, the saturation degree on tertiary road or level Four road is when being greater than 0.64, return 2.1 and 2.2.1 continue to upgrade road network;

Otherwise, complete road network and upgrade.

Further, the road in the 2.1.2 of described step 2 saturation degree computing formula be:

$Y_{A_{K_{\max }}}=\frac{f_{A_{K_{\max }}}}{C_{A_{K_{\max }}}}$ Formula (3)

In formula (3): represent road the volume of traffic obtained after Stochastic Equilibrium traffic assignation, represent road the traffic capacity.

Compared with prior art, the invention has the beneficial effects as follows:

(1) taken into full account the travel behaviour of traveler, to meet trip requirements, providing line efficiency is driving force, proposes the method for network of highways structure and grade configuration, can make full use of effective path resource, farthest reduce the travel time;

(2) change procedure of actual road network is paid close attention in the research of existing road network structure, take time shaft as research direction, carry out trend comparative analysis, the internal mechanism that road network structure develops is not proposed, the developing direction in road network future cannot be inferred, by road network renewal iteration gradually in the present invention, carried out road network and upgraded the prediction of developing, more can accurately show that travel time the shortest road network builds, carry out road network structure adjustment for administrative authority and grade provides a kind of effective method.

Accompanying drawing explanation

Fig. 1 is that road network of the present invention builds evolution method process flow diagram;

Fig. 2 is that 8 intercity road networks build evolutionary process schematic diagram;

" Z " in Fig. 2 represents iterations, and numeral 1 ~ 8 represents 8 different cities respectively,

"------" represents level Four road, "----" represent tertiary road, "-.-.-. " represents second grade highway, and "------" represents one-level road, " ... ... " represent highway;

Below in conjunction with the drawings and the specific embodiments, the present invention is described in detail.

Embodiment

K _i.maxrepresent and node K _ithe node that Connected degree is maximum, i.max ≠ i, K _i.sedrepresent and node K _ithe node that Connected degree is second largest, i.sed ≠ i, and ;

represent that after carrying out Stochastic Traffic Assignment, maximum road is embezzled and spent to road network, K _max.1represent road on a node, K _max.2represent road on another one node.

The traffic capacity refers under certain road and transportation condition, the maximum vehicle number by a certain section in the unit interval of a certain section on road.

City: the city chosen is that population is greater than 1,000,000 people cities.

The present invention treats each intercity trip data setting up road network and collects, and by calculating Connected degree, by the standard of Connected degree to each intercity connection, obtains initial road network; The saturation degree that Stochastic Equilibrium traffic assignation obtains every bar road is carried out to the initial road network obtained, the road maximum to saturation degree upgrades, update scheme comprises the node promoting category of roads with being connected other, if there is the node do not connected, update scheme has two kinds, by the standard of the shortest travel time, road is upgraded, then the road in the road network after renewal is carried out to the judgement of grade of service level, until the grade of all roads all meets three grades of service standards.

" node " described in the present invention represents city, is called between two nodes " road " without the connection of the 3rd node, is called between two nodes in " section " through the road of the 3rd node, and the set of all roads is " road network "; Category of roads of the present invention is divided into highway, one-level road, second grade highway, tertiary road and level Four road, and the grade of highway is the highest, and be then one-level road, second grade highway, tertiary road successively, the grade on level Four road is minimum;

Motor bus: refer to long more than 10 meters of vehicle body, more than 20, seat, is generally more than or equal to 7 row's seats.

Car: seating capacity, within 7, is generally less than and equals 3 row's seats.

In highway, the road of the lowest class is level Four road, in order to understand the grade situation of change step by step of road network in simulation process, so the road in the initial road network built is set as the lowest class, improve constantly by category of roads the evolutionary process reflecting road network;

In the present invention, the renewal of road network is each time called an iteration.

In order to a kind of road network line efficiency that improves of the present invention of description clearly builds evolution method, be specifically described below in conjunction with Figure of description and embodiment.

Embodiment 1:

Composition graphs 1, the road network that the raising of the present embodiment goes out line efficiency builds evolution method and is, a kind of road network line efficiency that improves builds evolution method, to obtain the minimum travel time for starting point, build intercity road network and plan, node represents city, total N number of node, N be more than or equal to 2 natural number, with K _iand K _jrepresent arbitrary node, i=1,2,3 ... N, j=1,2,3 ... N, and i ≠ j, the method comprises the following steps:

Step one: build road network

The trip data of the N number of node of 1.1 collection, computing node K _iwith node K _jbetween Connected degree , select and node K _ithe node K that Connected degree is maximum _i.max, connected node K _iwith node K _i.maxobtain road ;

The trip data of described node comprises:

E _g: the equal total output value of node g people, hundred million yuan;

M _g: node g population, ten thousand people;

B _g: node g daily goes on a journey number of times, times/day;

α _g: node g motor bus trip proportion;

β _g: node g car trip ratio;

: the conversion coefficient between motor bus and car, ;

R: the average seating capacity of motor bus, r=35;

μ _g: the trans-city trip proportion of node g resident;

F: wagon flow peak hour factor, F=0.1;

G _g: node g goes on a journey generation, people/sky;

P _g: node g trip attraction amount, people/sky;

D _gg': the length of road between node g and node g', km;

θ＝-0.3026；

τ ₁represent trip generation weight, τ ₁=0.2;

τ ₂represent trip traffic attraction weight, τ ₂=0.2;

τ ₃indicate line efficiency weight, τ ₃=0.6;

G=K _ior K _j, g'=K _ior K _j, and g ≠ g';

Described node K _iwith node K _jbetween Connected degree be formulated as:

${\mathrm{\λ}}_{K_i.K_j}=\frac{\exp \left({\mathrm{\δ}}_{K_i}\right)}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\exp \left({\mathrm{\δ}}_{K_i}\right)}\·\frac{\exp \left({\mathrm{\δ}}_{K_j}\right)}{\underset{j=1}{\overset{N}{\mathrm{\Σ}}}\exp \left({\mathrm{\δ}}_{K_j}\right)}$ Formula (1)

In formula (1):

represent node K _iglamour degree, ${\mathrm{\δ}}_{K_i}=\ln \underset{j=1}{\overset{N}{\mathrm{\Σ}}}\exp \left[\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(w_{K_i{K}_j}-w_{K_j{K}_i})\right],$

represent node K _jglamour degree, ${\mathrm{\δ}}_{K_j}=\ln \underset{i=1}{\overset{N}{\mathrm{\Σ}}}\exp \left[\frac{1}{N}\underset{j=1}{\overset{N}{\mathrm{\Σ}}}(w_{K_j{K}_i}-w_{K_i{K}_j})\right],$

represent node K _iwith node K _jbetween effectiveness, $W_{K_i.K_j}={\mathrm{\τ}}_1{G}_{K_i}^{\′}+{\mathrm{\τ}}_2{P}_{K_j}^{\′}+{\mathrm{\τ}}_3{d}_{K_i.K_j}^{\′},$

represent node K _jwith node K _ibetween effectiveness, $W_{K_j.K_i}={\mathrm{\τ}}_1{G}_{K_j}^{\′}+{\mathrm{\τ}}_2{P}_{K_i}^{\′}+{\mathrm{\τ}}_3{d}_{K_j.K_i}^{\′};$

G ' _kirepresent node K _itrip generation nondimensionalization,

G' _kjrepresent node K _jtrip generation nondimensionalization,

$G_{K_j}=M_{K_j}\·b_{K_j}\·({\mathrm{\α}}_{K_j}\·\frac{\mathrm{\φ}}{r}+{\mathrm{\β}}_{K_j})\·{\mathrm{\μ}}_{K_j}\·F,$

represent node K _jtrip attraction amount nondimensionalization;

$P_{K_j}=\frac{E_{K_j}\·M_{K_j}}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{E}_{K_i}\·M_{K_i}}\·\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{G}_{K_i};$

represent node K _itrip attraction amount nondimensionalization;

$P_{K_i}=\frac{E_{K_i}\·M_{K_i}}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{E}_{K_i}\·M_{K_i}}\·\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{G}_{K_i};$

represent node K _iwith node K _jbetween road go out line efficiency,

$d_{K_i.K_j}^{\′}={d^{\′}}_{K_j.K_i};$

1.2 judge and node K _ithe road number connected:

When with node K _iwhen the road connected has more than two, carry out step 2;

When with node K _iwhen the road connected has and only has one, then connect and node K again _ithe secondary large node K of Connected degree _i.sedobtain road , carry out step 2;

Road network is formed by the road set obtained in step 1.1 and step 1.2;

Step 2: select update scheme to upgrade road network

2.1 select update scheme:

2.1.1 the whole roads in the road network obtained step one carry out Stochastic Equilibrium traffic assignation, are obtained the saturation degree of every bar road in road network by Monte Carlo method,

For node K _iwith node K _j, road represent node K _iwith node K _jbetween road and the set in section.During every sub-distribution, according to travel time , by node K _iwith node K _jbetween whole volume of traffic be assigned to node K _iwith node K _jtravel time minimum road or section on, $q_{K_i{K}_j}=\frac{G_{K_i}\·P_{K_j}\·e^{-{\mathrm{\θd}}_{K_i{K}_j}}}{\underset{j=1}{\overset{N}{\mathrm{\Σ}}}{e}^{-{\mathrm{\θd}}_{K_i{K}_j}}\·P_{K_j}},$ represent that l sub-distribution is to road on the volume of traffic, represent l sub-distribution volume of traffic posterior nodal point K _iwith node K _jbetween road and section on average traffic,

${\stackrel{\‾}{X}}_{l.A_{K_i.K_j}}=[(l-1){\stackrel{\‾}{X}}_{(l-1).A_{K_i.K_j}}+X_{l.A_{K_i.K_j}}]/l$

As node K _iwith node K _jall roads and section all be less than K value, K is according to required precision value, and present case gets 0.25 when distributing, then Traffic growth rate stops, otherwise proceeds Traffic growth rate;

be the standard deviation of the l time Traffic growth rate,

$S_{l.A_{K_i.K_j}}=\sqrt{\frac{1}{l(l-1)}\underset{m=1}{\overset{l}{\mathrm{\Σ}}}{(X_{m.A_{K_i.K_j}}-{\stackrel{\‾}{X}}_{l.A_{K_i.K_j}})}^2};$

The saturation degree of every bar road in road network is obtained, the road maximum to saturation degree by above-mentioned Monte Carlo method upgrade, road the node connected is respectively node K _max.1with node K _max.2:

represent the road that saturation degree is maximum, road the node connected is respectively node K _max.1with node K _max.2;

2.1.2 parameter represent road the road network total travel time obtained when promoting one-level category of roads, parameter T _max.1represent increase by and node K _max.1total travel time of road network during the road connected, parameter T _max.2represent increase by and node K _max.2total travel time of road network during the road connected, total travel time of road network is the summation of the travel time of every bar road in road network, represent road travel time,

$t_{K_{\max }}=\frac{d_{A_{K_{\max }}}}{V_{A_{K_{\max }}}^0}(1+0.15*{Y_{A_{K_{\max }}}}^4)$ Formula (2)

In formula (2): represent road design rate, km/h, represent road saturation degree, represent road length, km;

Road in formula (2) saturation degree computing formula be:

$Y_{A_{K_{\max }}}=\frac{f_{A_{K_{\max }}}}{C_{A_{K_{\max }}}}$ Formula (3)

In formula (3): represent road the volume of traffic obtained after Stochastic Equilibrium traffic assignation, represent road the traffic capacity;

Work as road category of roads when being highest, then parameter do not exist, otherwise parameter exist; When do not exist in road network not with node K _max.1during the node connected, parameter T _max.1do not exist, otherwise parameter T _max.1exist; When do not exist in road network not with node K _max.2during the node connected, parameter T _max.2do not exist, otherwise parameter T _max.2exist;

Work as existence , T _max.1and T _max.2in a parameter time, perform exist parameter corresponding 2.2 in update scheme;

Work as existence , T _max.1and T _max.2in plural parameter, perform minimum parameter corresponding 2.2 in update scheme;

When minimum parameter has two or more, road minimum number or update scheme corresponding to the minimum parameter of category of roads is selected to upgrade road network;

2.2 pairs of road networks upgrade

2.2.1 parameter corresponding update scheme is by road category of roads promote one-level;

Parameter T _max.1corresponding update scheme is: in road network not with node K _max.1the node connected is K _1.n, n=1,2,3 ... N-2, connected node K _max.1with node K _1.n, obtain road ;

Parameter T _max.2corresponding update scheme is: in road network not with node K _max.2the node connected is K _2.n, n=1,2,3 ... N-2, connected node K _max.2with node K _2.nobtain road ;

2.2.2 calculated the saturation degree of every bar road in the road network after upgrading by Monte Carlo method, the saturation degree of every bar road is carried out to the judgement of service level;

For highways all in road network, when the saturation degree wherein having highway is greater than 0.88, return 2.1 and 2.2.1 continue road network is upgraded;

For one-level roads all in road network, when the saturation degree wherein having one-level road is greater than 0.8, return 2.1 and 2.2.1 continue road network is upgraded;

For second grade highway all in road network, tertiary road or level Four road, when wherein there being second grade highway, the saturation degree on tertiary road or level Four road is when being greater than 0.64, return 2.1 and 2.2.1 continue to upgrade road network;

Otherwise, complete road network and upgrade.

Embodiment 2:

Composition graphs 2 illustrates embodiment of the present invention: " city " in the present embodiment is " node ".

Target cities in the present embodiment has 8, illustrates the building process of this road network below in conjunction with accompanying drawing.

(1) collect the trip parameter value obtaining 8 cities in the present embodiment, each trip parameter value is in table 1, table 2 and table 3;

The population in table 18 city and GDP

City is numbered	1	2	3	4	5	6	7	8
									Population (M, ten thousand people)	132	210	318	222	282	504	210	156
GDP (E, hundred million yuan)	1110	2230	1030	1180	1400	3800	650	400

The sunrise places number in table 28 city

City is numbered	1	2	3	4	5	6	7	8
									Trip number of times (b, times/day)	0.9	0.7	0.8	1.1	1	1.2	0.7	0.5

Table 38 city other go out line parameter

(2) initial road network is set up, and go out line parameter in conjunction with what collect, 8 intercity Connected degree result of calculations are in table 4;

Table 48 city Connected degree result of calculation

Each point Connected degree	1	2	3	4	5	6	7	8
									1	/	0.16050	0.20433	0.13918	0.11984	0.09573	0.01037	0.00489
2	0.16050	/	0.15411	0.07509	0.17521	0.10125	0.01472	0.01827
									3	0.20433	0.15411	/	0.11365	0.29430	0.22869	0.04760	0.02853
4	0.13918	0.07509	0.11365	/	0.08677	0.34849	0.06320	0.03127
									5	0.11984	0.17521	0.29430	0.08677	/	0.47553	0.14006	0.19582
6	0.09573	0.10125	0.22869	0.34849	0.47553	/	0.29630	0.21744
									7	0.01037	0.01472	0.04760	0.06320	0.14006	0.29630	/	0.15885
8	0.00489	0.01827	0.02853	0.03127	0.19582	0.21744	0.15885	/

Obtaining initial road network by the result of calculation in upper table is 6-5-3-6-4-1-3-2-5-7-6-8-5, and be the initial road network in the Z=1 figure in Fig. 2, all roads are level Four road.

(3) evolutionary process, adopt matlab programming, build evolution method to road network of the present invention to simulate, represent the number of times of iteration in Fig. 2 with Z, each time the renewal of road network, just be called an iteration, through 49 iteration, obtain steady state (SS) road network, the saturation degree of each bar road all meets the requirement of three grades of service levels, in the evolutionary process of road network, road network structure corresponding to evolution number of times Z as shown in Figure 2.

The appearance that the evolution method that the present invention proposes demonstrates road network structure is the result of internal system Self-organization Evolution, in this approach as the Main Basis of road network structure planning, can make full use of path resource, and that effectively improves traveler goes out line efficiency.

Claims (2)

1. improve the road network line efficiency and build an evolution method, it is characterized in that, to obtain the minimum travel time for starting point, build intercity road network and plan, node represents city, total N number of node, N be more than or equal to 2 natural number, with K _iand K _jrepresent arbitrary node, i=1,2,3 ... N, j=1,2,3 ... N, and i ≠ j, the method comprises the following steps:

Step one: build road network

The trip data of the N number of node of 1.1 collection, computing node K _iwith node K _jbetween Connected degree select and node K _ithe node K that Connected degree is maximum _i.max, connected node K _iwith node K _i.maxobtain road

The trip data of described node comprises:

E _g: the equal total output value of node g people, hundred million yuan;

M _g: node g population, ten thousand people;

B _g: node g daily goes on a journey number of times, times/day;

α _g: node g motor bus trip proportion;

β _g: node g car trip ratio;

conversion coefficient between motor bus and car,

R: the average seating capacity of motor bus, r=35;

μ _g: the trans-city trip proportion of node g resident;

F: wagon flow peak hour factor, F=0.1;

G _g: node g goes on a journey generation, people/sky;

P _g: node g trip attraction amount, people/sky;

D _gg': the length of road between node g and node g', km;

θ＝-0.3026；

τ ₁represent trip generation weight, τ ₁=0.2;

τ ₂represent trip traffic attraction weight, τ ₂=0.2;

τ ₃indicate line efficiency weight, τ ₃=0.6;

G=K _ior K _j, g'=K _ior K _j, and g ≠ g';

Described node K _iwith node K _jbetween Connected degree be formulated as:

${\mathrm{\λ}}_{K_i\·K_j}=\frac{\exp \left({\mathrm{\δ}}_{K_i}\right)}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\exp \left({\mathrm{\δ}}_{K_i}\right)}\·\frac{\exp \left({\mathrm{\δ}}_{K_j}\right)}{\underset{j=1}{\overset{N}{\mathrm{\Σ}}}\exp \left({\mathrm{\δ}}_{K_j}\right)}$ Formula (1)

In formula (1):

represent node K _iglamour degree, ${\mathrm{\δ}}_{K_i}=\ln \underset{j=1}{\overset{N}{\mathrm{\Σ}}}\exp \left[\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}(w_{K_i{K}_j}-w_{K_j{K}_i})\right],$

represent node K _jglamour degree, ${\mathrm{\δ}}_{K_j}=\ln \underset{i=1}{\overset{N}{\mathrm{\Σ}}}\exp \left[\frac{1}{N}\underset{j=1}{\overset{N}{\mathrm{\Σ}}}(w_{K_j{K}_i}-w_{K_i{K}_j})\right],$

represent node K _iwith node K _jbetween effectiveness, $W_{K_i\·K_j}={\mathrm{\τ}}_1{G}_{K_i}^{\′}+{\mathrm{\τ}}_2{P}_{K_j}^{\′}+{\mathrm{\τ}}_3{d}_{K_i\·K_j}^{\′},$

represent node K _jwith node K _ibetween effectiveness, $W_{K_j\·K_i}={\mathrm{\τ}}_1{G}_{K_j}^{\′}+{\mathrm{\τ}}_2{P}_{K_i}^{\′}+{\mathrm{\τ}}_3{d}_{K_j\·K_i}^{\′},$

G ' _kirepresent node K _itrip generation nondimensionalization,

G' _kjrepresent node K _jtrip generation nondimensionalization, $G_{K_j}=M_{K_j}\·b_{K_j}\·({\mathrm{\α}}_{K_j}\·\frac{\mathrm{\φ}}{r}+{\mathrm{\β}}_{K_j})\·{\mathrm{\μ}}_{K_j}\·F,$

represent node K _jtrip attraction amount nondimensionalization; $P_{K_j}=\frac{E_{K_j}\·M_{K_j}}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{E}_{K_i}\·M_{K_i}}\·\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{G}_{K_i};$

represent node K _itrip attraction amount nondimensionalization; $P_{K_i}=\frac{E_{K_i}\·M_{K_i}}{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{E}_{K_i}\·M_{K_i}}\·\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{G}_{K_i};$

represent node K _iwith node K _jbetween road go out line efficiency, $d_{K_i\·K_j}^{\′}={d^{\′}}_{K_j\·K_i};$

1.2 judge and node K _ithe road number connected:

When with node K _iwhen the road connected has more than two, carry out step 2;

When with node K _iwhen the road connected has and only has one, then connect and node K again _ithe secondary large node K of Connected degree _i.sedobtain road carry out step 2;

Road network is formed by the road set obtained in step 1.1 and step 1.2;

Step 2: select update scheme to upgrade road network

2.1 select update scheme:

2.1.1 the whole roads in the road network obtained step one carry out Stochastic Equilibrium traffic assignation, are obtained the saturation degree of every bar road in road network by Monte Carlo method, represent the road that saturation degree is maximum, road the node connected is respectively node K _max.1with node K _max.2;

2.1.2 parameter represent road the road network total travel time obtained when promoting one-level category of roads, parameter T _max.1represent increase by and node K _max.1total travel time of road network during the road connected, parameter T _max.2represent increase by and node K _max.2total travel time of road network during the road connected, total travel time of road network is the summation of the travel time of every bar road in road network, represent road travel time,

$t_{K_{\max }}=\frac{d_{A_{K_{\max }}}}{V_{A_{K_{\max }}}^0}(1+0.15*{Y_{A_{K_{\max }}}}^4)$ Formula (2)

In formula (2): represent road design rate, km/h, represent road saturation degree, represent road length, km;

Work as road category of roads when being highest, then parameter do not exist, otherwise parameter exist; When do not exist in road network not with node K _max.1during the node connected, parameter T _max.1do not exist, otherwise parameter T _max.1exist; When do not exist in road network not with node K _max.2during the node connected, parameter T _max.2do not exist, otherwise parameter T _max.2exist;

Work as existence t _max.1and T _max.2in a parameter time, perform exist parameter corresponding 2.2 in update scheme;

Work as existence t _max.1and T _max.2in plural parameter, perform minimum parameter corresponding 2.2 in update scheme;

When minimum parameter has two or more, road minimum number or update scheme corresponding to the minimum parameter of category of roads is selected to upgrade road network;

2.2 pairs of road networks upgrade

2.2.1 parameter corresponding update scheme is by road category of roads promote one-level;

Parameter T _max.1corresponding update scheme is: in road network not with node K _max.1the node connected is K _1.n, n=1,2,3 ... N-2, connected node K _max.1with node K _1.n, obtain road

Parameter T _max.2corresponding update scheme is: in road network not with node K _max.2the node connected is K _2.n, n=1,2,3 ... N-2, connected node K _max.2with node K _2.nobtain road

2.2.2 calculated the saturation degree of every bar road in the road network after upgrading by Monte Carlo method, the saturation degree of every bar road is carried out to the judgement of service level;

For highways all in road network, when the saturation degree wherein having highway is greater than 0.88, return 2.1 and 2.2.1 continue road network is upgraded;

For one-level roads all in road network, when the saturation degree wherein having one-level road is greater than 0.8, return 2.1 and 2.2.1 continue road network is upgraded;

For second grade highway all in road network, tertiary road or level Four road, when wherein there being second grade highway, the saturation degree on tertiary road or level Four road is when being greater than 0.64, return 2.1 and 2.2.1 continue to upgrade road network;

Otherwise, complete road network and upgrade.

2. improve the road network line efficiency as described in claim 1 and build evolution method, it is characterized in that, the road in the 2.1.2 of described step 2 saturation degree computing formula be:

$Y_{A_{K_{\max }}}=\frac{f_{A_{K_{\max }}}}{C_{A_{K_{\max }}}}$ Formula (3)

In formula (3): represent road the volume of traffic obtained after Stochastic Equilibrium traffic assignation, represent road the traffic capacity.