CN111402600A - Urban road network mechanism association planning method based on complex network sand heap model - Google Patents
Urban road network mechanism association planning method based on complex network sand heap model Download PDFInfo
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Abstract
The invention discloses an urban road network mechanism association planning method based on a complex network sand heap model. The method provides a sand pile avalanche model in a complex network theory, analyzes the congestion distribution condition of the urban traffic network, helps to know the congestion mechanism between traffic roads, and finds defects in the design and planning process of the urban roads. The method comprises the steps of firstly, establishing an urban road network mechanism association model, considering the traffic dispersion capacity of roads and dynamic factors having correlation effect on congestion, and reasonably considering the factors into the association model through operations such as normalization and the like; by system simulation, an evolution mechanism process of the urban road is simulated, and an evolution propagation process of congestion after the urban road is congested is presented by means of an analysis process of a sand heap model in a complex network theory, so that the rationality of design and planning of the whole urban road network is integrally known, and a scientific basis is provided for further optimization of urban road planning.
Description
Technical Field
The invention relates to the field of traffic planning and design, in particular to an urban road network mechanism association planning method based on a complex network sand heap model.
Background
With the rapid development of society and the acceleration of urbanization process, the scale of urban road networks becomes increasingly large and complex, and the problem of traffic jam becomes more and more serious. Many cities try to solve the problem of traffic congestion by means of new construction, reconstruction, road widening, traffic guidance increase and the like, but the effect is not obvious, and the reason for this is that the design of the urban roads is unreasonable and the planning is lack of scientificity. Therefore, accurate future traffic state prediction has important significance and application value for urban traffic planning and design, and has important scientific significance for improving the overall throughput of a road network and relieving traffic jam degree by designing an efficient and stable dynamic route planning method. The structural characteristics of the road network have important influence on the traffic flow transmission process, so that the deep cognition of the structure of the road network and the disclosure of the internal operation and congestion mechanism of the traffic flow have important theoretical and practical significance for the efficient and reliable traffic guidance strategy in the future.
Disclosure of Invention
The invention aims to analyze the congestion distribution condition of an urban traffic network by combining a sand pile avalanche model in a complex network theory, help to know the congestion action mechanism among traffic roads, and further help to effectively discover the defects in road design in the design and planning process of the urban roads, thereby finally optimizing an efficient urban planning road network or modifying the defects in the existing roads and improving the running efficiency of the urban roads. The technical scheme adopted by the invention is as follows:
the urban road network mechanism association planning method based on the complex network sand heap model is characterized by comprising the following steps of:
step (1): establishing a unidirectional directed network set of an urban road network, wherein the urban road network is abstracted into the unidirectional directed network set:v is a network node set, and the network node represents a traffic intersection set;
step (2): determining the self bearing capacity of each road section in the city according to the actual situation
The factor of influence of the road section i assumed to be congested in the formulas (1) and (2) on the road section connected to the rear side isThe influence factor on the left turn and the right turn isAndthe factor affecting the road section ahead isni_front,ni_left,ni_right,ni_back∈R+Indicating the front of a congested road i linkNumber of roads into which rows, left rows, right rows and rear converge, R+The system is a positive integer set, and k _ back, k _ left, k _ right and k _ front represent that k _ back roads and k _ left, k _ right and k _ front roads converge in a congested road section i;
in the formula (3), the load-bearing capacity of each road section is ηiThe length of the road i is liThe number of the one-way lanes is piThe number of the roads which are connected with the road i and move forward, left and right is n respectivelyi_front,ni_left,ni_right. The number of roads merging from the rear is ni_backThe duration of the traffic light isIn the formulae (4) and (5), lmax,tmax,pmax,The method is characterized by comprising the following steps of representing the longest road length, the longest traffic light duration, the largest one-way lane number and the largest number of roads which are connected in the planned urban road network and are in forward, backward, left and right movement.
And (3): determining dynamic congestion function y of each road sectioni(t);
In the formula (6), t is the simulation time step length;
in the formula (7), the first and second groups,the highest speed limit of the congested road i is the average running speed of the vehicles on the road iCurrent time period Ti(t) compliance withAxis of ordinate, Ti(t) is a normal distribution function of the abscissa axis.
total daily congestion times m of road ii=mi+1。
And (5): and establishing a congestion time evaluation function of each road, and evaluating the reasonability of the design of the congestion time evaluation function.
Ti TotalTotal congestion time for road i in one day:
Ti Total=mi×t(8);
the congestion time evaluation function of each road is as follows:
the following preparation work is carried out before the simulation is carried out:
A) and setting parameters: simulating a time step t; average running speed of vehicleWith the current time period Ti(t) to determine expression (7);
C) Initializing the urban traffic networkThe relevant parameters of (2): road length l of each section iiNumber p of unidirectional lanesiThe number n of the roads which are connected with the road i and move forward, left and righti_front,ni_left,ni_rightAnd the number n of roads merging behindi_backTime length of traffic lightsHighest speed limit of road iTotal daily congestion times m of road ii;
D) Determining influence factors of road sections with rear side connection on each road section i at the starting moment according to expressions (1) and (2)Left-turn and right-turn influence factorAndinfluence factor of road section ahead
E) Calculating the bearing capacity η of each road section at the starting moment according to the expression (3)iAnd normalizing the same into the same according to (4) and (5)
F) Calculating a congestion function y of each road i at the initial moment according to an expression (6)i(t);
the simulation step circularly carries out the steps D) to G) according to the step length t);
calculating the total congestion times m of the road i in the whole day according to the judgment conditioniAnd calculating the total congestion time T of the road i in one day according to the expressions (8) and (9)i TotalAnd congestion time evaluation function
According to the total congestion time T of the road i in one dayi TotalAnd congestion time evaluation functionAnd calculating a result, and evaluating the total congestion condition of the urban road design.
The method is combined with a sand pile avalanche model in a complex network theory, analyzes the congestion distribution condition of the urban traffic network, helps to know the congestion action mechanism among the traffic roads, further helps to effectively discover the defects in the road design in the design and planning process of the urban roads, thereby finally optimizing an efficient urban planning road network or modifying the defects in the existing roads and improving the running efficiency of the urban roads.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The invention provides an urban road network mechanism association planning method based on a complex network sand pile model, and provides a method for analyzing the congestion distribution condition of an urban traffic network by combining a sand pile avalanche model in a complex network theory, helping to know the congestion action mechanism among traffic roads, finding lines which are easy to be congested and exist in the design and planning process of the urban roads, and further helping to effectively find defects in the road design in the design and planning process of the urban roads, so that an efficient urban planning road network is optimized finally or the defects in the existing roads are modified, and the operation efficiency of the urban roads is improved. The method comprises the steps of firstly, establishing an urban road network mechanism association model, reasonably considering the traffic dispersion capability of roads and dynamic factors which play a role in correlation to congestion of a certain road section in the process of congestion of urban roads, and reasonably considering the factors into the association model through operations such as normalization and the like; by system simulation, an evolution mechanism process of the urban road is simulated, and by means of an analysis process of a sand heap model in a complex network theory, the congestion evolution process and the congestion propagation process after the urban road is congested are presented, so that the rationality of the design and planning of the whole urban road network is integrally known, and a scientific basis is provided for further optimization of urban road planning. To illustrate the effects of the present invention, the following is a detailed description of the process of the present invention:
1. considering that the actual road lanes are usually bidirectional roads (there are also roads such as unidirectional lanes or tidal lanes), but congestion of a road in one direction usually does not affect the unobstructed condition of a road in another direction (special and few cases such as dotted line turning around are ignored), therefore, the urban road network can be abstracted into a unidirectional directional network set:where V is the set of network nodes (representing traffic ports).
2. Suppose that the road section i with congestion is influenced by the road section connected at the rear side by the factor ofThe influence factor on the left turn and the right turn isAndthe influence factor on the road section ahead isThe factor indicates the number of vehicles in the rear side vehicles driving into the road section and the number of vehicles in the road section, and the number of vehicles in the rear side vehicles passing through the front intersection makes forward movement, left turn and right turn, so that the vehicles are converged into the connected road. Wherein:
wherein n isi_front,ni_left,ni_right,ni_back∈R+Indicating the number of roads joining the front, left, right and rear of the congested road i+Is a positive integer set;
3. the bearing capacity of each road section is ηiLength l of the road iiNumber p of unidirectional lanesiAnd the number of the roads (n) connected with the road i, which are going forward, left and righti_front,ni_left,ni_right) And the number n of roads merging behindi_backTime length of traffic lightsThe condition factors are related to:
4. taking into account the length l of the road iiNumber p of unidirectional lanesiAnd the number of the roads (n) connected with the road i, which are going forward, left and righti_front,ni_left,ni_right) And merging at the rearNumber of roads ni_backDuration of traffic lightsThe isogenic dimensions are different, so the normalization processing is carried out as follows:
wherein: lmax,tmax,pmax,The method is characterized by comprising the following steps of representing the longest road length, the longest traffic light duration, the largest one-way lane number and the largest number of roads which are connected in the planned urban road network and are in forward, backward, left and right movement. The load-bearing capacity of each road section can be further expressed as
5. Dynamic congestion function y of each road sectioni(t) of (d). The function and the self-bearing capacity of the roadAverage running speed of vehicleCurrent time period Ti(t), rear road congestion functionAnd forward and left-right steering road congestion functionAnd its influence factorIt is related. Then y isi(t) can be expressed as:
wherein t is a simulation time step length; n isi_front,ni_left,ni_right,ni_back∈R+Indicating the number of roads into which the front, left, right and rear of the congested road i are connected, R+Is a positive integer set;
wherein:is the highest speed limit of the congested road i. Average running speed of vehicleCurrent time period Ti(t) compliance withAxis of ordinate, Ti(t) is a normal distribution function of the abscissa axis.
6. Setting congestion function thresholdsNamely whenIt is assumed that the road i is congested. At the moment, the total daily congestion times m of the road ii=mi+1;
7、Ti TotalTotal congestion time for road i in one day: t isi Total=mi×t(8)
the method is combined with a sand pile avalanche model in a complex network theory, analyzes the congestion distribution condition of the urban traffic network, helps to know the congestion action mechanism among the traffic roads, further helps to effectively discover the defects in the road design in the design and planning process of the urban roads, thereby finally optimizing an efficient urban planning road network or modifying the defects in the existing roads and improving the running efficiency of the urban roads.
Before the specific simulation steps are carried out, the following preparation work can be carried out:
1. setting simulation program starting parameters: the simulation time step length t can be selected according to 10 minutes; average running speed of vehicleWith the current time period Ti(t) determining an expression (7) as a normal distribution function;
2. generating urban traffic networksEstablishing a unidirectional directed network set of an urban road network, wherein the urban road network is abstracted into the unidirectional directed network set:wherein V is a network node set, the network node representing a traffic intersection set;
3. initializing an urban traffic networkThe relevant parameters of (2): road length l of each section iiNumber of unidirectional lanes piAnd the number of the roads (n) connected with the road i, which are going forward, left and righti_front,ni_left,ni_right) And the number n of roads converged at the reari_backTime length of traffic lightsHighest speed limit of road iTotal daily congestion times m of road iiEtc.;
4. determining the influence factor of each road section i by the road section connected at the rear side according to the expressions (1) and (2)The influence factor on the left turn and the right turn isAndthe influence factor on the road section ahead isAn equal factor ratio;
5. calculating the bearing capacity η of each road section according to expression (3)iAnd normalizing the same into the same according to (4) and (5)
6. The simulation step is carried out according to the step length t in a circulating way: calculating the congestion function y of each road i according to the expression (6) in each circulationi(t) of (d). Because general urban roads are distributed in a network shape, and each road section is a forward road or a rear road of other roads, the congestion condition of any road section is influenced by the traffic condition of the rear road of the road section through the expression (6), and meanwhile, the road condition of the road section can influence other road conditions; by analogy, when a certain road is congested, the congestion can be propagated downwards like 'sand pile avalanche', and further, the reasonability of the planning and design of the road network of the whole city can be reflected under the 'sand pile avalanche' condition.
8. Calculating the total daily congestion times m of the road i according to the judgment conditioniAnd calculating the total congestion time T of the road i in one day according to the expressions (8) and (9)i TotalAnd congestion time evaluation function
According to the total congestion time T of the road i in one dayi TotalAnd congestion time evaluation functionAnd evaluating the total congestion condition of the urban road design according to the calculation result, and performing targeted adjustment (for example, by simulating to find out the total congestion time T of a certain road i)i TotalAnd congestion time evaluation functionIf the road is larger, the number of lanes, the number of left and right forward connecting roads, the number of rear merging roads and the like of the road section can be planned again, and the bearing capacity is improved ηiAnd further, the improvement of the traffic level of the road section best explains how to adjust), effectively avoids the occurrence of the phenomenon, and further optimizes the parameters implemented in the simulation as the guiding basis for urban road planning design and traffic management.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (6)
1. The urban road network mechanism association planning method based on the complex network sand heap model is characterized by comprising the following steps of:
step (1): establishing one-way directed network of urban road networkIn aggregate, urban road networks are abstracted into unidirectional directed network sets:wherein V is a network node set, and the network node represents a traffic intersection set;
step (2): determining the self bearing capacity of each road section in the city according to the actual situation
And (3): determining dynamic congestion function y of each road sectioni(t);
And (5): and establishing a congestion time evaluation function of each road, and evaluating the reasonability of the design of the congestion time evaluation function.
2. The method of claim 1, wherein in step (2)' each road segment has its own load-bearing capacity"described using the following mathematical model:
wherein, the influence factor of the road section i assumed to be congested in the formulas (1) and (2) by the road section connected at the rear side isThe influence factor on the left turn and the right turn isAndthe influence factor on the road section ahead isni_front,ni_left,ni_right,ni_back∈R+Indicating the number of roads joining the front, left, right and rear of the congested road i+Is a positive integer set;
in the formula (3), the load-bearing capacity of each road section is ηiThe length of the road i is liThe number of the one-way lanes is piThe number of the roads which are connected with the road i and move forward, left and right is n respectivelyi_front,ni_left,ni_right(ii) a (ii) a (ii) a The number of roads merging from the rear is ni_backThe duration of the traffic light is
3. The method as claimed in claim 1, wherein in the step (3), "the dynamic congestion function y of each road segmenti(t) "is described using the following mathematical model:
in the formula (6), t is the simulation time step length;
4. The method of claim 1, wherein y is judged in the step (4)i(t) whether it is greater than a congestion function thresholdThe specific method of the algorithm is as follows:
total daily congestion times m of road ii=mi+1。
5. The method as claimed in claim 1, wherein the step (5) of establishing the congestion time evaluation function of each road is described by using the following mathematical model: :
Ti Totaltotal congestion time for road i in one day:
Ti Total=mi×t (8);
the congestion time evaluation function of each road is as follows:
6. the method of claim 1, wherein the traffic conditions of the urban road network are described using a mathematical model described by the following expression:
Ti Total=mi×t (8)
Wherein, the influence factor of the road section i assumed to be congested in the formulas (1) and (2) by the road section connected at the rear side isThe influence factor on the left turn and the right turn isAndthe influence factor on the road section ahead isni_front,ni_left,ni_right,ni_back∈R+Indicating the number of roads joining the front, left, right and rear of the congested road i+Is a positive integer set;
in the formula (3), the load-bearing capacity of each road section is ηiThe length of the road i is liThe number of the one-way lanes is piThe number of the roads which are connected with the road i and move forward, left and right is n respectivelyi_front,ni_left,ni_right(ii) a The number of roads merging behind isni_backThe duration of the traffic light is
In the formulae (4) and (5), lmax,tmax,pmax,Representing the longest road length, the longest traffic light duration, the largest number of one-way lanes and the maximum number of roads which are connected in each road and are used for forward running, backward entering, left running and right running in the planned urban road network;
in the formula (6), t is the simulation time step length;
in the formula (7), the first and second groups,the highest speed limit of the congested road i is the average running speed of the vehicles on the road iCurrent time period Ti(t) compliance withAxis of ordinate, Ti(t) is a normal distribution function of the abscissa axis;
in the formula (8), Ti TotalThe total congestion time of the road i in one day;
the parameters in the model are optimized through the simulation of the mathematical model of the expressions (1) to (9);
the following preparation work is carried out before the simulation is carried out:
A) and setting parameters: simulating a time step t; average running speed of vehicleWith the current time period Ti(t) to determine expression (7);
C) Initializing the urban traffic networkThe relevant parameters of (2): road length l of each section iiNumber p of unidirectional lanesiThe number n of the roads which are connected with the road i and move forward, left and righti_front,ni_left,ni_rightAnd the number n of roads merging behindi_backTime length of traffic lightsHighest speed limit of road iTotal daily congestion times m of road ii;
D) Determining influence factors of road sections with rear side connection on each road section i at the starting moment according to expressions (1) and (2)Left-turn and right-turn influence factorAndinfluence factor of road section ahead
E) Calculating the bearing capacity η of each road section at the starting moment according to the expression (3)iAnd normalizing the same into the same according to (4) and (5)
F) Calculating a congestion function y of each road i at the initial moment according to an expression (6)i(t);
the simulation step circularly carries out the steps D) to G) according to the step length t);
calculating the total congestion times m of the road i in the whole day according to the judgment conditioniAnd calculating the total congestion time T of the road i in one day according to the expressions (8) and (9)i TotalAnd congestion time evaluation function
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CN114582124B (en) * | 2022-03-02 | 2023-08-04 | 北京京东乾石科技有限公司 | Scene editing method, device, medium and electronic equipment |
CN117131581A (en) * | 2023-10-26 | 2023-11-28 | 乘木科技(珠海)有限公司 | Digital twin urban road construction system and method |
CN117131581B (en) * | 2023-10-26 | 2024-02-13 | 乘木科技(珠海)有限公司 | Digital twin urban road construction system and method |
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