CN110516938B - Regional goods exclusion road demarcating method based on heuristic algorithm - Google Patents
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
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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
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
The invention discloses a regional no-cargo road demarcation method based on a heuristic algorithm, which comprises the steps of firstly carrying out abstract analysis on a road network in a research range, then setting calculation formulas of truck passing total cost, social cost and transportation cost, then merging social cost and transportation cost factors into the heuristic algorithm, iterating by using the heuristic algorithm to obtain a path allowing the truck to pass, and finally distributing the truck on the path allowing the truck to pass by using a system optimal principle to obtain an optimal path for the truck to travel.
Description
Technical Field
The invention belongs to the field of traffic planning and management. In particular to a regional no-cargo road demarcation method based on a heuristic algorithm.
Background
The continuous inflow of population brings about the urban feature of suburb towns, the development intensity of land is continuously increased, and the construction land breaks through the old town range and continuously expands outwards. During this process, suburban road traffic characteristics change significantly. Because the land type along the road changes, suburban roads which originally bear a large amount of transit traffic gradually bear short-distance traffic, the traffic mixing phenomenon of passenger and goods traffic is increasingly serious, and the problems of noise, tail gas pollution and the like are also brought when traffic accidents occur frequently, so that the normal life of urban residents is seriously influenced.
The key to solving the problems is to reasonably define the no-cargo area and effectively separate the passenger and freight transportation from the space. More and more suburban town governments are aware of this, and are engaged in the implementation of a contraband policy. For example, the town Zhang Guwo in the western green district of Tianjin, 12, 2018 starts to apply traffic control measures to the partial area in which heavy trucks are prohibited from passing by time periods.
The local government currently only statically implements the contraband traffic control measures for a relatively complete area, and there is no detailed demonstration of how to scientifically plan the contraband area, and the scheme made is also not reasonable. Related academic research results in this respect are also less. If the cargo-banning area is too large, the freight cost is increased in an intangible way, and if the cargo-banning area is too small, the social cost (such as traffic safety, environmental pollution and the like) caused by the passing of the freight car cannot be effectively reduced, so that the purpose of banning cannot be achieved.
The trucks pass through different paths, and the social cost and the transportation cost of the trucks are different. How to find the optimal travel path of the truck becomes a key issue in defining the regional cargo exclusion range.
Based on the reasons, the method and the system creatively find the optimal path scheme for truck driving based on the heuristic algorithm, and further delimit the regional no-cargo road according to the obtained optimal path.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method for rapidly defining a road for implementing forbidden traffic control measures in a certain area under the condition of passenger-cargo traffic mixing.
The technical scheme adopted by the invention is as follows:
a regional no-good road demarcation method based on heuristic algorithm comprises the following steps:
step one, determining a research area as a road network in a suburban town range;
analyzing the regional road network by adopting an original method, abstracting intersections in the road network into points, wherein the number is m, the point set is G, and numbering is given to each point, and the range is from 1 to m; abstracting road sections between two adjacent points into straight line sections, wherein the number of the straight line sections is n, and assigning numbers (i, j) to each road section, wherein i epsilon (1-m-1), j epsilon (2-m), and i < j; then arbitrarily selecting two points on the resolved abstract road network as a departure place A and a destination B of the truck;
calculating assignment of a unit distance of truck driving to social cost generated by different land types by taking population density as a calculation basisThe specific method comprises the following steps:
firstly, counting all land types in a research area, and then calculating the average population density in each land type range within 24 hours on a certain working day, wherein the formula is as follows:
D f ＝p f /A f
wherein f is E (1-e), e represents the number of all land types in the research area; d (D) f Represents the population density of the f-th land type; p is p f Representing the sum of the total demographics at the end of each hour throughout a workday over a range of f land types;representing the total population number of the end of the q hours of the whole day within the range of the f land type, and q is E (1-24); a is that f Representing the f-th land type surfaceAccumulating;
secondly, sorting the average population densities of all the user averages from small to large, and respectively matching with the minimum value D in the average population densities of all the user averages min Performing ratio, and finally rounding the ratio result to positive integer to be used as assignment of a truck driving unit distance to social cost generated by different land typesTaking 1 at minimum;
step four, calculating social cost generated by running the truck on a road section with the number (i, j) between the AB, wherein the formula is as follows:
wherein the method comprises the steps ofRepresenting the social cost of truck k traveling on road segment numbered (i, j); />Representing the road length occupied by the f-th land type on the road segment numbered (i, j);
step five, calculating freight transportation cost, wherein the formula is as follows:
wherein the method comprises the steps ofRepresenting the transportation cost of truck k traveling on road segment numbered (i, j); g represents the transportation cost per unit distance of the truck; r is R i,j Representing the length of the road segment (i, j);
step six, calculating the total cost of truck passing, wherein the formula is as follows
C Total (S) ＝C Social agency (society) +C Transport and transport
Wherein C is Total (S) Representing the total cost of all trucks traveling from origin a to destination B; c (C) Social agency (society) Representing the social cost of all trucks traveling from origin a to destination B; c (C) Transport and transport Representing the transportation costs of all trucks traveling from origin a to destination B; h represents the total number of trucks;
step seven, generating a truck driving path scheme based on a heuristic algorithm, wherein the specific process is as follows:
setting a truck k (k=1, 2,., h) to determine a driving direction according to the information amount on each road section during driving; with taboo table tabu k (k=1, 2,., h) record the point that the truck has currently passed;a probability indicating whether the truck k is driving on the road section (i, j);
wherein, allowed k ＝{G-tabu k -represents the point at which truck k is allowed to select next; α is an informative heuristic, α=1;
β is a desired formula factor, β=4; τ ij The information amount on the road section (i, j) is expressed as follows:
η i,j as a heuristic function, its expressionThe formula is as follows:
and step eight, distributing the truck flow in the path scheme obtained in the step seven by applying the optimal principle of the Wardrop system, searching the path scheme with the shortest total running time of all trucks in the path scheme as a final selected scheme, and then calculating the total cost of all truck traffic, wherein the total running time of all trucks has the following calculation formula:
wherein Z represents the total running time of all trucks in the road network; q (Q) i,j Representing the truck flow allocated to road segment (i, j);
representing the traffic of the d-th path between the departure point A and the destination B; r represents the total number of paths calculated in the step seven; t is t i,j Representing the travel time of a truck on a road section (i, j), the expression is as follows:
t i,j,0 representing the time required for the truck to freely travel on the road section (i, j); c i,j Representing the traffic capacity of the road section (i, j);representing the path-segment related variables, the expression of which is as follows:
according to the regional no-load road demarcation method based on the heuristic algorithm, roads which need to be subjected to no-load measures in a certain region can be rapidly demarcated under the condition of passenger-cargo traffic mixing. Because the local government can not carry out scientific demonstration on the forbidden goods implementing range before implementing the forbidden goods policy at present, the forbidden goods range is unreasonable, the invention creatively provides a path method for searching the total running cost of the freight car, which is beneficial to scientifically defining the forbidden goods road range and improving the scientificity and rationality of the forbidden goods policy implementing range, thereby effectively separating the passenger and freight transport and finally improving the road traffic safety level.
Drawings
Fig. 1 is a technical flowchart of a method for demarcating a regional no-load road based on a heuristic algorithm according to the present invention.
FIG. 2 is a simplified road network diagram of a method of regional exclusion road delineating based on a heuristic algorithm of the present invention;
fig. 3 is a schematic diagram of a final determined path using the method of the present invention.
Detailed Description
The present invention will be described in detail with reference to examples and drawings.
The invention discloses a regional no-cargo road demarcation method based on a heuristic algorithm, which comprises the following steps:
step one, determining a research area as a road network in a suburban town range.
Analyzing the regional road network by adopting an original method, abstracting intersections in the road network into points, wherein the number is m, the point set is G, and numbering is given to each point, and the range is from 1 to m. The road sections between two adjacent points are abstracted into straight line sections, the number is n, and each road section is assigned with a number (i, j), wherein i epsilon (1-m-1), j epsilon (2-m), and i < j. By transformation, the real road network is abstracted into an abstract network. And then arbitrarily selecting two points on the parsed abstract road network as a departure place A and a destination B of the truck.
For regional road network analysis, reference may be made to the paper The network analysis of urban streets: a primal approach by S.Porta et al, 2006.
Calculating assignment of a unit distance of truck driving to social cost generated by different land types by taking population density as a calculation basisThe specific method comprises the following steps:
in the first step, the population density is taken as the calculation basis in consideration of the fact that the freight car passing social cost is mainly used for influencing the activities of people in the land. Firstly, counting all land types in a research area, and then calculating the average population density in the range of each land type within 24 hours on a certain working day, wherein the formula is as follows
D f ＝p f /A f
Wherein f is E (1-e), e represents the number of all land types in the research area; d (D) f Represents the population density of the f-th land type; p is p f Representing the sum of the total demographics at the end of each hour throughout a workday over a range of f land types;representing the total population number of the end of the q hours of the whole day within the range of the f land type, and q is E (1-24); a is that f Representing the area of the f-th land type.
Secondly, sorting the average population densities of all the user averages from small to large, and respectively matching with the minimum value D in the average population densities of all the user averages min Performing ratio, and finally rounding the ratio result to positive integer to be used as assignment of a truck driving unit distance to social cost generated by different land typesMinimum 1 and maximum not limited.
The said processThe larger the value of which is only related to the type of land, the greater the social cost that is generated.
Step four, calculating social cost generated by running the truck on a road section with the number (i, j) between the AB, wherein the formula is as follows:
wherein the method comprises the steps ofRepresenting the social cost of truck k traveling on road segment numbered (i, j); />The road length occupied by the f-th land type on the road section numbered (i, j) is represented.
Step five, calculating freight transportation cost, wherein the formula is as follows:
wherein the method comprises the steps ofRepresenting the result of a truck k travelling on road segments numbered (i, j)Raw transportation costs; g represents the transportation cost per unit distance of the truck; r is R i,j Representing the length of the road segment (i, j).
Step six, calculating the total cost of truck passing, wherein the formula is as follows
C Total (S) ＝C Social agency (society) +C Transport and transport
Wherein C is Total (S) Representing the total cost of all trucks traveling from origin a to destination B; c (C) Social agency (society) Representing the social cost of all trucks traveling from origin a to destination B; c (C) Transport and transport Representing the transportation costs of all trucks traveling from origin a to destination B; h represents the total number of trucks.
And step seven, generating a truck driving path scheme based on a heuristic algorithm.
Searching for C from an entire road network Total (S) The path with the smallest value has larger workload and needs to traverse calculation for each path. The heuristic algorithm can generate a path allowing the truck to run, so that the workload is reduced, and the road outside the path scheme is the no-cargo road. The specific process is as follows:
the truck k (k=1, 2,., h) is set to determine the traveling direction according to the information amount on each road section during traveling. Here use the taboo table tabu k (k=1, 2,., h) to record the point that the truck has currently passed. According to the principle of heuristic algorithm, in the driving process, the truck calculates the driving probability according to the information quantity and path heuristic information on each road section.The probability of whether the truck k is traveling on the road section (i, j) is represented.
Wherein, allowed k ＝{G-tabu k -represents the point at which truck k is allowed to select next; alpha is an information heuristic factor, represents the relative importance of the path and reflects C of the truck in the driving process Social agency (society) The greater the value of the function of the path selection, the more the truck tends to select a road section with low social cost; beta is a desired factor, representing C Transport and transport The greater the value, the more likely the truck will be to choose a path of less transportation cost; τ ij The information amount on the road section (i, j) is expressed as follows:
η i,j the expression is as follows:
the heuristic represents the desired degree to which the truck is traveling from point i to point j. In the case of a truck k,smaller, η i,j The bigger the->The larger.
Alpha and beta are preset parameters for controlling the weight relation between the information quantity and the heuristic information. When alpha=0, the algorithm evolves into a traditional random greedy algorithm, and the probability that the nearest point is selected is the largest; when β=0, the truck determines the path only according to the information amount, the algorithm will converge rapidly, so that the constructed optimal path often has a larger difference from the actual target, and the performance of the algorithm is worse. In the present invention, α=1, β=4 is set.
The algorithm can be specifically found in the ant colony algorithm principle and application thereof (section seashore, 2005).
And step eight, distributing the truck flow in the path scheme obtained in the step seven by applying the optimal principle of the Wardrop system, searching the path scheme with the shortest total running time of all trucks in the path scheme as a final selected scheme, and then calculating the total running cost of all trucks by adopting the total running cost formula of the trucks in the step six, wherein the total running time calculation formula of all trucks is as follows:
wherein Z represents the total running time of all trucks in the road network; q (Q) i,j Representing the truck flow allocated to road segment (i, j);
representing the traffic of the d-th path between the departure point A and the destination B; r represents the total number of paths calculated in the step seven; t is t i,j Representing the travel time of a truck on a road section (i, j), the expression is as follows:
t i,j,0 representing the time required for the truck to freely travel on the road section (i, j);c i,j representing the traffic capacity of the road segment (i, j).Representing the path-segment related variables, the expression of which is as follows:
example analysis
In order to verify the practicability of the regional no-cargo road demarcation method based on the heuristic algorithm, the method selects a classical road network Sioux Falls road network as a research object for testing, and selects a shortest path of freight car passing cost. In the example, the Sioux Falls road network is resolved into an abstract network, n=37 road segments, m=24 (including point A, B) points and 14 plots (see fig. 2), and f=6 land types in total. The example assumes a number of trucks of h=1000, a departure point a, a destination B, and a cost of 2 trucks per kilometer. The evaluation values assigned to each land type are shown in table 1. The length of each road section and the statistical evaluation values according to the land types on both sides of the road are shown in table 2.
Table 1 example road network each section length and section judgment value statistics results
Table 2 example land type and evaluation value for road network
By applying the heuristic algorithm, the path scheme is continuously generated, and the truck driving path scheme (shown in figure 3) is generated through 500 times of iterative computation, wherein the roads outside the path scheme are forbidden roads; and then distributing the truck flow in a path scheme according to the optimal principle of the Wardrop system, wherein the A-2-3-4-6-13-14 path distribution traffic quantity 515 vehicles and the A-1-5-9-12-14 path distribution traffic quantity 485 vehicles in the figure 3.
Claims (1)
1. The regional no-good road demarcation method based on the heuristic algorithm is characterized by comprising the following steps:
step one, determining a research area as a road network in a suburban town range;
analyzing the regional road network by adopting an original method, abstracting intersections in the road network into points, wherein the number is m, the point set is G, and numbering is given to each point, and the range is from 1 to m; abstracting road sections between two adjacent points into straight line sections, wherein the number of the straight line sections is n, and assigning numbers (i, j) to each road section, wherein i epsilon (1-m-1), j epsilon (2-m), and i < j; then arbitrarily selecting two points on the resolved abstract road network as a departure place A and a destination B of the truck;
step three, calculating a judgment value of the social cost of a truck running unit distance for different land types by taking population density as a calculation basisThe specific method comprises the following steps:
firstly, counting all land types in a research area, and then calculating the average population density of each land type within 24 hours on a certain working day, wherein the formula is as follows
D f ＝p f /A f
Wherein f is E (1-e), e represents the number of all land types in the research area; d (D) f Represents the population density of the f-th land type; p is p f Representing the f-th land typeSum of total demographics at the end of each hour throughout a workday, over a range;representing the total population number of the end of the q hours of the whole day within the range of the f land type, and q is E (1-24); a is that f Representing the area of the f-th land type;
secondly, sorting the average population densities of all the user averages from small to large, and respectively matching with the minimum value D in the average population densities of all the user averages min Performing ratio, and finally rounding the ratio result to positive integer to be used as a judgment value of the social cost of different land types generated by a truck running unit distanceTaking 1 at minimum;
step four, calculating social cost generated by running the truck on a road section with the number (i, j) between the AB, wherein the formula is as follows:
wherein the method comprises the steps ofRepresenting the social cost of truck k traveling on road segment numbered (i, j); />Representing the road length occupied by the f-th land type on the road segment numbered (i, j);
step five, calculating freight transportation cost, wherein the formula is as follows:
wherein the method comprises the steps ofRepresenting the transportation cost of truck k traveling on road segment numbered (i, j); g represents the transportation cost per unit distance of the truck; r is R i,j Representing the length of the road segment (i, j);
step six, calculating the total cost of truck passing, wherein the formula is as follows:
C total (S) ＝C Social agency (society) +C Transport and transport
Wherein C is Total (S) Representing the total cost of all trucks traveling from origin a to destination B; c (C) Social agency (society) Representing the social cost of all trucks traveling from origin a to destination B; c (C) Transport and transport Representing the transportation costs of all trucks traveling from origin a to destination B; h represents the total number of trucks;
step seven, generating a truck driving path scheme based on a heuristic algorithm, wherein the specific process is as follows:
setting a truck k (k=1, 2,., h) to determine a driving direction according to the information amount on each road section during driving; with taboo table tabu k (k=1, 2,., h) record the point that the truck has currently passed;a probability indicating whether the truck k is driving on the road section (i, j);
wherein, allowed k ＝{G-tabu k -represents the point at which truck k is allowed to select next; α is an informative heuristic, α=1; β is a desired formula factor, β=4; τ ij The information amount on the road section (i, j) is expressed as follows:
η i,j the expression is as follows:
and step eight, distributing the truck flow in the path scheme obtained in the step seven by applying the optimal principle of the Wardrop system, searching the path scheme with the shortest total running time of all trucks in the path scheme as a final selected scheme, and then calculating the total running cost of all trucks, wherein the total running time of all trucks has the following calculation formula:
wherein Z represents the total running time of all trucks in the road network; q (Q) i,j Representing the truck flow allocated to road segment (i, j);representing the traffic of the d-th path between the departure point A and the destination B; r represents the total number of paths calculated in the step seven; t is t i,j Representing the travel time of a truck on a road section (i, j), the expression is as follows:
t i,j,0 representing the time required for the truck to freely travel on the road section (i, j); c i,j Representing the traffic capacity of the road section (i, j);representing the path-segment related variables, the expression of which is as follows:
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