CN116151505B

CN116151505B - Cell line planning method and device, electronic equipment and readable storage medium

Info

Publication number: CN116151505B
Application number: CN202310424974.1A
Authority: CN
Inventors: 温桂龙
Original assignee: Shenzhen Mingyuan Cloud Technology Co Ltd
Current assignee: Shenzhen Mingyuan Cloud Technology Co Ltd
Priority date: 2023-04-20
Filing date: 2023-04-20
Publication date: 2023-08-04
Anticipated expiration: 2043-04-20
Also published as: CN116151505A

Abstract

The application discloses a cell line planning method, a device, electronic equipment and a readable storage medium, and relates to the technical field of artificial intelligence, wherein the cell line planning method comprises the following steps: randomly generating a first line planning scheme set based on map information of a target cell; calculating a first fitness corresponding to each wire-bound planning scheme in the first wire-bound planning scheme set according to the planning target of the target cell and traffic flow data; based on a preset genetic algorithm and the first fitness, selecting, crossing and mutating operations are carried out on each wire-line planning scheme, and a second wire-line planning scheme set is obtained; and selecting the wire-line planning scheme with the highest fitness from the first wire-line planning scheme set and the second wire-line planning scheme set as a target wire-line planning scheme. The method and the device solve the technical problem that the route passing efficiency of the traditional cell line planning scheme is low.

Description

Cell line planning method and device, electronic equipment and readable storage medium

Technical Field

The present disclosure relates to the field of artificial intelligence technologies, and in particular, to a cell line planning method, device, electronic equipment, and readable storage medium.

Background

With the acceleration of the urban process and the continuous growth of population, urban residents have higher and higher requirements on housing environments, wherein the district line planning is related to the comfort level and convenience of daily living of the residents in the district, the safety and sustainable development of the district are also related, and the line planning in the district also directly influences the traveling experience, safety and quality of life of the residents. Therefore, how to scientifically and effectively plan the cell line becomes an important research field in the current city planning. At present, the traditional district line-of-road planning scheme is based on experience and intuition of designers, has certain limitation, and is difficult to fully consider factors such as behavior habit, path preference, dynamic change and the like of resident trip, so that the problem that the planned line-of-road path is easy to have low passing efficiency such as redundancy, congestion, inconvenience and the like is easily caused.

Disclosure of Invention

The main objective of the present application is to provide a cell line planning method, a device, an electronic device and a readable storage medium, which aim to solve the technical problem of low path passing efficiency of the traditional cell line planning scheme.

In order to achieve the above object, the present application provides a cell line planning method, which includes:

Randomly generating a first line planning scheme set based on map information of a target cell;

calculating a first fitness corresponding to each line planning scheme in the first line planning scheme set according to the planning target and traffic flow data of the target cell, wherein the planning target at least comprises weights respectively corresponding to pedestrian travel time length, pedestrian and vehicle meeting probability, vehicle travel time length, pedestrian density and parking space searching time length;

based on a preset genetic algorithm and the first fitness, selecting, crossing and mutating operations are carried out on each wire-line planning scheme, and a second wire-line planning scheme set is obtained;

and selecting a wire-line planning scheme with highest fitness from the first wire-line planning scheme set and the second wire-line planning scheme set as a target wire-line planning scheme, wherein the target wire-line planning scheme is used for planning the wire line of a target cell.

Optionally, the traffic flow data at least includes time sequence distribution data of people flow and traffic flow in a target cell, and the step of calculating the first fitness corresponding to each of the first routing schemes in the first routing scheme set according to the planning target of the target cell and the traffic flow data includes:

Determining the corresponding pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length of each of the wire-bound planning schemes according to the time sequence distribution data and each of the wire-bound planning schemes in the first wire-bound planning scheme set;

and inputting weights corresponding to the pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length, which are corresponding to the respective line planning schemes, into a preset fitness function to obtain a first fitness corresponding to the line planning schemes in the first line planning scheme set.

Optionally, the step of performing selection, crossover and mutation operations on each of the wire-line planning schemes based on the preset genetic algorithm and the first fitness to obtain a second set of wire-line planning schemes includes:

calculating the sum of first fitness corresponding to all the wire-bound planning schemes in the first wire-bound planning scheme set to obtain total fitness;

determining individual selection probability of each of the on-line planning schemes based on the ratio of the first fitness to the total fitness corresponding to each of the on-line planning schemes;

And selecting a plurality of parent individuals from each of the routing schemes according to the individual selection probability, and executing intersection and mutation operations on the parent individuals to obtain a second routing scheme set.

inputting a first fitness corresponding to each wire-line planning scheme into a preset individual selection probability function to obtain individual selection probability corresponding to each wire-line planning scheme;

selecting a plurality of parent individuals from each of the routing schemes according to the individual selection probability, and executing intersection and mutation operations on the parent individuals to obtain a second routing scheme set;

wherein the expression of the individual selection probability function is:

wherein ,is->Individual selection probability of the individual wire-bound plan, +.>Is->Flexibility of the individual line planning scheme, +.>Sequence number for line planning scheme,/->The number of floor plan schemes in the first floor plan scheme set is determined.

Optionally, the second set of routing schemes includes child individuals, the step of selecting a parent individual from the routing schemes according to the individual selection probability, and performing crossover and mutation operations on the parent individual, and the step of obtaining the second set of routing schemes includes:

Selecting a plurality of parent individuals in each of the routing schemes based on the individual selection probabilities;

performing cross operation on the parent individuals to obtain a first child individual set;

performing mutation operation on the first child individual set to obtain a second child individual set;

returning to the execution step: selecting a plurality of parent individuals in each of the routing schemes based on the individual selection probabilities;

and when a preset condition is met, setting the second child individual set as a second line-of-sight planning scheme set, wherein the preset condition is that a line-of-sight planning scheme with the fitness higher than a preset fitness or the iteration number of which is not lower than a preset threshold exists in the second child individual set.

Optionally, the step of performing a crossover operation on the parent individuals to obtain a first set of child individuals includes:

establishing a plane rectangular coordinate system based on the map information of the target cell, and acquiring coordinates of each point on a line corresponding to the parent individual in the plane rectangular coordinate system;

binary coding is carried out on the parent individuals based on the coordinates, and chromosomes of the parent individuals are obtained;

randomly exchanging the segments of the chromosomes of each parent individual to generate corresponding offspring individuals.

Optionally, the map information includes at least fixed area information, and the step of randomly generating the first set of routing schemes based on the map information of the target cell includes:

and taking the fixed area information in the map information of the target cell as a limiting condition of a wire-line planning scheme, randomly generating a plurality of wire-line planning schemes corresponding to the target cell based on the limiting condition, and obtaining a first wire-line planning scheme set.

The application also provides a cell wire-line planning device, the cell wire-line planning device is applied to cell wire-line planning equipment, the cell wire-line planning device includes:

the initialization module is used for randomly generating a first line planning scheme set based on map information of a target cell;

the fitness calculation module is used for calculating first fitness corresponding to each wire-bound planning scheme in the first wire-bound planning scheme set according to the planning target and traffic flow data of the target cell, wherein the planning target at least comprises weights respectively corresponding to pedestrian travel duration, pedestrian and vehicle meeting probability, vehicle travel duration, pedestrian density and parking space searching duration;

the genetic evolution module is used for executing selection, crossing and mutation operations on each line planning scheme based on a preset genetic algorithm and the first fitness to obtain a second line planning scheme set;

And the scheme screening module is used for selecting the routing line planning scheme with the highest fitness from the first routing line planning scheme set and the second routing line planning scheme set as a target routing line planning scheme, wherein the target routing line planning scheme is used for planning the routing line of the target cell.

Optionally, the fitness calculating module is further configured to:

Optionally, the genetic evolution module is further configured to:

wherein the expression of the individual selection probability function is:

Optionally, the genetic evolution module is further configured to:

Optionally, the initialization module is further configured to:

The application also provides an electronic device, which is an entity device, and includes: the method comprises a memory, a processor and a program of the cell line planning method stored in the memory and capable of running on the processor, wherein the program of the cell line planning method can realize the steps of the cell line planning method when being executed by the processor.

The present application also provides a computer readable storage medium having stored thereon a program for implementing a cell wire planning method, which when executed by a processor implements the steps of the cell wire planning method as described above.

The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of a cell line planning method as described above.

The application provides a cell line planning method, device, electronic equipment and readable storage medium, firstly, based on map information of a target cell, a first line planning scheme set is randomly generated, and then according to planning targets and traffic flow data of the target cell, first fitness corresponding to each line planning scheme in the first line planning scheme set is calculated, wherein the planning targets at least comprise weights corresponding to pedestrian travel time length, pedestrian and vehicle meeting probability, vehicle travel time length, pedestrian density and parking space searching time length respectively, and further based on a preset genetic algorithm and the first fitness, selection, crossover and variation operations are performed on each line planning scheme to obtain a second line planning scheme set, finally, the line planning scheme with the highest fitness is selected from the first line planning scheme set and the second line planning scheme set to serve as a target line planning scheme, the technical scheme of the target cell is used for line planning of the target cell, the pedestrian and vehicle meeting probability, the pedestrian and the parking space meeting time length are combined, the first line planning scheme is calculated, the first line planning scheme is further selected according to the optimal line planning algorithm, the first line planning scheme is used for line planning with the optimal movement time length, and the first line planning scheme is calculated according to the optimal line planning algorithm is performed, and the first line planning scheme is completely planned by the first line planning scheme is selected, and the optimal line planning algorithm is performed according to the first line planning scheme is calculated, and the optimal line planning algorithm is performed, and the first line planning algorithm is used to obtain the optimal line planning algorithm, and the line planning algorithm is used to plan, and has the optimal line planning time and has high service time and high service time, and has high service time, and high service and is suitable service and time, and is suitable to and time, and service and time, and is suitable to and service. The technical defect that limitation exists in planning the cell line based on experience and intuition of a designer is overcome, and the path passing efficiency of planning the cell line is improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.

Fig. 1 is a flow chart of a first embodiment of a cell line planning method according to the present application;

fig. 2 is a flowchart illustrating steps S331 to S335 in the first embodiment of the cell line planning method of the present application;

FIG. 3 is a schematic diagram of single-point crossing of chromosomes of a parent individual in the cell line planning method of the present application;

FIG. 4 is a schematic diagram of a parent individual chromosome multipoint crossover in the cell line planning method of the present application;

fig. 5 is a schematic structural diagram of a cell line planning device according to an embodiment of the present application;

fig. 6 is a schematic device structure diagram of a hardware operating environment related to a cell line planning method in an embodiment of the present application.

The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings in conjunction with the embodiments.

Detailed Description

In order to make the above objects, features and advantages of the present application more comprehensible, the following description will make the technical solutions of the embodiments of the present application clear and complete with reference to the accompanying drawings of the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, based on the embodiments herein, which are within the scope of the protection of the present application, will be within the purview of one of ordinary skill in the art without the exercise of inventive faculty.

Example 1

With the acceleration of the urban process and the continuous growth of population, urban residents have higher requirements on housing environments. And a comfortable, convenient and efficient living environment has important significance for improving the life quality and improving the urban competitiveness. The line planning of the residential area is a very important aspect, and not only relates to the comfort and convenience of the residential area, but also relates to the safety and sustainable development of the residential area, so that the traveling experience, safety and life quality of residents are directly influenced. Therefore, how to scientifically and effectively plan the cell line becomes an important research field in the current city planning.

At present, the traditional cell line planning mode is based on experience and intuition, and is difficult to fully consider factors such as behavior habit, path preference, dynamic change and the like of resident trip, and the problems such as path redundancy, congestion, inconvenience and the like are easy to occur. Therefore, there is a need for an artificial intelligence based cell line planning method to improve the accuracy and practicality of cell line planning. According to the method and the system, the data are collected through the camera, life track data of households in the cell are collected, traffic flow data of the cell are obtained, the demand of the cell users on the line planning system is analyzed, the line planning is conducted through the genetic algorithm, the line planning scheme with high adaptability is screened out, accordingly, the target line planning scheme with high traffic efficiency is obtained, advice or basis can be provided for follow-up upgrading and reconstruction of the existing cell, and reference can be provided for real estate developers to develop new building plates.

An embodiment of the present application provides a cell line planning method, in a first embodiment of the cell line planning method of the present application, referring to fig. 1, the cell line planning method includes:

step S10, a first line planning scheme set is randomly generated based on map information of a target cell;

Step S20, calculating first fitness corresponding to each line planning scheme in the first line planning scheme set according to the planning target and traffic flow data of the target cell, wherein the planning target at least comprises weights respectively corresponding to pedestrian travel time length, pedestrian and vehicle meeting probability, vehicle travel time length, pedestrian density and parking space searching time length;

step S30, based on a preset genetic algorithm and the first fitness, selecting, crossing and mutating operations are carried out on each line planning scheme, and a second line planning scheme set is obtained;

and step S40, selecting a wire-line planning scheme with highest fitness from the first wire-line planning scheme set and the second wire-line planning scheme set as a target wire-line planning scheme, wherein the target wire-line planning scheme is used for planning the wire-line of a target cell.

In the embodiment of the present application, it should be noted that, the line planning scheme at least includes a road planning scheme in a cell, an entrance position, a parking area, a garage position, a gate position, and the like of each building, the line planning mainly refers to a route that a resident in the cell passes through in a walking or driving manner when traveling or returning home in a daily start, in the embodiment of the present application, multiple groups of line schemes (action routes) in the resident in the cell are generated based on a genetic algorithm, parameters of each group of line schemes in terms of a pedestrian traveling time length, a person-to-vehicle meeting probability, a vehicle traveling time length, a pedestrian density, a parking space searching time length, and the like are obtained through simulation, and then the adaptability of each group of line schemes is calculated according to the pedestrian traveling time length, the person-to-vehicle meeting probability, the vehicle traveling time length, the pedestrian density, the parking space searching time length, and the like, wherein the pedestrian time length is the average time length of a resident in the cell arrives outside the cell from home, the average time length of a resident in the parking space is found when the vehicle arrives outside the cell, and the average time length of a resident in the parking space is found outside the parking space. The map information at least comprises information of an unalterable building, facility or area in the target cell, for example, when the old cell is remodeled and upgraded, some road, intersection or gate positions cannot be changed, so that the line planning scheme is generated on the basis of the original map information, i.e. the newly generated line planning scheme cannot conflict with the information of the unalterable building, facility or area in the map information. In addition, the first fitness is used for measuring the advantages and disadvantages of each line planning scheme in the first line planning scheme set, and is also used for calculating the selection probability when each line planning scheme is processed in a genetic algorithm, so that the higher the line planning scheme with higher fitness is, the higher the probability of being selected is, the higher the generated line planning scheme in the second line planning scheme set is, and the better technical effect of the line planning scheme is achieved on the basis of the original line planning scheme.

In the embodiment of the present application, when a planning target of a target cell is obtained, a method of performing poll statistics on residents in the target cell may be adopted to obtain which parameter of a line planning result is focused by the residents, and the number of people focused on each parameter is used as a corresponding weight of each parameter to calculate the fitness of a line planning scheme. For example, in the poll, the average travel duration of the pedestrians accounts for 35%, the meeting probability of the pedestrians and the vehicles accounts for 30%, the average travel duration of the vehicles accounts for 20%, the density of the pedestrians accounts for 10%, and the average parking space searching duration of the pedestrians accounts for 5%, so that the weights corresponding to the travel duration of the pedestrians, the meeting probability of the pedestrians, the travel duration of the vehicles, the density of the pedestrians and the parking space searching duration are respectively 0.35, 0.3, 0.2, 0.1 and 0.05. In addition, the traffic flow data are people flow distribution data and traffic flow distribution data on a district road in each time period of the whole day, and can be collected through each monitoring camera arranged in the district, and the traffic flow data are used as variables for inputting each line planning scheme to determine the corresponding pedestrian travel time length, the probability of meeting people and vehicles, the vehicle travel time length, the pedestrian density and the parking space searching time length of each line planning scheme.

As an example, steps S10 to S40 include: based on fixed building position information and fixed road information in map information of a target cell, randomly generating a plurality of groups of line planning schemes in the map of the target cell to obtain a first line planning scheme set; extracting pedestrian travel time length, pedestrian and vehicle meeting probability, vehicle travel time length, pedestrian density, parking space searching time length and corresponding attention number in a planning target from intention statistics information of residents in a target cell, and determining weights corresponding to the pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length according to the pedestrian travel time length, the pedestrian and vehicle meeting probability, the parking space searching time length and the corresponding attention number; collecting people flow distribution data and traffic flow distribution data in a target cell at each time period according to a monitoring camera in the target cell, and inputting the people flow distribution data and the traffic flow distribution data into each line planning scheme to obtain pedestrian travel time length, pedestrian and vehicle meeting probability, vehicle travel time length, pedestrian density and parking space searching time length corresponding to each line planning scheme; determining a first fitness corresponding to each of the line planning schemes in the first line planning scheme set according to the pedestrian travel time, the pedestrian and vehicle meeting probability, the vehicle travel time, the pedestrian density and the parking space searching time; determining individual selection probabilities of the routing schemes according to the first fitness of the routing schemes; based on individual selection probabilities respectively corresponding to all the wire-bound planning schemes in the first wire-bound planning scheme set, sequentially selecting, crossing and mutating all the wire-bound planning schemes to obtain a second wire-bound planning scheme set, wherein the second wire-bound planning scheme set consists of all the wire-bound planning schemes after evolution; calculating the adaptability of each wire-bound planning scheme in the second wire-bound planning scheme set; and selecting an optimal target wire-bound planning scheme from the first wire-bound planning scheme set and the second wire-bound planning scheme set based on the fitness, wherein the target wire-bound planning scheme is used for planning wires of a target cell.

The step of calculating a first fitness corresponding to each line planning scheme in the first line planning scheme set according to the planning target of the target cell and the traffic flow data comprises the following steps:

step S21, determining the travel time length of pedestrians, the meeting probability of vehicles, the travel time length of vehicles, the pedestrian density and the parking space searching time length corresponding to each of the wire-bound planning schemes according to the time sequence distribution data and each of the wire-bound planning schemes in the first wire-bound planning scheme set;

step S22, inputting the pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length corresponding to each of the line planning schemes, and weights corresponding to the pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length respectively into a preset fitness function, so as to obtain a first fitness corresponding to each line planning scheme in the first line planning scheme set.

In this embodiment of the present application, it should be noted that the time sequence distribution data includes traffic time sequence distribution data and traffic time sequence distribution data, which are used to characterize how many people travel and return home in a cell are distributed in each time period of each day, that is, the traffic and the flow of people in the cell in each time period.

As an example, the time period may be divided in units of hours, for example, 120 walking trips and 78 car trips in the period of 6 to 7 am, 578 walking trips and 312 car trips in the period of 7 to 8 am, and these time sequence distribution data are input into corresponding simulation models in the line planning scheme to obtain simulation results corresponding to the residents of the target cell under the current line planning scheme when the residents appear, and parameters in the planning targets are extracted from the simulation results to measure the performance of the line planning scheme, wherein the process of the travel simulation for the residents may employ TESS NG

Simulation software such as (microscopic traffic simulation software) and VISSIM (traffic simulator) constructs a road traffic simulation model to realize, but is not limited to, and furthermore, the time period can be divided in minutes, and the time period is specific to the traffic flow condition in each minute cell, so as to obtain more accurate time sequence distribution data.

As an example, steps S21 to S22 include: constructing a corresponding simulation model according to each wire-bound planning scheme in the first wire-bound planning scheme set; inputting the people flow time sequence distribution data and the traffic flow time sequence distribution data into each simulation model to obtain a corresponding simulation result; extracting the pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length corresponding to each line planning scheme in the first line planning scheme set from each model result; and inputting weights corresponding to the pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length, which are corresponding to the respective line planning schemes, into a preset fitness function, and calculating to obtain a first fitness corresponding to each line planning scheme in the first line planning scheme set.

Wherein, as an example, the fitness function has the expression:

wherein ,for the first fitness->For the travel duration of pedestrians, the pedestrian is->For the weight corresponding to the pedestrian travel duration,for the probability of meeting a person or a car, < > a person or a car>Weight corresponding to the probability of meeting the vehicles and the passenger, and +.>For the duration of travel of the vehicle>Weight corresponding to the travel duration of the vehicle, < ->For pedestrian density->Weight corresponding to the pedestrian density, +.>For the parking stall seek duration,>and searching for the weight corresponding to the duration for the parking space.

Wherein the step of performing selection, crossover and mutation operations on each of the wire-bound plans based on the preset genetic algorithm and the first fitness to obtain a second wire-bound plan set includes:

step S31, calculating the sum of first fitness corresponding to all the wire-bound planning schemes in the first wire-bound planning scheme set to obtain total fitness;

step S32, determining individual selection probability of each wire-line planning scheme based on the ratio of the first fitness to the total fitness corresponding to each wire-line planning scheme;

and step S33, selecting a plurality of parent individuals from the wire-bound planning schemes according to the individual selection probability, and executing intersection and mutation operations on the parent individuals to obtain a second wire-bound planning scheme set.

In the embodiment of the application, it should be noted that, in the embodiment of the application, a genetic algorithm is adopted to process each planning scheme in an initial first line planning scheme set, the genetic algorithm is an algorithm for improving the design of evolution rules of the reference biology simulating natural evolution searching optimal solutions, the unprocessed first line planning scheme set is taken as an original individual, operations such as simulating natural selection variation in the natural world are adopted for the individuals, each line planning scheme in a corresponding second line planning scheme set is generated, namely, the individual after genetic evolution is obtained, and finally, according to the fitness of each line planning scheme, the optimal solution, namely, the line planning scheme with highest traffic efficiency is selected and applied to a target cell, so that line design or upgrading transformation of the target cell is completed. In addition, in the embodiment of the application, a proportional fitness selection (proportional fitness assignment) method is adopted to allocate the selection probability of each line planning scheme, which is a method of determining the selection probability completely by the fitness, so that the line planning scheme with higher fitness has higher selection probability and higher chance of becoming a parent, and further, the child individuals (line planning schemes in the second line planning scheme set) obtained by evolution also have higher fitness. The step of selecting a plurality of parent individuals from each of the routing schemes according to the individual selection probability includes selecting a group of routing schemes as parent individuals from the set of first routing schemes based on the individual selection probability and a selection method (such as roulette rules), and the crossover and mutation operations are common technical means of genetic algorithms in the prior art, which are not described herein.

As an example, step S31 to step S33 include: calculating the sum of first fitness corresponding to all the wire-bound planning schemes in the first wire-bound planning scheme set to obtain total fitness; calculating the ratio of the first fitness to the total fitness corresponding to each of the wire-bound planning schemes, and determining the individual selection probability of each of the wire-bound planning schemes; based on the individual selection probability of each wire-line planning scheme, carrying out roulette selection on each wire-line planning scheme to obtain a parent individual set; sequentially carrying out pairwise crossing operation on the parent individuals in the parent individual set to obtain crossed first child individuals; and carrying out mutation operation on each first child individual based on preset mutation probability to obtain a mutated second child individual and a second line planning scheme set formed by each second child individual.

As another example, the step of performing the selecting, crossing and mutating operations on each of the wire-line planning schemes based on the preset genetic algorithm and the first fitness, and obtaining the second set of wire-line planning schemes may further include:

step S34, inputting a preset individual selection probability function into a first fitness corresponding to each wire-line planning scheme to obtain individual selection probability corresponding to each wire-line planning scheme;

Step S35, selecting a plurality of parent individuals from each of the line planning schemes according to the individual selection probability, and executing intersection and mutation operations on the parent individuals to obtain a second line planning scheme set;

wherein the expression of the individual selection probability function is:

The step of obtaining a second routing plan set includes:

step S331, selecting a plurality of parent individuals from each line planning scheme based on the individual selection probability;

step S332, performing cross operation on the parent individuals to obtain a first child individual set;

step S333, performing mutation operation on the first child individual set to obtain a second child individual set;

step S334, return to execute the following steps: selecting a plurality of parent individuals in each of the routing schemes based on the individual selection probabilities;

And step S335, setting the second sub-individual set as a second line planning scheme set when a preset condition is met, wherein the preset condition is that a line planning scheme with the fitness higher than a preset fitness or the iteration number of which is not lower than a preset threshold exists in the second sub-individual set.

In the embodiment of the present application, it should be noted that, the executing steps of the steps S331 to S335 are as shown in fig. 2, and the embodiment of the present application obtains enough new wire planning schemes by repeatedly executing the operations of selecting, intersecting and mutating each wire planning scheme, and then selects the target wire planning scheme based on the fitness values of all the wire planning schemes, so as to obtain the wire planning scheme most suitable for the target cell, so as to improve the traffic efficiency of residents in the target cell, and avoid the problems of redundancy, congestion, and the like; in addition, the preset condition can automatically select whether to stop iteration based on the fitness or whether to stop iteration based on the iteration times according to specific requirements, if the adaptability requirements on the line planning schemes are more accurate, the stop time is selected based on the adaptability of each line planning scheme in the second child individual set, so that the line planning schemes meeting the preset fitness can be obtained; if a routing scheme with the highest global angle is wanted, a preset threshold value which is large enough can be set to obtain a large number of routing schemes, and then the routing scheme with the highest global angle is selected, so that the problem of local optimization can be avoided.

In addition, the roulette rule is applied to select a plurality of parent individuals among the roulette schemes, and a precedence order exists among the roulette schemes in the first roulette scheme set.

As an example, steps S331 to S335 include: calculating the accumulated probability of each of the routing schemes according to the individual selection probability of each of the routing schemes, wherein the accumulated probability is equal to the sum of the individual selection probability of the routing scheme and the individual selection probability of all routing schemes arranged before the routing scheme; generating a uniformly distributed pseudo random number r in the [0,1] interval, and judging whether r is smaller than the individual selection probability of the line planning schemes with the arrangement order of 1 in each line planning scheme; if the number is smaller than the first set, selecting a line planning scheme with the arrangement order of 1 as a parent individual; if not, selecting a line planning scheme with the ordering order of k as a parent, wherein the cumulative probability of the line planning scheme with the ordering order of k is larger than r and the cumulative probability of the line planning scheme with the ordering order of k-1 is smaller than r; returning to the execution step: generating a uniformly distributed pseudo random number r in the interval [0,1] until the number of selected parent individuals reaches a preset number; binary coding is carried out on each parent individual to obtain a chromosome of each parent individual, wherein the chromosome of each parent individual comprises an individual coding string; randomly exchanging parent individuals to obtain fragments in individual coding strings in chromosomes to obtain child individuals and a first child individual set formed by the child individuals, wherein the number of parent individuals participating in exchange can be two or more. Acquiring a preset variation probability; generating a uniformly distributed pseudo random number s in the interval [0,1], and judging whether s is not more than a preset variation probability; if not, inverting the first bit of the individual code strings of the child individuals sequenced to 1 in the first child individual set; if the value is greater than the preset value, no treatment is carried out; returning to the execution step: generating a uniformly distributed pseudo random number s in the interval [0,1], judging whether s is not more than a preset mutation probability or not until all bits of all child individuals in the first child individual set are processed, and obtaining each child individual after mutation and a second child individual set formed by each child individual; the process returns to the execution step S331: and selecting a plurality of parent individuals from each of the routing schemes based on the individual selection probability, and executing step S332-step S333 until the position meeting the preset condition is reached, and setting the obtained second child individual set as a second routing scheme set.

As an example, the expression for calculating the cumulative probability of each of the floor planning schemes is:

wherein ,is the sequence number->Cumulative probability of the wire-bound programming scheme, +.>Sequence number for line planning scheme,/->For the initial sequence number of the summation>Probabilities are selected for the individuals.

As an example, when the Crossover operation is performed on the parent individuals and the number of parent individuals participating in Crossover is 2, a Single-point Crossover (Single-point crosslever) or a Two-point Crossover/multiple-point crosslever (Two-point/multiple-point crosslever) shown in fig. 3, and a 5-point Crossover (m=5) shown in fig. 4 may be selected, wherein the Single-point Crossover refers to that only one Crossover point is randomly set in an individual code string, the chromosome is divided into Two parts, and the left and right sides of the child chromosome are respectively derived from the chromosomes of Two parent individuals. Two-point crossing/multi-point crossing means that two or more crossing points are randomly arranged in an individual code string, and then partial fragment switching is performed in a space switching manner.

Wherein the first set of child individuals includes child individuals, and the step of performing a crossover operation on the parent individuals to obtain the first set of child individuals includes:

step A10, a plane rectangular coordinate system is established based on the map information of the target cell, and coordinates of points on a line corresponding to the parent are obtained in the plane rectangular coordinate system;

Step A20, binary coding is carried out on the parent individuals based on the coordinates, and chromosomes of the parent individuals are obtained;

step A30, randomly exchanging the segments of the chromosomes of each parent individual to generate corresponding offspring individuals.

In the embodiment of the present application, it should be noted that when the plane rectangular coordinate system is established, an edge point of the target cell may be selected as the origin when the origin is selected, for example, if the map shape of the target cell is a rectangle, then the vertex of the lower left corner of the rectangle may be selected as the origin of the plane rectangular coordinate system, so that the coordinate value of each point on the moving line of the line planning scheme is a positive number, so as to facilitate calculation. The process of binarizing the parent individual is the process of binarizing the coordinates of the parent individual. For example, the coordinates of the starting point on the moving line of a certain line planning scheme are (3, 6), the coordinates of the second sampling point are (6, 7) and the coordinates of the third sampling point are (7, 9), and the coordinates are (0011, 0110), (0110,0111) and (0111,1001) after being converted into the binary form, respectively, and the corresponding individual code string is 001101100110011101111001, where it should be noted that the number of bits of the binary number and the number of sampling points after the coordinates are converted into the binary form can be set according to the specific situation, and the present invention is not limited thereto. In addition, the minimum exchange unit of the fragments in the process of randomly exchanging the fragments of the chromosomes of each parent individual is a code string corresponding to one point, for example, in the process of exchanging the fragments of the chromosomes, the selected fragments are at least 8-bit binary codes, and the binary code strings corresponding to the fragments are used for representing coordinates of one or more points.

As an example, steps a10 to a30 include: according to the map information of the target cell, selecting a vertex in the target cell as an origin, and establishing a plane rectangular coordinate system based on the origin; reading coordinates of sampling points on the moving lines of each parent in the plane rectangular coordinate system, binarizing the coordinates to obtain individual code strings of each parent; and cutting and randomly exchanging the coding string fragments of each parent individual according to the crossing points on the individual coding strings to generate new child individuals.

Wherein the map information at least includes fixed area information, and the step of randomly generating a first set of wire-bound planning schemes based on the map information of the target cell includes:

and S11, taking the fixed area information in the map information of the target cell as a limiting condition of a wire-line planning scheme, and randomly generating a plurality of wire-line planning schemes corresponding to the target cell based on the limiting condition to obtain a first wire-line planning scheme set.

In this embodiment of the present application, it should be noted that, the target cell may be a new cell to be planned and designed, or may be an old cell to be upgraded and modified, and the fixed area information is an area which is already designed in the target cell and cannot be modified or a part of the old cell which is not modified according to specific requirements, and the line planning scheme in this embodiment of the present application is generated on the above-mentioned constraint condition, and cannot contradict the fixed area information.

The embodiment of the application provides a district line planning method, firstly, a first line planning scheme set is randomly generated based on map information of a target district, then, according to planning targets and traffic flow data of the target district, first fitness corresponding to each line planning scheme in the first line planning scheme set is calculated, wherein the planning targets at least comprise weights respectively corresponding to pedestrian travel time length, pedestrian meeting probability, vehicle travel time length, pedestrian density and parking space searching time length, further, based on a preset genetic algorithm and the first fitness, selection, crossing and variation operations are carried out on each line planning scheme to obtain a second line planning scheme set, finally, a line planning scheme with the highest fitness is selected from the first line planning scheme set and the second line planning scheme set as a target line planning scheme, wherein the target line planning scheme is used for planning the line of a target cell, the technical scheme of the embodiment of the application combines parameters such as pedestrian travel time length, pedestrian and vehicle meeting probability, vehicle travel time length, pedestrian density, parking space searching time length and the like in the planning target to calculate the fitness, comprehensively considers the evaluation results of each dimension of the path passing efficiency in the line planning scheme, selects, crosses and mutates the initialized first line planning scheme by adopting a genetic algorithm to obtain an evolved second line planning scheme, searches the optimal solution of line planning according to the fitness of each line planning scheme to obtain the target line planning scheme with the highest fitness, realizes the line planning of the cell by replacing manual operation with an artificial intelligent algorithm, the technical defect that limitation exists in planning the cell line based on experience and intuition of a designer is overcome, and the path passing efficiency of planning the cell line is improved.

Example two

The embodiment of the application also provides a cell wire-line planning device, the cell wire-line planning device is applied to a cell wire-line planning device, and referring to fig. 5, the cell wire-line planning device includes:

an initialization module 101, configured to randomly generate a first set of wire-line planning schemes based on map information of a target cell;

the fitness calculating module 102 is configured to calculate, according to a planning target of the target cell and traffic flow data, a first fitness corresponding to each of the first line planning schemes in the first line planning scheme set, where the planning target at least includes weights corresponding to a pedestrian travel duration, a pedestrian and vehicle meeting probability, a vehicle travel duration, a pedestrian density, and a parking space searching duration, respectively;

the genetic evolution module 103 is configured to perform selection, crossover and mutation operations on each of the wire-line planning schemes based on a preset genetic algorithm and the first fitness, so as to obtain a second wire-line planning scheme set;

and a solution screening module 104, configured to select a routing plan with the highest fitness from the first routing plan set and the second routing plan set as a target routing plan, where the target routing plan is used for planning a routing line of a target cell.

Optionally, the fitness calculating module is further configured to:

Optionally, the genetic evolution module is further configured to:

wherein the expression of the individual selection probability function is:

Optionally, the genetic evolution module is further configured to:

Optionally, the initialization module is further configured to:

The cell line planning device provided by the application adopts the cell line planning method in the embodiment, and solves the technical problem of low path passing efficiency of the traditional cell line planning scheme. Compared with the prior art, the beneficial effects of the cell line planning device provided by the embodiment of the present application are the same as those of the cell line planning method provided by the above embodiment, and other technical features in the cell line planning device are the same as those disclosed in the method of the previous embodiment, which are not described in detail herein.

Example III

The embodiment of the application provides electronic equipment, the electronic equipment includes: at least one processor; and a memory communicatively linked to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the cell line planning method of the first embodiment.

Referring now to fig. 6, a schematic diagram of an electronic device suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistant, personal digital assistants), PADs (tablet computers), PMPs (Portable Media Player, portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 6 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.

As shown in fig. 6, the electronic device may include a processing means (e.g., a central processing unit, a graphic processor, etc.) that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) or a program loaded from a storage means into a random access memory (RAM, random access memory). In the RAM, various programs and data required for the operation of the electronic device are also stored. The processing device, ROM and RAM are connected to each other via a bus. Input/output (I/O) interfaces are also linked to the bus.

In general, the following systems may be linked to I/O interfaces: input devices including, for example, touch screens, touch pads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices including, for example, liquid crystal displays (LCDs, liquid crystal display), speakers, vibrators, etc.; storage devices including, for example, magnetic tape, hard disk, etc.; a communication device. The communication means may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. While electronic devices having various systems are shown in the figures, it should be understood that not all of the illustrated systems are required to be implemented or provided. More or fewer systems may alternatively be implemented or provided.

In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from ROM. The above-described functions defined in the methods of the embodiments of the present disclosure are performed when the computer program is executed by a processing device.

The electronic equipment provided by the application adopts the cell line planning method in the embodiment, and solves the technical problem of low path passing efficiency of the traditional cell line planning scheme. Compared with the prior art, the beneficial effects of the electronic device provided by the embodiment of the present application are the same as those of the cell line planning method provided by the first embodiment, and other technical features of the electronic device are the same as those disclosed by the method of the previous embodiment, which are not described in detail herein.

It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the description of the above embodiments, particular features, structures, materials, or characteristics may be combined in any suitable manner in any one or more embodiments or examples.

The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Example IV

The present embodiment provides a computer readable storage medium having computer readable program instructions stored thereon for performing the method of cell line planning in the first embodiment.

The computer readable storage medium provided by the embodiments of the present application may be, for example, a usb disk, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical link having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (EPROM, erasable Programmable Read-Only Memory, or flash Memory), an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this embodiment, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, or device. Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

The above-described computer-readable storage medium may be contained in an electronic device; or may exist alone without being assembled into an electronic device.

The computer-readable storage medium carries one or more programs that, when executed by an electronic device, cause the electronic device to: randomly generating a first line planning scheme set based on map information of a target cell; calculating a first fitness corresponding to each line planning scheme in the first line planning scheme set according to the planning target and traffic flow data of the target cell, wherein the planning target at least comprises weights respectively corresponding to pedestrian travel time length, pedestrian and vehicle meeting probability, vehicle travel time length, pedestrian density and parking space searching time length; based on a preset genetic algorithm and the first fitness, selecting, crossing and mutating operations are carried out on each wire-line planning scheme, and a second wire-line planning scheme set is obtained; and selecting a wire-line planning scheme with highest fitness from the first wire-line planning scheme set and the second wire-line planning scheme set as a target wire-line planning scheme, wherein the target wire-line planning scheme is used for planning the wire line of a target cell.

Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be linked to the user's computer through any kind of network, including a local area network (LAN, local area network) or a wide area network (WAN, wide Area Network), or it may be linked to an external computer (e.g., through the internet using an internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The modules described in the embodiments of the present disclosure may be implemented in software or hardware. Wherein the name of the module does not constitute a limitation of the unit itself in some cases.

The computer readable storage medium provided by the application stores computer readable program instructions for executing the cell line planning method, and solves the technical problem of low path passing efficiency of the traditional cell line planning scheme. Compared with the prior art, the beneficial effects of the computer readable storage medium provided in the embodiment of the present application are the same as those of the cell line planning method provided in the above embodiment, and are not described in detail herein.

Example five

The computer program product provided by the application solves the technical problem of low path passing efficiency of the traditional cell line planning scheme. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as those of the cell line planning method provided by the above embodiment, and are not described herein.

The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the scope of the claims, and all equivalent structures or equivalent processes using the descriptions and drawings of the present application, or direct or indirect application in other related technical fields are included in the scope of the claims.

Claims

1. A cell line planning method, characterized in that the cell line planning method comprises:

selecting a wire-bound planning scheme with highest fitness from the first wire-bound planning scheme set and the second wire-bound planning scheme set as a target wire-bound planning scheme, wherein the target wire-bound planning scheme is used for planning wires of a target cell;

2. The cell wire-planning method of claim 1 wherein the step of performing the selecting, crossing and mutating operations on each of the wire-planning schemes based on a predetermined genetic algorithm and the first fitness to obtain a second set of wire-planning schemes comprises:

3. The cell wire-line planning method of claim 2 wherein the step of performing the selecting, crossing and mutating operations on each of the wire-line planning schemes based on the predetermined genetic algorithm and the first fitness to obtain a second set of wire-line planning schemes comprises:

Wherein the expression of the individual selection probability function is:

4. The cell routing method of claim 2, wherein the second set of routing schemes includes child individuals, wherein the step of selecting a parent individual from among the routing schemes based on the individual selection probabilities, and performing crossover and mutation operations on the parent individual, and wherein the step of obtaining the second set of routing schemes includes:

5. The cell line planning method of claim 4 wherein the first set of child individuals comprises child individuals, and wherein the step of performing a crossover operation on the parent individuals comprises:

6. The cell wire-planning method of claim 1, wherein the map information includes at least fixed area information, and wherein the step of randomly generating the first wire-planning scheme set based on the map information of the target cell includes:

and taking the fixed area information in the map information of the target cell as a limiting condition of a wire-line planning scheme, and randomly generating a plurality of wire-line planning schemes corresponding to the target cell based on the limiting condition to obtain a first wire-line planning scheme set.

7. A cell line planning apparatus, characterized in that the cell line planning apparatus comprises:

the scheme screening module is used for selecting a routing scheme with highest fitness from the first routing scheme set and the second routing scheme set as a target routing scheme, wherein the target routing scheme is used for planning a routing of a target cell;

the traffic flow data at least comprises time sequence distribution data of people flow and traffic flow in a target cell, and the fitness calculation module is further used for: determining the corresponding pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length of each of the wire-bound planning schemes according to the time sequence distribution data and each of the wire-bound planning schemes in the first wire-bound planning scheme set; and inputting weights corresponding to the pedestrian travel time length, the pedestrian and vehicle meeting probability, the vehicle travel time length, the pedestrian density and the parking space searching time length, which are corresponding to the respective line planning schemes, into a preset fitness function to obtain a first fitness corresponding to the line planning schemes in the first line planning scheme set.

8. An electronic device, the electronic device comprising:

at least one processor; the method comprises the steps of,

a memory communicatively linked to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the cell line planning method of any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a program for realizing a cell wire-line planning method, the program for realizing a cell wire-line planning method being executed by a processor to realize the steps of the cell wire-line planning method according to any one of claims 1 to 6.