CN111489018A

CN111489018A - Dynamic self-adaptive intelligent station group arrangement method and system

Info

Publication number: CN111489018A
Application number: CN202010235509.XA
Authority: CN
Inventors: 钟志华; 吴军
Original assignee: Dexin Smart Technology Shanghai Co ltd; Tongji University
Current assignee: Dexin Smart Technology Shanghai Co ltd; Tongji University
Priority date: 2020-03-30
Filing date: 2020-03-30
Publication date: 2020-08-04

Abstract

The invention discloses a dynamic self-adaptive intelligent station group arrangement method and a system, wherein in a target urban area, all intelligent stations are marked in a road system and presented in an electronic map of a travel reservation program so as to display the specific position of each intelligent station; the intelligent station comprises a plurality of established fixed stations and a plurality of virtual stations with adjustable positions; the distribution density and the position of the virtual sites refer to at least the following influence factors: crowd density, travel demand intensity and actual geographic characteristics of a specific area; the influence factors are all displayed in the travel appointment program; the virtual stop is at a position point in the road system where a stop is legal for the vehicle to receive the passenger. The arrangement mode of the intelligent stations can be dynamically optimized, so that passengers can be conveniently positioned and found, and the running efficiency of urban traffic is improved.

Description

Dynamic self-adaptive intelligent station group arrangement method and system

Technical Field

The invention belongs to the field of big data processing, and particularly relates to a station group system for public transportation.

Background

The existing urban public transportation system has the problems of fixed line stations, low operation speed, long walking distance of passengers, long waiting time, poor comfort degree and the like, and is difficult to adapt to the strong demands of urban residents on the improvement of the future advanced urban trip service quality. One of the difficulties is that the arrangement method of bus stops lags behind, a bus company receives a demand (generally, the construction of a new road or a new area) in a certain time period, the design of the stations is comprehensively considered according to population density, commercial density, the utilization property of surrounding land, the grade of the urban road, the transfer connection of the surrounding land and the like, and the distance between the stations is generally between 200m and 1.5 km. The design of the final station is less than satisfactory.

The prior art has the following defects:

1. the existing bus stop is limited by the existing bus system, the coverage rate is poor (the coverage rate is less than 80%, the detour distance is long, the average nonlinear coefficient is as high as 1.95, and the problem of the last kilometer is prominent);

2. the position of the site is determined by the population density and business density of the design and arrangement at the time, and cannot be adjusted in time along with the change of time;

3. because the existing bus station needs to be built, the project amount is relatively large, the cost is high, and the bus station is limited by the surrounding environment.

Disclosure of Invention

The invention provides a dynamic self-adaptive intelligent station group arrangement method and system, which can dynamically optimize the arrangement mode of intelligent stations so as to facilitate the positioning and searching of passengers and improve the operation efficiency of urban traffic.

The purpose of the invention is realized as follows: the dynamic self-adaptive intelligent station group arrangement method comprises an intelligent station arrangement step, wherein when the step is implemented, all intelligent stations are marked in a road system in a target urban area and are displayed in an electronic map of a travel reservation program so as to display the specific position of each intelligent station;

the intelligent station comprises a plurality of established fixed stations and a plurality of position-adjustable virtual stations;

the distribution density and the position of the virtual sites refer to at least the following influence factors: crowd density, travel demand intensity and actual geographic characteristics of a specific area;

the above-mentioned influence factors are all displayed in the travel appointment program;

the virtual stop is positioned at a position point of a legal parking passenger in the road system.

Furthermore, the distribution density and the positions of the virtual stations are also referred to the normal pace of the ordinary person, the distance between any two adjacent virtual stations is set by taking the normal pace of the ordinary person as a reference, and the distance between any two adjacent virtual stations is not less than 100 meters.

Further, the distribution density of the virtual sites increases as the population density, which is measured by a travel reservation program and a regional thermodynamic diagram analysis, increases.

Further, the travel demand intensity is based on the reserved travel frequency and the crowd density in different time periods.

Further, the actual geographic feature of the specific area includes an outline shape of the specific area.

Further, the distribution density and the position adjustment frequency of the virtual sites refer to an actual travel state; aiming at an area with weakened travel demand intensity, reducing the number of virtual sites in the area; and aiming at the area with the enhanced travel demand intensity, increasing the distribution density of the virtual sites of the area, or increasing the number of the virtual sites of the area.

Further, the position of the virtual site can be set by one or more users in an electronic map of a travel reservation program to be a newly added virtual site.

As another aspect of the present invention, a system to which the above arrangement method is applied includes:

the master control end is used for gathering information of all intelligent stations in real time, arranging and adjusting positions of the virtual stations and sharing the processed information of the intelligent stations to users and bus drivers;

and the user side with the travel reservation program is used for selecting the starting intelligent station and/or the destination intelligent station, generating and displaying the optimal travel route scheme, and displaying all the intelligent station information shared by the master control side.

The system also comprises a navigation module which navigates the bus driver to any intelligent station according to the bus route.

The user side with the travel reservation program is a mobile phone or an electronic screen of a built fixed station.

The beneficial effects of the invention include:

1. the arrangement mode of the intelligent stations can be dynamically optimized, the area with dense population and travel demand can be well covered, the distribution density and the position of the intelligent stations can be timely adjusted according to the change of the travel demand, so that passengers can be conveniently positioned and searched, the running efficiency of urban traffic is improved, and the utilization rate of public traffic resources is improved;

2. the flexibility of travel selection of the user is improved, the user can carry out autonomous marking setting in an electronic map of a travel reservation program to become a newly-added virtual station, or the system automatically allocates the position and distribution density of the virtual station, so that the virtual station closest to the travel reservation program or a built fixed station is marked according to travel requirements, and the travel distance of passengers is reduced as much as possible;

3. all the intelligent stations can be presented in an electronic map of a travel reservation program and can be selected as target stations, the user reservation program can be arranged on a mobile phone and a touch screen computer (or a special electronic device) of a bus station, and an optimized travel scheme can be formed according to a destination selected by a client;

4. the established fixed station is continuously reserved and embodied in the user reservation program, and meanwhile, the original physical bus station also provides a physical intelligent reservation inquiry terminal, so that convenience is brought to the old, children and users who are inconvenient to use the mobile reservation program.

Drawings

FIG. 1 is a flow chart of the collection of intelligent station group information;

FIG. 2 is a flow chart of the setup of an intelligent site group;

FIG. 3 is a flow chart of dynamic adjustment of an intelligent site group.

Detailed Description

The dynamic self-adaptive intelligent station group arrangement method comprises an intelligent station arrangement step, wherein when the step is implemented, all intelligent stations are marked in a road system in a target urban area and are displayed in an electronic map of a travel reservation program so as to display the specific position of each intelligent station.

The intelligent station comprises a plurality of established fixed stations and a plurality of virtual stations with adjustable positions;

the distribution density and the position of the virtual sites are at least referred to the following influence factors: crowd density, travel demand intensity and actual geographic characteristics of a specific area;

the virtual station is positioned at a position point of a road system where a vehicle is legally parked and received.

The system applicable to the dynamic self-adaptive intelligent station group arrangement method comprises the following steps:

Considering that different travel demands exist in different urban areas, the road system is divided into two basic types, namely a road network and a mesh in the embodiment.

The road network consists of road sections and road section intersection nodes. The road section refers to a section of urban road for daily running of public transport vehicles, and can be unidirectional or bidirectional, single-channel or multi-channel.

The mesh refers to a closed area which is formed by surrounding adjacent road sections and does not contain other road sections, and can be a closed residential area, a factory area, a special area and the like.

The system considers the following factors in units of meshes in the intelligent station distribution design:

1. population density: the distribution density of residents or workers in the meshes is measured and calculated by a travel reservation program according to the sampling test and the analysis of the regional thermodynamic diagram, the population density influences the distribution density of the intelligent stations in the region, and the greater the general population density is, the greater the distribution density of the intelligent stations (particularly virtual stations) is;

2. the intensity of travel demand: the travel reservation program calculates travel demand intensity of different sections in the mesh according to travel frequency and crowd density of different sections, and the travel demand intensity is used as a main basis for setting the intelligent station;

3. reachability regional actual geographic features such as rivers, cells, factories, stations, business centers, and the like will affect the reachability of the smart site, thereby affecting the actual distribution of the smart site;

4. meanwhile, considering the normal pace of the ordinary people and the willingness of the ordinary people to walk and wait for the vehicles in different areas, the distance between two adjacent intelligent stations is divided into the following steps:

100 meters (which can make walking more comfortable): walking at an average pace (5 km/h) for about 1 minute and 12 seconds;

200 m: walking at an average pace (5 km/h) for about 2 minutes and 24 seconds;

300 m: walking at an average pace (5 km/h) for about 3 minutes 36 seconds;

400 m: walking at an average pace (5 km/h) for about 4 minutes 48 seconds;

500 m: walking at an average pace (5 km/h) for about 6 minutes;

over 500 m.

Combining the above factors, the site specific location in the system coverage area is determined by the following steps.

As shown in fig. 1, step 1: information acquisition process of intelligent station group

The intelligent station group system collects information such as the position of an appropriate intelligent station on a road section along the periphery of the mesh to generate a system map database. The intelligent site may be the following: (1) a temporary parking place for the public on the road section; (2) a non-public temporary parking spot, a smart city trip parking spot with allowed road conditions and approved by a road administration department, and a certain mark; (3) the location of the fixed platform has been established.

The intelligent station information is collected through the following modes:

1. according to the input of relevant geography and city planning data (geographic data) of a municipal system, identifying the position of a mesh by software in an auxiliary way, and simultaneously preliminarily determining alternative addresses of intelligent stations and compiling corresponding serial numbers of each address on road sections around the mesh;

2. setting a site distance standard in the mesh according to the relevant geography of the municipal system and city planning data (geographic data);

3. according to the data of the urban thermodynamic diagram, calibrating the personnel density and the trip frequency of the road section around the mesh;

4. the intelligent site group design group surveys in the field, finally determines the latitude and longitude of the alternative address and determines the final serial number.

Step 2: setting of intelligent station group

And the master control end sets the intelligent station from the alternative address set according to the required intensity and outputs the station information to the vehicle scheduling and reservation system. The selection of the intelligent station is based on the following principle: 1, the distance between the stations meets the standard; 2, all road sections along the periphery of the mesh can be covered by stations at a standard station interval, namely, intelligent stations are arranged on the road sections around the mesh at a standard station distance; 3. road conditions are allowed and approved by road authorities.

Fig. 2 shows a flow of setting the smart site group:

1. one or more core cells are selected as the starting cells for the smart site setup and their characteristic dimension H, i.e., the maximum value of the distance between any two building exits commonly used in the cells, is calculated. If multiple core cells are processed in parallel, the core cells should not be adjacent to each other;

2. analyzing the distribution density P and the trip frequency F of residents or workers in each starting mesh;

3. calculating the travel demand intensity distribution X of the mesh (P × F) according to a certain mesh precision (the site distance standard L b can be used as the mesh division precision);

4. finding the grid WXmax of the maximum value of X;

5. finding a place Dj closest to WXmax from the alternative site set D, and determining the place Dj as a core site;

6. if the station distance standard L b of the mesh is less than H, stations do not need to be arranged around the mesh, otherwise, a point closest to L b away from the core station is searched in the candidate station set, and the candidate station set is set as an intelligent station;

7. drawing a circle (the circle becomes a station covering circle) by taking the determined station as a center and taking L b as a radius, if the union of the circles completely covers the mesh, no new station is needed to be arranged at the periphery of the mesh, otherwise, the steps 1-6 are repeated until the union of all station covering circles completely covers the mesh;

8. setting up stations for all core meshes by the method;

9. continuously arranging stations for adjacent meshes of the station in the same method until all the stations of the meshes are arranged;

10. if a plurality of core meshes are selected, the station arrangement of all the core meshes and adjacent meshes thereof should be synchronously advanced in a hierarchical level;

11. for the situation of one core mesh, the station settings of adjacent meshes of two core meshes may conflict, and then the addressing of the stations needs to be compromised, for example, the conflict can be solved by reducing or increasing the distance standard between the stations;

12. when processing adjacent meshes of the core mesh, firstly calculating the travel demand distribution X of the adjacent meshes, firstly setting a station according to X, and then coordinating with the set station;

13. the stop of the bidirectional road can also be arranged in two directions, and is similar to the conventional bus stop at present.

As shown in fig. 3, step 3: the dynamic adjustment process of the intelligent station group comprises the following steps:

1. the station of the established fixed station platform is determined as a first-stage station;

2. according to the number of the reserved persons in the travel reservation program, the intelligent virtual station can be set as a primary station or a secondary station, periodic dynamic adjustment is allowed, the adjustment frequency can be set according to the reference actual travel habit, and adjustment is performed once every quarter by default;

3. the system monitors the service condition of the stations, gradually eliminates the intelligent stations or areas with less use, and dynamically optimizes the intelligent station setting in the areas by adjusting the distance standard L b of the intelligent stations according to the mesh theory for the areas with stronger requirements;

4. recommendation of additional sites: in the travel system of the smart city, passengers can also recommend stations through the station recommending function of the travel reservation program, when the recommended number of people reaches more than 100, the system adds the smart stations into a candidate station group, and performs fusion optimization with peripheral smart stations according to the mesh theory;

5. the bus stop information is gathered to the master control end, the bus stop information is intelligently processed by the master control end and then is shared with a user and a bus driver, the user can inquire the bus stop position, the bus stop distance, the bus route and the predicted arrival time of the bus through a reservation program or a reservation terminal, and the system navigates the bus driver to each intelligent bus stop according to the bus route.

It should be noted that while the foregoing has described the spirit and principles of the invention with reference to several specific embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, nor is the division of aspects, which is for convenience only as the features in these aspects cannot be combined. The invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A dynamic self-adaptive intelligent station group arrangement method comprises an intelligent station arrangement step, wherein when the step is implemented, all intelligent stations are marked in a road system in a target urban area and are presented in an electronic map of a travel reservation program so as to display the specific position of each intelligent station, and the method is characterized in that:

2. The method as claimed in claim 1, wherein the distribution density and the location of the virtual stations are further determined by reference to a normal pace of a human, the distance between any two adjacent virtual stations is determined by reference to the normal pace of the human, and the distance between any two adjacent virtual stations is within a comfortable walking range.

3. The method as claimed in claim 2, wherein the distribution density of the virtual sites increases with the increase of population density, and the population density is measured by a travel reservation program and a regional thermodynamic diagram analysis.

4. The method of claim 2, wherein the intensity of travel demand is based on the frequency of scheduled trips and crowd density at different time intervals.

5. The method of claim 2, wherein the area-specific physical geographic feature comprises a shape of an outline of the area-specific physical geographic feature.

6. The method according to claim 4, wherein the distribution density and the position adjustment frequency of the virtual sites refer to an actual travel state; aiming at an area with weakened travel demand intensity, reducing the number of virtual sites in the area; and aiming at the area with the enhanced travel demand intensity, increasing the distribution density of the virtual sites of the area, or increasing the number of the virtual sites of the area.

7. The method as claimed in claim 1, wherein the virtual site is configured to be a newly added virtual site by one or more users making autonomous mark setting in an electronic map of a travel reservation program.

8. A system to which the arrangement method according to claims 1-7 is applied, characterized by comprising:

9. The system of claim, further comprising a navigation module for navigating a bus driver to any intelligent stop according to a bus route.

10. The system of claim, wherein the user terminal with travel reservation program is a mobile phone or an electronic screen of a built fixed site.