CN113066304B - Traffic capacity configuration system applying urban brain cloud platform - Google Patents
Traffic capacity configuration system applying urban brain cloud platform Download PDFInfo
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- CN113066304B CN113066304B CN202110616374.6A CN202110616374A CN113066304B CN 113066304 B CN113066304 B CN 113066304B CN 202110616374 A CN202110616374 A CN 202110616374A CN 113066304 B CN113066304 B CN 113066304B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
- G08G1/127—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams to a central station ; Indicators in a central station
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Abstract
A traffic capacity configuration system applying an urban brain cloud platform relates to the technical field of urban intelligent management. The system comprises an analysis module, a correction module and a configuration module. The analysis module is used for obtaining the distribution situation of the real-time population number based on the real-time GPS positioning heat and the city population number. And the correction module is used for confirming the potential traffic volume of the public transport by combining the video image analysis of the intersection and the public transport station according to the real-time population distribution condition. The configuration module is used for adjusting the public transportation shift of the corresponding area according to the public transportation potential transportation volume of each area so as to meet the requirement of the public transportation potential transportation volume. The system can accurately guide the allocation and optimization of traffic resources according to the real-time change of the urban traffic condition, can effectively improve the utilization rate of traffic capacity, enables the traffic transportation efficiency to be higher, is beneficial to reducing the waste of the traffic capacity and improves the smoothness of the overall urban traffic management.
Description
Technical Field
The invention relates to the technical field of urban intelligent management, in particular to a traffic capacity configuration system applying an urban brain cloud platform.
Background
With the continuous progress of internet technology, a service platform constructed based on the internet and intelligent technology increasingly serves the daily work and life of people. At present, although the application to the internet is more and more in the work of configuring the traffic capacity, the overall management level is still low, and how to integrally adjust and optimize the traffic resources according to the real-time traffic conditions of the city makes a key for improving the overall traffic resource management level of the city.
In view of this, the present application is specifically made.
Disclosure of Invention
The invention aims to provide a traffic capacity configuration system applying an urban brain cloud platform, which can accurately guide the allocation and optimization of traffic resources according to the real-time change of urban traffic conditions, effectively improve the utilization rate of traffic capacity, improve the traffic transportation efficiency, reduce the waste of traffic capacity and improve the overall traffic management smoothness of cities.
The embodiment of the invention is realized by the following steps:
a traffic capacity configuration system employing an urban brain cloud platform, comprising: the device comprises an analysis module, a correction module and a configuration module.
The analysis module is used for obtaining the distribution situation of the real-time population number based on the real-time GPS positioning heat and the city population number.
And the correction module is used for confirming the potential traffic volume of the public transport by combining the video image analysis of the intersection and the public transport station according to the real-time population distribution condition.
The configuration module is used for adjusting the public transportation shift of the corresponding area according to the public transportation potential transportation volume of each area so as to meet the requirement of the public transportation potential transportation volume.
Further, the number of people obtained by analyzing the video images of the public transportation stations is the real-time traffic volume of the corresponding public transportation stations. And analyzing the video images of the intersections to obtain the occupation ratios of the pedestrians, wherein the number of the pedestrians in the corresponding area is the product of the real-time population number and the occupation ratio of the pedestrians. The potential traffic volume of the public transportation is the difference between the number of pedestrians in the corresponding area and the real-time traffic volume of the public transportation station.
Further, the occupancy of the pedestrians is the ratio of the number of the pedestrians passing through the corresponding intersection to the total number of the pedestrians passing through the intersection. The total number of people passing through the intersection is the sum of the number of pedestrians and the number of people in passing vehicles, the number of people in the vehicles is the product of the number of passing vehicles and the average number of people in each vehicle, and the average number of people in each vehicle is the average number of people in each vehicle in the urban taxi taking platform. In the vehicles of the taxi taking platform, the number of the empty vehicles is marked as 1, the number of the non-empty vehicles is determined by the actual number of the vehicles, and the average number of the vehicles in each taxi taking platform is the total number of the taxi taking platform divided by the total number of the vehicles of the taxi taking platform.
Further, at 7-9 and 17-19 points per day on a weekday, the potential mass transit for offices and residential areas is 1.2 times.
Further, the potential traffic volume in commercial leisure areas is 1 time at 10-15 points per day on a working day.
Further, the potential traffic volume in commercial leisure areas is 1.2 times at 15-20 points per day on a weekday.
Further, the potential traffic volume in commercial leisure areas is 1.5 times at 15-20 points per day on non-working days.
Further, the traffic capacity configuration system applying the urban brain cloud platform further comprises an alarm module. The alarm module is used for alarming when at least one of the real-time traffic volume and the potential traffic volume of the public transportation at the public transportation station exceeds the traffic capacity of the corresponding area.
Further, the alarm module is also used for prompting when at least one of the real-time traffic volume and the potential traffic volume of the public transportation at the public transportation station exceeds 90% of the traffic capacity of the corresponding area and lasts for 10-20 min.
The embodiment of the invention has the beneficial effects that:
in the working process of the traffic capacity configuration system applying the urban brain cloud platform, the analysis module is used for obtaining the urban population distribution situation based on the real-time GPS positioning heat, wherein the GPS positioning heat has high precision and is a common positioning tool, and the GPS positioning heat can accurately reflect the distribution proportion situation of urban population under the condition of the popularity of the current smart phone. According to the real-time GPS positioning heat degree and the general population of the city, the real-time population quantity distribution condition of each area of the city can be calculated.
On the basis, the correction module can obtain the actual occupation ratio of the pedestrians by carrying out video image analysis on the video of the camera arranged at the intersection, and the pedestrians are potential transportation objects of the public transportation means and reflect the potential transportation amount of the public transportation means.
The configuration module is used for adjusting the public transport shift of the corresponding area according to the potential traffic volume of the public transport of each area, so that the actual required transport capacity of the transportation means is configured for each area, the requirement of the corresponding area in the corresponding time can be met, and the accurate distribution and scheduling of the public transport resources are realized.
Therefore, the corresponding public transportation resources can be matched according to the actual demand condition of each region, the condition of people flow congestion can be prevented, the possible idle or redundant public transportation resources can be reasonably utilized, and the method has positive significance for reducing the idle ratio of the public transportation resources. Therefore, the allocation of the public transportation resources can be more sufficient and reasonable, the method has a good reference meaning for reasonably planning the total amount of the public transportation resources in the whole city, and the extreme condition that the public transportation resources are excessive or insufficient can be avoided.
In general, the traffic capacity configuration system applying the urban brain cloud platform provided by the embodiment of the invention can accurately guide the allocation and optimization of traffic resources according to the real-time change of urban traffic conditions, can effectively improve the utilization rate of traffic capacity, enables the traffic transportation efficiency to be higher, is beneficial to reducing the waste of traffic capacity and improves the overall traffic management smoothness of cities.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments.
Thus, the following detailed description of the embodiments of the present invention is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
The embodiment provides a traffic capacity configuration system applying a city brain cloud platform, which comprises: the device comprises an analysis module, a correction module and a configuration module.
The analysis module is used for obtaining the distribution situation of the real-time population number based on the real-time GPS positioning heat and the city population number.
And the correction module is used for confirming the potential traffic volume of the public transport by combining the video image analysis of the intersection and the public transport station according to the real-time population distribution condition.
The configuration module is used for adjusting the public transportation shift of the corresponding area according to the public transportation potential transportation volume of each area so as to meet the requirement of the public transportation potential transportation volume.
In the working process, the analysis module is used for obtaining the population distribution situation of the city based on the real-time GPS positioning heat, wherein the GPS positioning heat has higher precision and is a common positioning tool, and the GPS positioning heat can accurately reflect the distribution proportion situation of the population of the city under the condition of the popularity of the current smart phone. According to the real-time GPS positioning heat degree and the general population of the city, the real-time population quantity distribution condition of each area of the city can be calculated.
On the basis, the correction module can obtain the actual occupation ratio of the pedestrians by carrying out video image analysis on the video of the camera arranged at the intersection, and the pedestrians are potential transportation objects of the public transportation means and reflect the potential transportation amount of the public transportation means.
The configuration module is used for adjusting the public transport shift of the corresponding area according to the potential traffic volume of the public transport of each area, so that the actual required transport capacity of the transportation means is configured for each area, the requirement of the corresponding area in the corresponding time can be met, and the accurate distribution and scheduling of the public transport resources are realized.
Therefore, the corresponding public transportation resources can be matched according to the actual demand condition of each region, the condition of people flow congestion can be prevented, the possible idle or redundant public transportation resources can be reasonably utilized, and the method has positive significance for reducing the idle ratio of the public transportation resources. Therefore, the allocation of the public transportation resources can be more sufficient and reasonable, the method has a good reference meaning for reasonably planning the total amount of the public transportation resources in the whole city, and the extreme condition that the public transportation resources are excessive or insufficient can be avoided.
In general, the traffic capacity configuration system applying the urban brain cloud platform can accurately guide the allocation and optimization of traffic resources according to the real-time change of urban traffic conditions, can effectively improve the utilization rate of traffic capacity, enables the traffic transportation efficiency to be higher, is beneficial to reducing the waste of traffic capacity and improves the overall traffic management smoothness of cities.
Further, in this embodiment, the number of people obtained by analyzing the video image of the public transportation station is the real-time traffic volume of the corresponding public transportation station. For example, the number of persons obtained by analyzing video images at a subway station is the actual number of persons being transported at the subway station at that time.
The pedestrian occupation ratio can be obtained through video image analysis of the intersection, and the pedestrian number in the corresponding area is the product of the real-time population number and the pedestrian occupation ratio.
The real-time population number of the corresponding area is obtained by multiplying the real-time GPS positioning heat proportion of the area by the total population number of the city, and the real-time GPS positioning heat proportion is the proportion of the real-time GPS positioning heat proportion of the area in the real-time GPS positioning heat synthesis of the city. The proportion of the pedestrians is the proportion of the number of the pedestrians passing through the corresponding intersection to the total number of the pedestrians passing through the intersection. The total number of people passing through the intersection is the sum of the number of pedestrians and the number of people in passing vehicles, and the number of people in the vehicles is the product of the number of passing vehicles and the average number of people in each vehicle.
The average number of people in each vehicle is represented by the average number of people in each vehicle in the urban taxi taking platform, and researches of the inventor find that the travel rule and the travel habit of people are mainly determined by public transport conditions, taxi taking convenience and the conditions of the number of people in taxi taking and self-driving, and the conditions of the number of people in taxi taking and self-driving have high similarity. The data may be obtained from statistics of the taxi-taking platform.
In the vehicles of the taxi taking platform, only active vehicles (namely, vehicles actually carrying out passenger carrying work) on the same day are counted, the number of empty vehicles is recorded as 1, non-empty vehicles are determined by the actual number of the vehicles (calculated by drivers), and the average number of people of each vehicle in the taxi taking platform is the total number of the active vehicles of the taxi taking platform divided by the total number of the active vehicles of the taxi taking platform.
The average value of the occupation ratios of the pedestrians at the road junctions in the area is used for representing the occupation ratio of the pedestrians in the area. Then, the number of pedestrians in the area is equal to the product of the total number of pedestrians in the area and the proportion of pedestrians in the area, the pedestrians are likely to take the public transportation, and the number of pedestrians in the area minus the real-time transportation amount of the public transportation station obtains the number of potential people who are likely to take the public transportation, namely the potential transportation amount of the public transportation, and the potential transportation pressure of the public transportation in the future is predicted.
Through the design, the transportation pressure possibly faced by the public transportation can be fully predicted, so that the reference function is played for the subsequent allocation of the public transportation resources.
Further, at 7-9 and 17-19 points per day on weekdays, the potential mass transit for office and residential areas is 1.2 times, i.e., the original value is multiplied by 1.2.
At 10-15 o' clock per day of the working day, the potential traffic volume in the commercial leisure area is 1 times, i.e. the original value is multiplied by 1 (i.e. the value is not changed).
At 15-20 o' clock per day on a working day, the potential traffic volume in commercial leisure areas is 1.2 times, i.e., the original value is multiplied by 1.2.
At 15-20 o' clock per day on non-working days, the potential traffic volume in commercial leisure areas is 1.5 times, i.e. the original value is multiplied by 1.2.
Through the design, according to the actual conditions of different periods, the condition of transportation pressure is corrected, and the phenomenon that people flow is detained in the transportation peak period can be avoided to the greatest extent, so that the overall transportation efficiency is improved.
It should be noted that, through the above manner, the situation that the transportation resource allocation is adopted after the stream of people is seriously detained can be effectively avoided, if the transportation resource allocation is carried out after the stream of people is seriously detained, the allocation difficulty is very large, and the bearing capacity of other areas to the large transportation pressure can be obviously weakened.
The traffic capacity configuration system applying the urban brain cloud platform predictively carries out advance planning and early warning, is favorable for allocating traffic transportation resources in advance, avoids temporary mess of feet, and greatly improves the traffic transportation management capability. On the other hand, the appropriate transportation resources can be allocated for the corresponding transportation demands, the surplus and the idle of the transportation resources are effectively avoided, and the utilization rate of the transportation resources is greatly improved. If the transportation resources are excessive, for example, the number of bus runs is too many, so that resource waste is avoided, extra traffic burden is brought to ground transportation by the extra buses, and traffic jam risk is increased.
Therefore, the traffic capacity configuration system applying the urban brain cloud platform improves the utilization rate of traffic transportation resources, enables the corresponding public transport means to transport passengers as many as possible within the safe transport capacity range, improves the capacity of the number of people passing a lane in unit time, equivalently improves the utilization rate of the traffic capacity, enables urban road resources to be more fully utilized, and effectively relieves traffic pressure.
Further, in this embodiment, the traffic capacity configuration system using the urban brain cloud platform further includes an alarm module. The alarm module is used for alarming when at least one of the real-time traffic volume and the potential traffic volume of the public transportation at the public transportation station exceeds the traffic capacity of the corresponding area. In addition, the alarm module is also used for prompting when at least one of the real-time traffic volume and the potential traffic volume of the public transportation at the public transportation station exceeds 90% of the traffic capacity of the corresponding area and lasts for 10-20 min.
It is to be appreciated that the alert module may prompt, without limitation, after at least one of real-time traffic volume and potential traffic volume at the mass transit site exceeds 90% of traffic capacity of the corresponding area for 10, 12, 15, 18, or 20 minutes. Can be flexibly selected according to actual operation requirements.
In conclusion, the traffic capacity configuration system applying the urban brain cloud platform can accurately guide the allocation and optimization of traffic resources according to the real-time change of urban traffic conditions, can effectively improve the utilization rate of traffic capacity, enables the traffic transportation efficiency to be higher, is beneficial to reducing the waste of traffic capacity and improves the overall traffic management smoothness of cities.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A traffic capacity configuration system applying a city brain cloud platform is characterized by comprising:
the analysis module is used for obtaining the real-time population distribution condition based on the real-time GPS positioning heat and the city population;
the correction module is used for confirming the potential traffic volume of the public transport by combining the video image analysis of the intersection and the public transport station according to the real-time population distribution condition;
the configuration module is used for adjusting the public transportation shift of the corresponding area according to the potential public transportation volume of each area so as to meet the requirement of the potential public transportation volume;
the number of people obtained by analyzing the video image of the camera of the public transportation station is the real-time traffic volume of the corresponding public transportation station; analyzing the video image of the camera at the intersection to obtain the occupation ratio of the pedestrians, wherein the number of the pedestrians in the corresponding area is the product of the real-time population number and the occupation ratio of the pedestrians; the potential traffic volume of the public transportation is the difference between the number of pedestrians in the corresponding area and the real-time traffic volume of the public transportation station.
2. The traffic capacity configuration system applying the urban brain cloud platform according to claim 1, wherein the proportion of pedestrians is the proportion of the number of pedestrians passing through a corresponding intersection to the total number of pedestrians passing through the intersection; wherein, the total number of people passing through the intersection is the sum of the number of pedestrians and the number of people in passing vehicles, the number of people in the vehicles is the product of the number of passing vehicles and the average number of people in each vehicle, and the average number of people in each vehicle is the average number of people in each vehicle in the urban taxi taking platform; in the vehicles of the taxi taking platform, the number of the empty vehicles is marked as 1, the number of the non-empty vehicles is determined by the actual number of the vehicles, and the average number of the vehicles in each taxi taking platform is the total number of the taxi taking platform divided by the total number of the vehicles of the taxi taking platform.
3. The traffic capacity configuration system applying the urban brain cloud platform according to claim 2, wherein the potential traffic volume of public transportation in the office area and the residential area is 1.2 times at 7-9 o 'clock and 17-19 o' clock per day of the working day.
4. The traffic capacity configuration system applying the urban brain cloud platform according to claim 2, wherein the potential traffic volume of public transportation in the business leisure area is 1 time at 10-15 points per day of the working day.
5. The traffic capacity configuration system applying the urban brain cloud platform according to claim 2, wherein the potential traffic volume of public transportation in the business leisure area is 1.2 times at 15-20 o' clock per day of the working day.
6. The traffic capacity configuration system applying the urban brain cloud platform according to claim 2, wherein the potential traffic volume of public transportation in the commercial leisure area is 1.5 times at 15-20 points per day on a non-working day.
7. The traffic capacity configuration system applying the city brain cloud platform according to claim 1, further comprising an alarm module; the alarm module is used for alarming when at least one of the real-time traffic volume and the potential traffic volume of the public transportation at the public transportation station exceeds the traffic capacity of the corresponding area.
8. The traffic capacity configuration system applying the urban brain cloud platform according to claim 7, wherein the alarm module is further configured to prompt after at least one of real-time traffic volume and potential traffic volume of public transportation at the public transportation site exceeds 90% of the traffic capacity of the corresponding area for 10-20 min.
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| US8645050B2 (en) * | 2010-09-09 | 2014-02-04 | Google Inc. | Transportation information systems and methods associated with degradation modes |
| CN109299438B (en) * | 2018-09-21 | 2023-01-17 | 东南大学 | Public transport facility supply level evaluation method based on network appointment data |
| CN109657843B (en) * | 2018-11-28 | 2023-04-18 | 深圳市综合交通设计研究院有限公司 | Integrated planning decision support system of urban plug-in bus system |
| CN109509351B (en) * | 2019-01-04 | 2020-07-28 | 江苏省城市规划设计研究院 | Method for calculating bus sharing rate in areas around bus stop |
| CN112309119B (en) * | 2020-11-03 | 2021-10-26 | 广州市交通规划研究院 | Urban traffic system capacity analysis optimization method |
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