CN106991818B - Method, storage medium and system for effectively relieving urban traffic congestion - Google Patents
Method, storage medium and system for effectively relieving urban traffic congestion Download PDFInfo
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- CN106991818B CN106991818B CN201710369685.0A CN201710369685A CN106991818B CN 106991818 B CN106991818 B CN 106991818B CN 201710369685 A CN201710369685 A CN 201710369685A CN 106991818 B CN106991818 B CN 106991818B
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- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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Abstract
The invention provides a method, a storage medium and a system for effectively relieving urban traffic jam. And fusing various real-time road condition data aiming at each detection point to obtain final accurate road condition data. Judging whether the detection point is a congestion source, if so, immediately calling video monitoring equipment at the position of the congestion source to shoot an image or a video, and immediately sending the image or the video to a mobile terminal of a duty police, which is associated with the detection point in advance, so that the duty police can immediately obtain a congestion cause image of the congestion source when congestion occurs, and if false alarm is given, the system does not give an alarm. Otherwise, according to the image content, the image content is determined to be provided by the system received by the mobile terminal, and whether other polices need to be mobilized to the scene or not is determined while the image content is being dredged to the scene of the congestion source, so that the congestion source is eliminated in a bud state.
Description
Technical Field
The invention relates to the field of public security traffic management, in particular to a method and a system for effectively relieving urban traffic jam.
Background
The urban road congestion brings great trouble to daily travel of people, much time is wasted on the road when people go to work and go out of work every day, time and economic losses are brought to individuals, economic development of a city is severely restricted, and policeman traffic management department decision makers and expert scholars also provide various ideas and research subjects for relieving traffic congestion, and the urban road congestion relieving method plays a certain role. However, the causes of traffic congestion are manifold, and the key to relieving road traffic congestion is: 1. the method comprises the steps of rapidly finding congestion, rapidly determining the location of a congestion source, 3 rapidly determining the cause of the congestion source, and 4 rapidly moving a police to a scene to eliminate the congestion source in a bud state. Therefore, road traffic jam is effectively alleviated, the found jam source and cause must be rapidly assigned to the police on duty, and the police is required to rapidly reach the position formed by the jam source, so that the jam source is eliminated in the bud.
Disclosure of Invention
Therefore, a method, a storage medium and a system for effectively relieving urban traffic congestion are provided, so that the position of a congestion source is quickly determined, the cause of the congestion source is quickly and automatically sent to a police on duty in the source district, the police judge whether to arrive at the scene immediately according to the cause displayed by a video image, if the result is false alarm, the system is replied to the scene, and if the result is congested, whether other policemen are mobilized to arrive at the scene together to eliminate the congestion source in a bud state is determined.
The invention provides a method for effectively relieving urban traffic jam, which comprises the following steps:
determining an area needing relieving urban traffic congestion on an electronic map, marking detection points between the exit and entrance positions of all intersections in the determined area and the intersections, setting the distance between every two adjacent detection points within a set threshold range, setting a specific number at each detection point, and associating the number of each detection point with the ID number of the video monitoring equipment corresponding to the position of the detection point;
a secondary police dispatching table is formulated, wherein congestion causes corresponding to each on-duty police, contact ways of each on-duty police and countermeasures plans corresponding to each congestion cause are recorded in the secondary police dispatching table; each secondary alarm adjusting table is provided with an alarm adjusting table number, and the alarm adjusting table number is associated with the corresponding detection point number;
acquiring real-time road condition information of each detection point, dividing real-time road condition data into four types of severe congestion, slowness and smoothness, and marking classification results on the corresponding detection points on the electronic map;
for each detection point, determining whether the detection point is a congestion source according to the road condition data of the detection point and the road condition data of the detection point adjacent to the downstream of the detection point;
carrying out parallel processing on a plurality of congestion source detection points which appear simultaneously, calling video monitoring equipment with corresponding ID numbers to acquire congestion cause images of the congestion sources according to the number of each congestion source detection point, and sending the congestion cause images to a specified mobile terminal of a duty police in a corresponding secondary police dispatching list;
after the mobile terminal receives the congestion cause image, the on-duty police judges whether the congestion cause image belongs to false alarm or not according to the congestion cause image, if the congestion cause image belongs to false alarm, the on-duty police directly feeds back the congestion cause image through the mobile terminal, and sends feedback information that the on-duty police cannot give out the alarm; if the mobile terminal does not belong to the false alarm, the on-duty police determines whether other on-duty police need to be mobilized to a congestion source according to the congestion cause displayed by the mobile terminal, and automatically displays a contact way when other on-duty police need to be mobilized;
and sending an alarm adjusting instruction to the corresponding on-duty police according to the contact way, and moving the corresponding on-duty police to the scene where the detection point at the congestion source is located for dredging.
Optionally, in the above method for effectively relieving urban traffic congestion, the real-time traffic information of each detection point is obtained, the real-time traffic data is divided into four types of severe congestion, slowness and smoothness, and the classification result is marked to the corresponding detection point on the electronic map, so that the real-time traffic information of the detection point is obtained in the following manner:
acquiring position and speed data of all mobile phones in the area in real time, associating the position and speed data of each mobile phone to corresponding geographic position coordinates in the electronic map, and acquiring first real-time road condition data of each detection point according to the average moving speed of all mobile phones in the detection range of the detection point;
reading at least three groups of road condition cloud data through the internet, determining real-time road condition data on a geographic position coordinate corresponding to each detection point according to the at least three groups of road condition cloud data, and obtaining second real-time road condition data of the detection points;
and fusing the first real-time road condition data and the second real-time road condition data to obtain road condition data of each detection point, dividing the real-time road condition data into four types of severe congestion, slowness and smoothness, and marking the classification result to the corresponding detection point on the electronic map.
Optionally, in the method for effectively relieving urban traffic congestion, the method includes acquiring position and speed data of all the mobile phones in the area sent by the mobile communication data center, associating the position and speed data of each mobile phone to a corresponding geographic position coordinate in the electronic map, and acquiring road condition data of the detection points as the first real-time road condition data according to the moving speeds of all the mobile phones in the coverage area of each detection point, and specifically includes:
configuring a detection range for each detection point, wherein the starting point of the detection range is the midpoint position of the detection point and the immediately upstream detection point, and the end point of the detection range is the midpoint position of the detection point and the immediately downstream detection point;
for each detection point, if the position and speed data of the mobile phone are not found in the detection range, the road condition data of the detection point is directly marked as smooth, otherwise, the moving speed V of each mobile phone in the detection range is obtainedaWherein a is more than or equal to 1 and less than or equal to A, A is the total number of the mobile phones in the detection range of the detection point, and the speed data of the detection point is calculated according to the following formula:
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is larger than or equal to a first threshold value, marking the road condition data of the detection point as smooth;
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is greater than or equal to a second threshold value and is smaller than a first threshold value, marking the road condition data of the detection point as slow;
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is greater than or equal to a third threshold value and is smaller than a second threshold value, marking the road condition data of the detection point as congestion;
and if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is smaller than a third threshold value, marking the road condition data of the detection point as serious congestion.
Optionally, in the method for effectively relieving urban traffic congestion, for each detection point, the step of determining whether the detection point is a congestion source according to the traffic data of the detection point and the traffic data of the detection point immediately downstream of the detection point specifically includes:
if the detected point is marked as severe congestion and the detected point close to the downstream is not severe congestion, determining the detected point as a congestion source;
if the detected point is marked as congestion and the detected point close to the downstream is not seriously congested or jammed, determining the detected point as a congestion source;
if a checkpoint is marked as slow and the checkpoint immediately downstream is not heavily congested or slow, then the checkpoint is determined to be the source of the congestion.
The present invention also provides a storage medium storing computer instructions for performing any one of the above methods for effectively alleviating urban traffic congestion when the computer instructions are executed by a computer.
The invention also provides a system for effectively relieving urban traffic jam, which comprises the following steps:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the one processor to cause the at least one processor to:
determining an area needing relieving urban traffic congestion on an electronic map, marking detection points between the exit and entrance positions of all intersections in the determined area and the intersections, setting the distance between every two adjacent detection points within a set threshold range, setting a specific number at each detection point, and associating the number of each detection point with the ID number of the video monitoring equipment corresponding to the position of the detection point;
a secondary police dispatching table is formulated, wherein congestion causes corresponding to each on-duty police, contact ways of each on-duty police and countermeasures plans corresponding to each congestion cause are recorded in the secondary police dispatching table; each secondary alarm adjusting table is provided with an alarm adjusting table number, and the alarm adjusting table number is associated with the corresponding detection point number;
acquiring real-time road condition information of each detection point, dividing real-time road condition data into four types of severe congestion, slowness and smoothness, and marking classification results on the corresponding detection points on the electronic map;
for each detection point, determining whether the detection point is a congestion source according to the road condition data of the detection point and the road condition data of the detection point adjacent to the downstream of the detection point;
when a plurality of congestion source detection points occur simultaneously, parallel processing can be carried out, according to the number of each congestion source detection point, video monitoring equipment with a corresponding ID number is called to collect congestion cause images of congestion sources, and the congestion cause images are simultaneously sent to a corresponding mobile terminal of an on-duty police in a corresponding secondary police dispatching list;
after the mobile terminal receives the congestion cause image, the on-duty police judges whether the congestion cause image belongs to false alarm or not according to the congestion cause image, if the congestion cause image belongs to false alarm, the on-duty police directly feeds back the congestion cause image through the mobile terminal, and sends feedback information that the on-duty police cannot give out the alarm; if the police on duty does not belong to the false alarm, the police on duty inputs the congestion cause through the mobile terminal, determines whether other police on duty need to be mobilized to the congestion source according to the congestion cause, and automatically displays the contact way when other police on duty need to be mobilized;
and sending an alarm adjusting instruction to the corresponding on-duty police according to the contact way, and moving the on-duty police to the site where the detection point at the congestion source is located for dredging.
Compared with the prior art, the technical scheme provided by the invention at least has the following beneficial effects:
the invention provides a method, a storage medium and a system for effectively relieving urban traffic jam, wherein detection points are marked on an electronic map of an area needing relieving urban traffic jam, the distance between two adjacent detection points is within a set threshold range, each detection point is provided with a specific number, the number of each detection point is associated with the ID number of a video monitoring device corresponding to the position of the detection point, and the ID number is also associated with at least one mobile terminal of a police on duty. And for each detection point, fusing various real-time road condition data to obtain the real-time road condition of the detection point. Judging whether the detection point is a congestion source, if so, immediately calling video monitoring equipment at the position of the congestion source to shoot an image or a video, and immediately sending the image or the video to a mobile terminal of a duty police, which is associated with the detection point in advance, so that the duty police can immediately obtain a congestion cause image of the congestion source when congestion occurs, and if false alarm is given, the system does not give an alarm. Otherwise, according to the image content, the image content is determined to be provided by the system received by the mobile terminal, and whether other polices need to be mobilized to the scene or not is determined while the image content is being dredged to the scene of the congestion source, so that the congestion source is eliminated in a bud state.
Drawings
In order that the present invention may be more readily and clearly understood, reference is now made to the following detailed description of the invention taken in conjunction with the accompanying drawings, in which,
FIG. 1 is a flow chart of a method for effectively alleviating urban traffic congestion according to one embodiment of the present invention;
FIG. 2 is a schematic diagram of an interface for marking detection points on a road within a partial city range according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a method for determining whether a checkpoint is a source of congestion according to an embodiment of the present invention;
fig. 4 is a schematic block diagram of a system for effectively alleviating urban traffic congestion according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present 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. And the technical features mentioned in the different embodiments of the invention described below can be combined with each other as long as they do not conflict with each other.
Example 1
The embodiment provides a method for effectively relieving urban traffic congestion, as shown in fig. 1, including the following steps:
s1: determining an area needing relieving urban traffic congestion on an electronic map, marking detection points between the exit and entrance positions of all intersections in the determined area and the intersections, setting the distance between every two adjacent detection points within a set threshold range, setting a specific number at each detection point, and associating the number of each detection point with the ID number of the video monitoring equipment corresponding to the position of the detection point; as shown in fig. 2, preferably, detecting points are marked at the entrance and exit positions of all intersections of an urban road and between adjacent intersections on an electronic map, and if the length of the expressway is greater than a preset distance, the detecting points are marked on the expressway; if the crossing distance of the common road is larger than the preset distance, marking detection points among the crossings, marking the detection points on the electronic map and numbering the detection points. In the electronic map labeling detection point, the actual distance between two adjacent detection points can be set between 50 meters and 150 meters. The arrows in the figure indicate the direction of travel, which for electronic maps records the coordinates of the geographic position itself, so that the geographic position coordinates of the detected points are known for certainty, as long as they are marked at the corresponding positions. The position of each detection point corresponds to a video monitoring device, and the detection point number corresponds to the ID number of the video monitoring device, so that when the traffic condition of the detection point needs to be monitored, the video monitoring device corresponding to the ID number can be directly called through the number of the detection point to carry out real-time shooting.
S2: a secondary police dispatching table is formulated, wherein congestion causes corresponding to each on-duty police, contact ways of each on-duty police and countermeasures plans corresponding to each congestion cause are recorded in the secondary police dispatching table; each secondary alarm adjusting table is provided with an alarm adjusting table number, and the alarm adjusting table number is associated with the corresponding detection point number; the number of the on-duty police can be distributed according to the actual condition of the area, generally, the number of the on-duty police corresponding to each detection point is more than one person, different on-duty police can correspond to different congestion causes, and specifically, the name of the on-duty police and the telephone number of the mobile terminal can be directly related to the detection point number. Various data can be stored in a related way by adopting a mode shown in the table 1:
table 1 data association table
As shown in table 1, as long as the number of the detection point is determined, the ID number of the video monitoring device and the contact way of the on-duty police can be determined immediately, and as long as the congestion cause is determined, the on-duty police specifically heading for the congestion source to dredge can be determined, and a pre-plan countermeasure can be given for the on-duty police to refer to.
S3: and acquiring real-time road condition information of each detection point, dividing the real-time road condition data into four types of severe congestion, slowness and smoothness, and marking classification results on the corresponding detection points on the electronic map. The real-time road condition data can be dark red, yellow and green, the dark red is used for representing serious congestion, the red is used for representing congestion, the yellow is used for representing slow congestion, the green is used for representing smooth traffic, the real-time road condition data can also comprise a geographical position coordinate and a road condition of the geographical position coordinate, and after the road condition data of a certain detection point is read, the real-time road condition data is directly associated with the geographical position coordinate on the electronic map.
S4: for each detection point, determining whether the detection point is a congestion source according to the road condition data of the detection point and the road condition data of the detection point adjacent to the downstream of the detection point;
s5: the method comprises the steps of carrying out parallel processing on a plurality of congestion source detection points which appear at the same time, calling video monitoring equipment with corresponding ID numbers to acquire congestion cause images of congestion sources according to the number of each congestion source detection point, and simultaneously sending the congestion cause images to a corresponding mobile terminal of an on-duty police in a corresponding secondary police dispatching list;
s6: after the mobile terminal receives the congestion cause image, the on-duty police judges whether the congestion cause image belongs to false alarm or not according to the congestion cause image, if the congestion cause image belongs to false alarm, the on-duty police directly feeds back the congestion cause image through the mobile terminal, and sends feedback information that the on-duty police cannot give out the alarm; if the police on duty does not belong to the false alarm, the police on duty inputs the congestion cause through the mobile terminal, automatically prompts according to the congestion cause to determine whether other police on duty need to be mobilized to the congestion source, and automatically displays the contact way when other police on duty need to be mobilized;
s7: and sending an alarm adjusting instruction to the corresponding on-duty police according to the contact way, and moving the on-duty police to the site where the detection point at the congestion source is located for dredging.
In the scheme, detection points are marked on an electronic map of an area needing relieving urban traffic congestion, the distance between two adjacent detection points is within a set threshold range, each detection point is provided with a specific number, the number of each detection point is associated with the ID number of the video monitoring equipment corresponding to the position of the detection point, and meanwhile, the number of each detection point is also associated with at least one mobile terminal of a duty police. And for each detection point, fusing various real-time road condition data to obtain the real-time road condition of the detection point. Judging whether the detection point is a congestion source, if so, immediately calling video monitoring equipment at the position of the congestion source to shoot an image or a video, and immediately sending the image or the video to a mobile terminal of a duty police, which is associated with the detection point in advance, so that the duty police can immediately obtain a congestion cause image of the congestion source when congestion occurs, and if false alarm is given, the system does not give an alarm. Otherwise, according to the image content, the image content is determined to be provided by the system received by the mobile terminal, and whether other polices need to be mobilized to the scene or not is determined while the image content is being dredged to the scene of the congestion source, so that the congestion source is eliminated in a bud state.
In the scheme, the core point of the method is that for a traffic control center, the correctness of the congestion source does not need to be judged by police-receiving personnel, and the congestion cause image of the congestion source can be sent to the mobile terminal of the police on duty on the road surface as long as the prompt information of the congestion source can be received. The on-duty police judges whether the current prompt information is true, if not, the on-duty police directly does not need to give out the police and sends the information to the traffic control center, if the true police needs to give out the police, the on-duty police judges the congestion cause and inputs the congestion cause to the mobile terminal, and the mobile terminal can directly and automatically pop up the on-duty police corresponding to the congestion cause according to the input congestion cause.
Example 2
In this embodiment, the real-time traffic information of each detection point is obtained, the real-time traffic data is divided into four types, namely, severe congestion, slowness and smoothness, and the classification result is marked on the corresponding detection point on the electronic map, so that the real-time traffic information of the detection point is obtained in the following manner:
s31: acquiring position and speed data of all mobile phones in the area in real time, associating the position and speed data of each mobile phone to corresponding geographic position coordinates in the electronic map, and acquiring first real-time road condition data of each detection point according to the average moving speed of all mobile phones in the detection range of the detection point; because the geographic position coordinate information is recorded on the electronic map, the position coordinate information of the mobile phone can be directly compared with the position coordinate information of the electronic map, and the position and speed information of the mobile phone is marked to the corresponding position of the electronic map. Therefore, the current position and the moving speed of the mobile phone can be obtained. Existing mobile phones each have a positioning function module and transmit their own Location information to a mobile communication data center in real time, such as an existing LBS (Location Based Service), which obtains Location information (Geographic coordinates or geodetic coordinates) of a mobile phone user through a radio communication network (e.g., GSM network, CDMA network) of a telecommunication mobile operator or an external positioning manner (e.g., GPS), and provides corresponding services to the user with support of a GIS (Geographic information System) platform. Therefore, the specific position and speed information of each mobile phone can be directly obtained from the mobile communication data center. In this embodiment, after the position and speed data of the mobile phone are obtained, the first real-time traffic data of the detection point is obtained through the following steps.
S311: configuring a detection range for each detection point, wherein the starting point of the detection range is the midpoint position of the detection point and the immediately upstream detection point, and the end point of the detection range is the midpoint position of the detection point and the immediately downstream detection point; if there is no other detection point upstream of a certain detection point, it is taken as a starting point, and similarly, if there is no other detection point downstream of a certain detection point, it is taken as an ending point.
S312: for each detection point, if the position and speed data of the mobile phone are not found in the detection range, the road condition data of the detection point is directly marked as smooth, otherwise, the moving speed V of each mobile phone in the detection range is obtainedaWherein a is more than or equal to 1 and less than or equal to A, A is the total number of the mobile phones in the detection range of the detection point, and the speed data of the detection point is calculated according to the following formula:
that is, if there is no mobile phone in the detection range of the detection point, it is directly determined that there is no vehicle in the detection range of the detection point, and the vehicle can run according to the highest speed limit, and the road condition data is smooth and is directly represented by green.
S313: if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is larger than or equal to a first threshold value, marking the road condition data of the detection point as smooth; if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is greater than or equal to a second threshold value and is smaller than a first threshold value, marking the road condition data of the detection point as slow; if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is greater than or equal to a third threshold value and is smaller than a second threshold value, marking the road condition data of the detection point as congestion; and if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is smaller than a third threshold value, marking the road condition data of the detection point as serious congestion. As described above, the first threshold, the second threshold, and the third threshold may be set according to the actual situation, for example, the first threshold is selected to be 0.6, the second threshold is selected to be 0.4, and the third threshold is selected to be 0.2.
S32: reading at least three groups of road condition cloud data through the internet, determining real-time road condition data on a geographic position coordinate corresponding to each detection point according to the at least three groups of road condition cloud data, and obtaining second real-time road condition data of the detection points; specifically, many government departments release road condition information data to the internet, the data can be acquired free of charge, and the step can be performed by directly reading corresponding road condition data from the internet, so that in actual application, the average road condition of multiple groups of data can be obtained, or the road condition data of the detection point can be acquired according to the principle of representing which road condition data has the largest number of groups and marking the road condition data of the detection point as which road condition.
S33: and fusing the first real-time road condition data and the second real-time road condition data to obtain road condition data of each detection point, dividing the real-time road condition data into four types of severe congestion, slowness and smoothness, and marking the classification result to the corresponding detection point on the electronic map.
The real-time road condition data of the detection points are obtained more accurately by means of fusion of various data, and the situation that the road condition data acquired by a single way is large in error can be avoided.
Example 3
In this embodiment, for each detection point, the step of determining whether the detection point is a congestion source according to the traffic data of the detection point and the traffic data of the immediately downstream detection point may be implemented by the method shown in fig. 3:
s41: judging whether the detection point of a certain number is dark red, if so, executing step S42, otherwise, executing step S43;
s42: judging whether the detection point immediately downstream of the detection point with the number is dark red or not, if not, executing the step S47, and if so, returning to the step S3;
s43: judging whether the number detection point is red, if so, executing step S44, otherwise, executing step S45;
s44: judging whether the detecting point immediately downstream of the detecting point with the number is dark red or red, if not, executing the step S47, and if so, returning to the step S3;
s45: judging whether the detecting point of the number is yellow, if so, executing the step S46, otherwise, returning to the step S3;
s46: judging whether the detection point immediately downstream of the detection point with the number is dark red or yellow, if not, executing the step S47, and if so, returning to the step S3;
s47: and determining the number detection point as a congestion source.
The deep red above indicates severe congestion, red indicates congestion, yellow indicates slowness, and green indicates unblocked. That is, if a certain detection point is deep red, but its immediately downstream detection point is not deep red, the detection point is a congestion source. If a certain detection point is red, but the detection point immediately downstream of the certain detection point is not deep red or red, the detection point is the congestion source. If a certain detection point is yellow, but the detection point at the downstream of the certain detection point is not deep red, nor yellow, the detection point is the congestion source. By adopting the judging mode, the detection point corresponding to the congestion source can be obtained very simply and quickly, the specific position of the congestion source can be determined according to the corresponding relation between the detection point and the geographic position coordinate, and the guarantee is provided for quickly eliminating the congestion source.
In the method for effectively alleviating urban traffic congestion in this embodiment, after step S4, the method further includes the following steps:
s41: for each congestion source detection point, calculating a blocking coefficient of the congestion source according to road condition data of the congestion source detection point and road condition data of a downstream adjacent detection point;
accordingly, in step S5, the blocking coefficient of the congestion source is associated with the number of the congestion source detection point and then transmitted to the mobile terminal of the on-duty police together. The calculation process of the blocking coefficient specifically comprises the steps that at the moment when each detection point becomes a congestion source, the initial value of the blocking coefficient is zero; in each preset period, updating the blocking coefficient of each congestion source according to the following steps:
s411: and judging whether the congestion source is dark red, if so, executing the step S412, and otherwise, executing the step S414.
S412: judging whether the immediately downstream detection point is green, if so, adding a first value to the obstruction coefficient of the congestion source at the current moment by a preset period value, wherein the preset period is in units of seconds, such as 1 second, 2 seconds and the like, otherwise, executing step S413, and the first value can be selected according to the actual situation, which is 1.5 in the embodiment.
S413: judging whether the downstream adjacent detection point is yellow, if so, adding a second numerical value to the blocking coefficient of the congestion source at the current moment by a preset period value; the second numerical value can be selected according to actual conditions, and is selected to be 1 in the embodiment; otherwise, the obstruction coefficient of the congestion source at the current time is added with a third value, which is selected according to the actual situation and is 0.5 in this embodiment, by a preset period value.
S414: and judging whether the congestion source is red, if so, executing the step S415, otherwise, executing the step S416.
S415: and judging whether the downstream adjacent detection point is green, if so, adding a second numerical value to the blocking coefficient of the congestion source at the current moment by a preset period value, and if not, executing the step S416.
S416: and adding a third numerical value to the blocking coefficient of the congestion source at the current moment by a preset period value.
S417: and clearing the blockage coefficient of the congestion source which is changed into green in the area every second.
And for the detection point serving as the congestion source, determining the blocking coefficient of the congestion source according to the difference between the road condition and the road condition of the detection point adjacent to the downstream direction of the detection point. If the difference between the road condition of the immediately downstream detection point and the road condition of the congestion source is larger, the congestion source has larger resistance to the downstream, and therefore the blocking coefficient should be larger. For example, when a certain congestion source is dark red, and the detected point immediately adjacent to the downstream direction is green, and the detected point immediately adjacent to the downstream direction is red, the blocking coefficient of the former is larger than that of the latter.
Example 4
The present embodiment provides a storage medium storing computer instructions for performing the method for effectively alleviating urban traffic congestion according to any one of embodiments 1 to 3 when the computer instructions are executed by a computer.
Example 5
The present embodiment provides a system for effectively alleviating urban traffic congestion, as shown in fig. 4, including:
at least one processor 1; and the number of the first and second groups,
a memory 2 communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory 2 stores instructions executable by the one processor 1 to enable the at least one processor 1 to:
determining an area needing relieving urban traffic congestion on an electronic map, marking detection points between the exit and entrance positions of all intersections in the determined area and the intersections, setting the distance between every two adjacent detection points within a set threshold range, setting a specific number at each detection point, and associating the number of each detection point with the ID number of the video monitoring equipment corresponding to the position of the detection point;
a secondary police dispatching table is formulated, wherein congestion causes corresponding to each on-duty police, contact ways of each on-duty police and countermeasures plans corresponding to each congestion cause are recorded in the secondary police dispatching table; each secondary alarm adjusting table is provided with an alarm adjusting table number, and the alarm adjusting table number is associated with the corresponding detection point number;
acquiring real-time road condition information of each detection point, dividing real-time road condition data into four types of severe congestion, slowness and smoothness, and marking classification results on the corresponding detection points on the electronic map;
for each detection point, determining whether the detection point is a congestion source according to the road condition data of the detection point and the road condition data of the detection point adjacent to the downstream of the detection point;
carrying out parallel processing on a plurality of congestion source detection points which appear simultaneously, calling video monitoring equipment with corresponding ID numbers to acquire congestion cause images of the congestion sources according to the number of each congestion source detection point, and sending the congestion cause images to any one on-duty police mobile terminal in a corresponding secondary police dispatching list;
after the mobile terminal receives the congestion cause image, the on-duty police judges whether the congestion cause image belongs to false alarm or not according to the congestion cause image, if the congestion cause image belongs to false alarm, the on-duty police directly feeds back the congestion cause image through the mobile terminal, and sends feedback information that the on-duty police cannot give out the alarm; if the police on duty does not belong to the false alarm, the police on duty inputs the congestion cause through the mobile terminal, the mobile terminal automatically prompts whether other police on duty need to be mobilized to the congestion source according to the congestion cause, and automatically displays the contact way when other police on duty need to be mobilized;
and sending an alarm adjusting instruction to the corresponding on-duty police according to the contact way, and moving the on-duty police to the site where the detection point at the congestion source is located for dredging.
In the above, the processors may be respectively disposed in the traffic control center and the mobile terminal of the on-duty police.
Example 6
The embodiment provides a system for effectively relieving urban traffic jam, which comprises a control device arranged in a traffic management control center and a mobile terminal worn or held by a police on duty. Wherein:
the control device is configured to:
determining an area needing relieving urban traffic congestion on an electronic map, marking detection points between the exit and entrance positions of all intersections in the determined area and the intersections, setting the distance between every two adjacent detection points within a set threshold range, setting a specific number at each detection point, and associating the number of each detection point with the ID number of the video monitoring equipment corresponding to the position of the detection point; a secondary police dispatching table is formulated, wherein congestion causes corresponding to each on-duty police, contact ways of each on-duty police and countermeasures plans corresponding to each congestion cause are recorded in the secondary police dispatching table; each secondary alarm adjusting table is provided with an alarm adjusting table number, and the alarm adjusting table number is associated with the corresponding detection point number; acquiring real-time road condition information of each detection point, dividing real-time road condition data into four types of severe congestion, slowness and smoothness, and marking classification results on the corresponding detection points on the electronic map; for each detection point, determining whether the detection point is a congestion source according to the road condition data of the detection point and the road condition data of the detection point adjacent to the downstream of the detection point; carrying out parallel processing on a plurality of congestion source detection points which appear simultaneously, calling video monitoring equipment with corresponding ID numbers to acquire congestion cause images of the congestion sources according to the number of each congestion source detection point, and sending the congestion cause images to any one on-duty police mobile terminal in a corresponding secondary police dispatching list;
the mobile terminal is configured to: after receiving the congestion cause image, the on-duty police judges whether the congestion cause image belongs to false alarm or not, if the congestion cause image belongs to false alarm, the on-duty police directly feeds back the congestion cause image through a mobile terminal, and sends feedback information that the on-duty police cannot give out the alarm; if the police on duty does not belong to the false alarm, the police on duty inputs the congestion cause through the mobile terminal, the mobile terminal automatically prompts whether other police on duty need to be mobilized to the congestion source according to the congestion cause, and automatically displays the contact way when other police on duty need to be mobilized;
and sending an alarm adjusting instruction to the corresponding on-duty police according to the contact way, and moving the on-duty police to the site where the detection point at the congestion source is located for dredging.
In the scheme, detection points are marked on an electronic map of an area needing relieving urban traffic congestion, the distance between two adjacent detection points is within a set threshold range, each detection point is provided with a specific number, the number of each detection point is associated with the ID number of the video monitoring equipment corresponding to the position of the detection point, and meanwhile, the number of each detection point is also associated with at least one mobile terminal of a duty police. And for each detection point, fusing various real-time road condition data to obtain the real-time road condition of the detection point. Judging whether the detection point is a congestion source, if so, immediately calling video monitoring equipment at the position of the congestion source to shoot an image or a video, and immediately sending the image or the video to a mobile terminal of a duty police, which is associated with the detection point in advance, so that the duty police can immediately obtain a congestion cause image of the congestion source when congestion occurs, and if false alarm is given, the system does not give an alarm. Otherwise, according to the image content, the image content is determined to be provided by the system received by the mobile terminal, and whether other polices need to be mobilized to the scene or not is determined while the image content is being dredged to the scene of the congestion source, so that the congestion source is eliminated in a bud state.
In the scheme, the core point of the system is that for a traffic control center, police receiving personnel do not need to be equipped, and the system directly sends the congestion cause image of the congestion source to a mobile terminal of an on-duty police as long as the system receives the prompt information of the congestion source. The on-duty police judges whether the current prompt information is true or not, if not, the on-duty police directly does not need to give out police and sends the information to the traffic control center, if the true police is determined to need giving out police, the on-duty police judges the congestion cause according to the video picture, the congestion cause is input to the mobile terminal, and the mobile terminal can directly pop up the on-duty police corresponding to the congestion cause according to the input congestion cause.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (4)
1. A method for effectively relieving urban traffic congestion is characterized by comprising the following steps:
determining an area needing relieving urban traffic congestion on an electronic map, marking detection points between the exit and entrance positions of all intersections in the determined area and the intersections, setting the distance between every two adjacent detection points within a set threshold range, setting a specific number at each detection point, and associating the number of each detection point with the ID number of the video monitoring equipment corresponding to the position of the detection point;
a secondary police dispatching table is formulated, wherein congestion causes corresponding to each on-duty police, contact ways of each on-duty police and countermeasures plans corresponding to each congestion cause are recorded in the secondary police dispatching table; each secondary alarm adjusting table is provided with an alarm adjusting table number, and the alarm adjusting table number is associated with the corresponding detection point number;
acquiring real-time road condition data of each detection point, dividing the real-time road condition data into four types of severe congestion, slowness and smoothness, and marking classification results on the corresponding detection points on the electronic map;
for each detection point, determining whether the detection point is a congestion source according to the road condition data of the detection point and the road condition data of the detection point adjacent to the downstream of the detection point;
carrying out parallel processing on a plurality of congestion source detection points which appear simultaneously, calling video monitoring equipment with corresponding ID numbers to acquire congestion cause images of the congestion sources according to the number of each congestion source detection point, and sending the congestion cause images to a specified mobile terminal of a duty police in a corresponding secondary police dispatching list;
after the mobile terminal receives the congestion cause image, the on-duty police judges whether the congestion cause image belongs to false alarm or not according to the congestion cause image, if the congestion cause image belongs to false alarm, the on-duty police directly feeds back the congestion cause image through the mobile terminal, and sends feedback information that the on-duty police cannot give out the alarm; if the mobile terminal does not belong to the false alarm, the on-duty police determines whether other on-duty police need to be mobilized to a congestion source according to the congestion cause displayed by the mobile terminal, and automatically displays a contact way when other on-duty police need to be mobilized;
sending an alarm adjusting instruction to the corresponding on-duty police according to the contact way, and moving the corresponding on-duty police to the scene where the detection point at the congestion source is located for dredging;
the method comprises the steps of obtaining real-time road condition data of each detection point, dividing the real-time road condition data into four types of severe congestion, slowness and smoothness, marking classification results on the corresponding detection points on an electronic map, and obtaining the real-time road condition data of the detection points in the following modes:
acquiring position and speed data of all mobile phones in the area in real time, associating the position and speed data of each mobile phone to corresponding geographic position coordinates in the electronic map, and acquiring first real-time road condition data of each detection point according to the average moving speed of all mobile phones in the detection range of the detection point; the method specifically comprises the following steps:
configuring a detection range for each detection point, wherein the starting point of the detection range is the midpoint position of the detection point and the immediately upstream detection point, and the end point of the detection range is the midpoint position of the detection point and the immediately downstream detection point;
for each detection point, if the position and speed data of the mobile phone are not found in the detection range, the road condition data of the detection point is directly marked as smooth, otherwise, the moving speed V of each mobile phone in the detection range is obtainedaWherein a is more than or equal to 1 and less than or equal to A, A is the total number of the mobile phones in the detection range of the detection point, and the speed data of the detection point is calculated according to the following formula:
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is larger than or equal to a first threshold value, marking the road condition data of the detection point as smooth;
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is greater than or equal to a second threshold value and is smaller than a first threshold value, marking the road condition data of the detection point as slow;
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is greater than or equal to a third threshold value and is smaller than a second threshold value, marking the road condition data of the detection point as congestion;
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is smaller than a third threshold value, marking the road condition data of the detection point as serious congestion;
reading at least three groups of road condition cloud data through the internet, determining real-time road condition data on a geographic position coordinate corresponding to each detection point according to the at least three groups of road condition cloud data, and obtaining second real-time road condition data of the detection points;
and fusing the first real-time road condition data and the second real-time road condition data to obtain road condition data of each detection point, dividing the real-time road condition data into four types of severe congestion, slowness and smoothness, and marking the classification result to the corresponding detection point on the electronic map.
2. The method as claimed in claim 1, wherein the step of determining, for each detection point, whether the detection point is a congestion source according to the traffic data of the detection point and the traffic data of the detection point immediately downstream from the detection point specifically comprises:
if the detected point is marked as severe congestion and the detected point close to the downstream is not severe congestion, determining the detected point as a congestion source;
if the detected point is marked as congestion and the detected point close to the downstream is not seriously congested or jammed, determining the detected point as a congestion source;
if a checkpoint is marked as slow and the checkpoint immediately downstream is not heavily congested or slow, then the checkpoint is determined to be the source of the congestion.
3. A storage medium storing computer instructions for performing the method of claim 1 or 2 when executed by a computer for effectively alleviating urban traffic congestion.
4. A system for effectively alleviating urban traffic congestion, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
determining an area needing relieving urban traffic congestion on an electronic map, marking detection points between the exit and entrance positions of all intersections in the determined area and the intersections, setting the distance between every two adjacent detection points within a set threshold range, setting a specific number at each detection point, and associating the number of each detection point with the ID number of the video monitoring equipment corresponding to the position of the detection point;
a secondary police dispatching table is formulated, wherein congestion causes corresponding to each on-duty police, contact ways of each on-duty police and countermeasures plans corresponding to each congestion cause are recorded in the secondary police dispatching table; each secondary alarm adjusting table is provided with an alarm adjusting table number, and the alarm adjusting table number is associated with the corresponding detection point number;
acquiring real-time road condition data of each detection point, dividing the real-time road condition data into four types of severe congestion, slowness and smoothness, and marking classification results on the corresponding detection points on the electronic map; obtaining real-time road condition data of the detection points by the following method:
acquiring position and speed data of all mobile phones in the area in real time, associating the position and speed data of each mobile phone to corresponding geographic position coordinates in the electronic map, and acquiring first real-time road condition data of each detection point according to the average moving speed of all mobile phones in the detection range of the detection point; the method specifically comprises the following steps:
configuring a detection range for each detection point, wherein the starting point of the detection range is the midpoint position of the detection point and the immediately upstream detection point, and the end point of the detection range is the midpoint position of the detection point and the immediately downstream detection point;
for each detection point, if the position and speed data of the mobile phone are not found in the detection range, the road condition data of the detection point is directly marked as smooth, otherwise, the moving speed V of each mobile phone in the detection range is obtainedaWherein a is more than or equal to 1 and less than or equal to A, A is the total number of the mobile phones in the detection range of the detection point, and the total number is calculated according to the following formulaSpeed data of the detection point:
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is larger than or equal to a first threshold value, marking the road condition data of the detection point as smooth;
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is greater than or equal to a second threshold value and is smaller than a first threshold value, marking the road condition data of the detection point as slow;
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is greater than or equal to a third threshold value and is smaller than a second threshold value, marking the road condition data of the detection point as congestion;
if the ratio of the speed data of the detection point to the highest speed limit value of the road section where the detection point is located is smaller than a third threshold value, marking the road condition data of the detection point as serious congestion;
reading at least three groups of road condition cloud data through the internet, determining real-time road condition data on a geographic position coordinate corresponding to each detection point according to the at least three groups of road condition cloud data, and obtaining second real-time road condition data of the detection points;
the first real-time road condition data and the second real-time road condition data are fused to obtain road condition data of each detection point, the real-time road condition data are divided into four types of serious congestion, slowness and smoothness, and classification results are marked to the corresponding detection points on the electronic map;
for each detection point, determining whether the detection point is a congestion source according to the road condition data of the detection point and the road condition data of the detection point adjacent to the downstream of the detection point;
when a plurality of congestion source detection points appear at the same time, parallel processing can be carried out, according to the number of each congestion source detection point, the video monitoring equipment with the corresponding ID number is called to acquire a congestion cause image of the congestion source, and the congestion cause image is simultaneously sent to a corresponding mobile terminal of an on-duty police in a corresponding secondary police dispatching list;
after the mobile terminal receives the congestion cause image, the on-duty police judges whether the congestion cause image belongs to false alarm or not according to the congestion cause image, if the congestion cause image belongs to false alarm, the on-duty police directly feeds back the congestion cause image through the mobile terminal, and sends feedback information that the on-duty police cannot give out the alarm; if the police on duty does not belong to the false alarm, the police on duty inputs the congestion cause through the mobile terminal, determines whether other police on duty need to be mobilized to the congestion source according to the congestion cause, and automatically displays the contact way when other police on duty need to be mobilized;
and sending an alarm adjusting instruction to the corresponding on-duty police according to the contact way, and moving the on-duty police to the site where the detection point at the congestion source is located for dredging.
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| CN110580807A (en) * | 2019-09-06 | 2019-12-17 | 杭州思源信息技术股份有限公司 | Intelligent traffic management system capable of relieving traffic jam |
| CN110853345A (en) * | 2019-09-25 | 2020-02-28 | 陈广柱 | Crossing intensive information acquisition system for traffic police command |
| CN111028507B (en) * | 2019-12-16 | 2022-05-13 | 阿波罗智联(北京)科技有限公司 | Traffic jam cause determining method and device |
| CN111681432B (en) * | 2020-04-30 | 2022-03-29 | 大连理工大学 | Method and device for determining congestion source of intersection containing signal lamp |
| CN111798660B (en) * | 2020-06-30 | 2021-12-07 | 腾讯科技（深圳）有限公司 | Vehicle information display and acquisition method and device and related equipment |
| CN113538915B (en) * | 2021-07-21 | 2023-02-28 | 阿波罗智联(北京)科技有限公司 | Method, device, storage medium and program product for processing traffic jam event |
| CN113671986B (en) * | 2021-07-28 | 2022-10-18 | 合肥工业大学 | Task allocation method and system for unmanned aerial vehicle and vehicle under cooperation of air and ground |
| CN114202918A (en) * | 2021-12-06 | 2022-03-18 | 软通智慧信息技术有限公司 | Traffic distribution method and device for coping with traffic jam, electronic equipment and medium |
| CN117151427B (en) * | 2023-10-27 | 2024-01-30 | 湖南思达软件技术有限公司 | Traffic police service collaborative management method and system based on big data |
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