CN115578233B - Traffic emergency evacuation method, system and computer equipment - Google Patents
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Abstract
The invention provides a traffic emergency evacuation method, a system and computer equipment, and relates to the field of traffic planning, wherein the method comprises the following steps: acquiring real-time people stream monitoring data, regional data and activity data; judging an early warning state according to the real-time people stream monitoring data, the regional data and the activity data; issuing early warning information according to the early warning state; according to the early warning state, carrying out people stream slow evacuation; and carrying out public transportation emergency dispatching according to the early warning state. Compared with the prior art, the method improves the order, the high efficiency and the safety of large-scale active emergency evacuation, and reduces the possibility of emergency occurrence and the harm caused by the emergency.
Description
Technical Field
The invention relates to the field of traffic planning, in particular to a traffic emergency evacuation method, a system and computer equipment.
Background
With the development of society, the holding of large-scale activities is increased, and the emergency situation of the large-scale activities can cause the phenomena of short-time traffic evacuation demand increase, unbalanced traffic evacuation direction and the like around the activity site, and the evacuation process has the problems of strong harm and diffraction, especially the congestion and congestion generation during the evacuation process, so the order, the safety and the high efficiency of the traffic emergency evacuation of the large-scale activities are to be improved.
Disclosure of Invention
The invention solves the problem of traffic congestion caused by large-scale activities, thereby improving the order, the high efficiency and the safety of people in the evacuation process and reducing the possibility of emergencies and the harm caused by the emergencies.
In order to solve the problems, the invention provides a traffic emergency evacuation method, which comprises the following steps:
acquiring real-time people stream monitoring data, regional data and activity data;
judging an early warning state according to the real-time people stream monitoring data, the regional data and the activity data;
issuing early warning information according to the early warning state;
according to the early warning state, carrying out people stream slow evacuation;
and carrying out public transportation emergency dispatching according to the early warning state.
Optionally, the real-time people stream monitoring data includes real-time people, the area data includes area and accommodation people, the activity data includes activity type and activity end time, and the early warning state is judged according to the real-time people stream monitoring data, the area data and the activity data, specifically including:
obtaining a people stream saturation index according to the real-time number of people and the accommodating number of people;
obtaining a unit area number index according to the real-time number of people and the area of the area;
and judging the early warning state according to the people stream saturation index, the unit area number index, the activity type and the activity ending time.
Optionally, the real-time people stream monitoring data further includes congestion road section information and congestion site information, and the issuing of the early warning information according to the early warning state specifically includes:
and according to the early warning state, releasing the congestion road section information and/or the congestion site information.
Optionally, the area data further includes key area data and traffic cell data, and the step of performing people stream slow evacuation according to the early warning state specifically includes:
acquiring historical trip chain data;
obtaining historical traffic space-time variation according to the historical travel chain data;
obtaining the people stream slow evacuation route according to the historical people stream space-time change, the activity ending time and the real-time people stream monitoring data;
the historical trip chain data are obtained through the historical key area data and the historical traffic cell data.
Optionally, obtaining the historical traffic space-time variation according to the historical travel chain data specifically includes:
according to the historical trip chain data, obtaining the people's flow trip space-time distribution and traffic mode proportion in specific activities and specific time;
according to the people stream travel space-time distribution, obtaining a historical people stream travel distribution proportion;
and obtaining the time-space change of the historical people flow according to the historical people flow travel distribution proportion and the traffic mode proportion.
Optionally, the obtaining the people stream slow evacuation route according to the historical people stream space-time variation, the activity ending time and the real-time people stream monitoring data specifically includes:
obtaining a separated evacuation flow of people according to the real-time flow monitoring data, the historical flow of people time-space change and the activity ending time;
and obtaining the people flow slow evacuation route according to the separated evacuation people flow and the real-time people flow monitoring data.
Optionally, the public transportation emergency dispatch is performed according to the early warning state, which specifically includes:
acquiring historical public transportation data and travel requirements of current public transportation;
and carrying out public transportation emergency dispatching according to the historical public transportation data and the travel demand of the current public transportation.
Compared with the prior art, the traffic emergency evacuation method has the advantages that: the invention provides a traffic emergency evacuation method, which is characterized in that the traffic emergency evacuation method is used for acquiring real-time people stream monitoring data, area data and activity data, judging an early warning state, issuing early warning information according to the early warning state, carrying out people stream slow evacuation and/or public traffic emergency dispatch, solving the traffic congestion phenomenon during large-scale activities, improving the order, safety and high efficiency of large-scale activity evacuation and reducing the possibility of occurrence of emergencies and harm caused by the emergencies.
In order to solve the technical problem, the invention also provides a traffic emergency evacuation system, which comprises:
the acquisition unit is used for acquiring real-time people stream monitoring data, regional data and activity data;
the early warning unit is used for judging an early warning state according to the real-time people stream monitoring data, the regional data and the activity data;
the processing unit is used for issuing early warning information according to the early warning state;
the processing unit is also used for carrying out people flow slow evacuation according to the early warning state;
and the processing unit is also used for carrying out public transportation emergency dispatch according to the early warning state.
Optionally, the processing unit includes a trip distribution module, a trip mode module, an evacuation module, an optimization module and a release module, and specifically includes:
the travel distribution module is used for obtaining the travel distribution proportion of the historical people flow according to the historical travel chain information;
the travel mode module is used for obtaining traffic mode proportion according to the history travel chain information;
the evacuation module is used for obtaining the separated evacuation flow according to the time-space change of the historical flow, the activity ending time and the real-time flow monitoring data;
the optimizing module is used for obtaining a slow traffic evacuation route according to the divided evacuation traffic and the real-time traffic monitoring data;
the optimizing module is also used for carrying out public transportation emergency dispatching according to the historical public transportation data and the travel demand of the current public transportation;
and the issuing module is used for issuing the early warning information according to the early warning state.
The traffic emergency evacuation system and the traffic emergency evacuation method have the same advantages as compared with the prior art, and are not described in detail herein.
In order to solve the technical problem, the invention also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of the traffic emergency evacuation method when executing the computer program.
The advantages of the computer device and the traffic emergency evacuation method of the present invention are the same as those of the prior art, and are not described in detail herein.
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FIG. 1 is an application environment diagram of a traffic emergency evacuation method in an embodiment of the present invention;
FIG. 2 is a flow chart of a traffic emergency evacuation method according to an embodiment of the present invention;
FIG. 3 is a block diagram of a traffic emergency evacuation system in accordance with an embodiment of the present invention;
fig. 4 is an internal structural diagram of a computer device in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and thoroughly described below with reference to the accompanying drawings.
In the description of embodiments of the present application, the term "description of some embodiments" means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same implementations or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Fig. 1 is an application environment diagram of a traffic emergency evacuation method in an embodiment of the present application. Referring to fig. 1, the traffic emergency evacuation method is applied to a traffic emergency evacuation system. The traffic emergency evacuation system includes a terminal 110 and a server 120. The terminal 110 and the server 120 are connected through a network. The terminal 110 may be a desktop terminal or a mobile terminal, and the mobile terminal may be at least one of a mobile phone, a tablet computer, a notebook computer, and the like. The server 120 may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.
In one embodiment, a traffic emergency evacuation method is provided. The present embodiment is mainly exemplified by the application of the method to the terminal 110 (or the server 120) in fig. 1. Referring to fig. 2, the traffic emergency evacuation method specifically includes the steps of:
step S1, acquiring real-time people stream monitoring data, regional data and activity data;
step S2, judging an early warning state according to the real-time people stream monitoring data, the regional data and the activity data;
and step S3, according to the early warning state, issuing early warning information and/or carrying out people flow slow evacuation and/or carrying out public transportation emergency dispatch.
In some embodiments, the early warning status is divided into three types; when the intelligent lamp post evacuation information release and voice broadcasting functions are triggered in the first-level early warning state, regional personnel are reminded of evacuation safety and orderly evacuation; when the intelligent lamp post evacuation information is in a secondary early warning state, the intelligent lamp post evacuation information is issued, the slow traffic flow of the whole road section is monitored and early warned, the slow moving line is optimized, and the emergency evacuation passenger flow of the relevant station is sent to a public transportation and subway group; when the system is in a three-level early warning state, early warning information is issued to carry out people flow slow evacuation, and meanwhile, the system is dynamically reported to a main department to realize dynamic scheduling of bus and subway operation and emergency warning of key slow road sections.
The embodiment provides a traffic emergency evacuation method, which judges the early warning state through real-time people stream monitoring data, regional data and activity data, and carries out corresponding warning evacuation modes on the on-site personnel of the activity according to different early warning states, thereby improving the order, the high efficiency and the safety of large-scale activity emergency evacuation and reducing the possibility of occurrence of emergencies and the harm caused by the emergencies.
In some embodiments, in step S1, the real-time people stream monitoring data includes a real-time number of people, the area data includes an area and a containing number of people, the activity data includes an activity type and an activity end time, and the early warning state is judged according to the real-time people stream monitoring data, the area data and the activity data, and specifically includes:
step S11, obtaining a people stream saturation index according to the real-time number of people and the accommodating number of people;
step S12, obtaining a unit area number index according to the real-time number of people and the area of the area;
and step S13, judging the early warning state according to the people stream saturation index, the unit area people number index, the activity type and the activity ending time.
In some preferred embodiments, the people stream saturation indicator is the quotient of the real-time number of people and the number of people accommodated, and the unit area number indicator is the quotient of the real-time number of people and the area of the area; different people flow saturation indexes, different people number indexes in unit area, different activity types and different activity ending time correspond to early warning states of different grades, for example, when the activity type is a exhibition activity, the people flow saturation is more than 50%, the people number in unit area is less than 5, and the early warning state is a primary early warning state when the activity ending time is 10 days after the non-working day; when the activity type is light show activity, the people flow saturation is more than 80%, the number of people per unit area is less than 10, and the early warning state is a secondary early warning state when the working day of the activity ending time is the early peak of working hours; when the activity type is concert activities, the people flow saturation is more than 100%, the number of people in a unit area is more than 10, and the early warning state is a three-level early warning state when the working day of the activity ending time is the early peak of working hours;
wherein, the number of people in real time can be obtained through the position big data; the number of the accommodations, the type of the activities and the time of the end of the activities can be obtained by the activities sponsor; the regional area is obtained through a big data computing platform TransPaaS for urban traffic control, the TransPaaS platform provides a full life cycle management function of traffic industry data, a multi-field traffic algorithm model is integrated, an urban traffic brain center is formed, and energy is applied to the whole industry. The data of the number of people in real time, the area of the area and the like can be obtained by other modes, methods or corresponding platforms, databases and the like, and are not described herein.
In some embodiments, in step S3, the real-time traffic monitoring data further includes congestion road section information and congestion site information, and the issuing of the early warning information according to the early warning state specifically includes:
and step S31, according to the early warning state, releasing the congestion road section information and/or the congestion site information.
In some preferred embodiments, the information of the crowded road section and the information of the crowded site are obtained through video AI identification, and when the early warning state is the primary early warning state, the intelligent lamp post evacuation information release and voice broadcasting functions are triggered to remind regional personnel of evacuating safety and orderly evacuation;
wherein, the screen AI recognition is based on advanced artificial intelligence technology to comprehensively detect real-time demand information.
In some embodiments, in step S3, the area data further includes key area data and traffic cell data, and performing people stream slow evacuation according to the early warning state specifically includes:
step S32, acquiring historical trip chain data;
step S33, according to the historical trip chain data, obtaining historical people flow space-time variation;
step S34, obtaining the people flow slow evacuation route according to the historical people flow space-time variation, the activity ending time and the real-time people flow monitoring data;
the historical trip chain data are obtained through the historical key area data and the historical traffic cell data.
In some embodiments, in step S33, the obtaining the historical traffic space-time variation according to the historical travel chain data specifically includes:
step S331, according to the historical trip chain data, obtaining the people' S trip space-time distribution and traffic mode proportion in specific activities and specific time;
step S332, obtaining a historical people-stream travel distribution ratio according to the people-stream travel space-time distribution;
step S333, obtaining the time-space variation of the historical people flow according to the historical people flow travel distribution proportion and the traffic mode proportion;
in some preferred embodiments, according to the historical trip chain data, calculating the time-space distribution of the starting and ending points of the personnel trip in a specific activity and a specific time period from the key area to the traffic cell, namely the OD (origin-destination) distribution, so as to obtain the historical distribution proportion from the key area to the traffic cell; meanwhile, under the condition of lack of current travel chain data, traffic distribution calculation can be carried out on key areas by means of a macroscopic traffic model related method to obtain OD distribution, and then time distribution is carried out on the OD distribution to obtain approximate OD distribution in an activity time period as a reference;
the historical trip chain data comprise individual trip data such as mobile phone signaling, buses, subways, taxis and the like, and are obtained through a TransPaaS platform; the OD profile is the start point and end point profile; the macroscopic traffic model related method is mainly based on traffic flow distribution of road section road resistance delay functions; the traffic cell is a space minimum unit defined for researching and analyzing residents and traveling and distribution of vehicles; the key area is an area which needs to be focused according to the actual traffic situation, and is variable.
In some embodiments, according to historical travel chain data (such as individual travel data of buses, subways, taxis and the like), calculating travel distribution from key areas to traffic areas and travel distribution among the traffic areas, and calculating traffic mode (such as buses, subways and taxis) proportion of the traffic areas as a reference; meanwhile, under the condition of lack of current travel chain data, the traffic mode proportion can be calculated by means of a macroscopic traffic model related method, so that the purpose of identifying traffic modes used by evacuees to a destination with high precision is achieved;
wherein, the traffic mode comprises slow running, such as riding and electric vehicles; private car driving, shared car, for example: a taxi; public transportation, for example: conventional public transportation and rail transportation.
In some embodiments, step S34 obtains the people-stream slow evacuation route according to the historical people-stream space-time variation, the activity ending time and the real-time people-stream monitoring data, and specifically includes:
step S341, obtaining a separated evacuation flow according to the real-time flow monitoring data, the historical flow space-time variation and the activity ending time;
step S342, obtaining the people flow slow evacuation route according to the separated evacuation people flow and the real-time people flow monitoring data.
In some embodiments, according to real-time people flow number monitoring of an area and combining with activity ending time, dividing the number of people at the end of an activity according to a historical people flow trip distribution proportion and a traffic mode proportion, and calculating the people flow in a cell division mode during people evacuation, namely, predicting the space-time distribution of emergency evacuation people in a slow-going network, a bus station, a subway station and a taxi waiting area.
In some preferred embodiments, the intelligent lamp post can also be called to identify the personnel flow, namely the personnel flow on the slow-going network, and the monitoring data can be checked with the calculated data to check the accuracy of the calculation result; and meanwhile, calling the traffic of the bus stop identification personnel, namely the traffic of the bus stop, checking the monitoring data of the bus stop and the calculated data, and checking the accuracy of the calculation result.
In some embodiments, according to the flow rate of people to be evacuated in a split manner and the spatial distribution of people flow evacuation gathering points in each traffic manner, slow evacuation paths are planned, and diversion is guided by means of intelligent lamp poles, indication guideboards and the like so as to avoid too concentrated passing through a certain road section; in addition, according to the space positions of subways and bus stops, the areas of taxi boarding and alighting, parking lots and the like are reasonably divided again; meanwhile, by setting scenes of various different passenger flow scales, analyzing the space rule and mode of people flow evacuation under various situations by using a traffic simulation technology, and formulating a corresponding management scheme;
the scenes of different passenger flow scales generally comprise legal holiday scenic spot scenes, large-scale activity scenes, severe weather scenes and emergency scenes, such as concert evacuation, exhibition evacuation, severe weather subway evacuation and the like.
In some embodiments, in step S3, public transportation emergency dispatch is performed according to the early warning state, which specifically includes:
step S35, acquiring historical public transportation data and travel requirements of current public transportation;
and step S36, carrying out public transportation emergency dispatching according to the historical public transportation data and the travel demand of the current public transportation.
In some preferred embodiments, the historical public transportation data comprises historical public transportation passenger flow assessment, historical public transportation travel domains and public transportation travel time, and according to travel demands in the current evacuation process, the travel demands of people stream evacuation on public transportation are distributed to specific bus stops and routes, and reasonable distribution of bus transportation capacity resources is achieved by combining bus network space distribution.
The embodiment provides a traffic emergency evacuation method, which generally judges the early warning state through real-time people stream monitoring data, regional data and activity data, and carries out corresponding warning evacuation modes on-site personnel according to different early warning states.
As shown in fig. 3, in one embodiment, there is provided a traffic emergency evacuation system comprising:
an acquiring unit 310, where the acquiring unit 310 is configured to acquire real-time people stream monitoring data, regional data, and activity data;
the early warning unit 320 is configured to determine an early warning state according to the real-time people stream monitoring data, the area data and the activity data;
the processing unit 330 is configured to issue early warning information according to the early warning state by the processing unit 330;
the processing unit 330 is further configured to perform slow traffic evacuation according to the early warning status;
the processing unit 330 is further configured to perform public transportation emergency dispatch according to the early warning state.
The judging unit 320 in this embodiment is further configured to obtain a people stream saturation index according to the real-time number of people and the accommodating number of people; obtaining a unit area number index according to the real-time number of people and the area of the area; and judging the early warning state according to the people stream saturation index, the unit area people number index, the activity type and the activity ending time.
The processing unit 330 in this embodiment is further configured to issue the congestion section information and/or the congestion site information according to the early warning status.
The processing unit 330 in this embodiment is further configured to obtain historical trip chain data; obtaining historical traffic space-time variation according to the historical travel chain data; and obtaining the people stream slow evacuation route according to the historical people stream space-time change, the activity ending time and the real-time people stream monitoring data.
The processing unit 330 in this embodiment is further configured to obtain historical public transportation data and travel requirements of current public transportation; and carrying out public transportation emergency dispatching according to the historical public transportation data and the travel demand of the current public transportation.
In some preferred embodiments, the processing unit comprises a trip distribution module, a trip mode module, an evacuation module, an optimization module, and a publication module, wherein,
the trip distribution module is used for obtaining the time-space distribution and traffic mode proportion of the people's trips in specific activities and specific time according to the historical trip chain information (individual trip data such as mobile phone signaling, buses, subways and taxis), then calculating to obtain the historical people's trips distribution proportion, and meanwhile, under the condition that the current trip chain data is lack, calculating the traffic distribution of key areas by means of a macroscopic traffic model correlation method to obtain the OD distribution, and then distributing the time of the OD distribution to obtain the approximate OD distribution in the activity time period;
the travel mode module is used for calculating travel distribution from key areas to traffic areas and travel distribution among the traffic areas according to the historical travel chain information (such as individual travel data of buses, subways, taxis and the like), and calculating traffic mode (such as buses, subways and taxis) proportion of the traffic areas;
the evacuation module is used for calculating the people flow in a cell division mode during people evacuation according to the real-time people flow number monitoring of the area and the result of dividing the number of people at the end of the activity according to the historic people flow trip distribution proportion and the traffic mode proportion by combining the activity end time, namely, the space-time distribution prediction of emergency evacuation people in the slow-going network, the bus station, the subway station and the taxi waiting area;
the optimizing module is used for planning a slow evacuation path according to the separated evacuation flow and the spatial distribution of the people flow evacuation gathering points of each traffic mode, guiding and diverting through the modes of intelligent lamp poles, indication guideboards and the like, and avoiding too intensively passing through a certain road section; in addition, according to the space positions of subways and bus stops, the areas of taxi boarding and alighting, parking lots and the like are reasonably divided again; meanwhile, by setting scenes of various different passenger flow scales, analyzing the space rule and mode of people flow evacuation under various situations by using a traffic simulation technology, and formulating a corresponding management scheme;
the optimizing module is also used for distributing the travel demands of people stream evacuation on public transportation to specific bus stops and routes according to the historical public transportation passenger flow assessment, the historical public transportation travel area and the public transportation travel time and the travel demands in the current evacuation process, and reasonably distributing bus transport capacity resources by combining with bus network space distribution;
the issuing module is used for issuing the prediction characteristic information of the emergency evacuation passenger flow to an information issuing screen (intelligent lamp pole), a traffic bureau, a public transport group and a track group according to the space-time distribution of the passenger flow such as the walking of a street, the walking to a public transport station, the subway station and the like, so that the effect of efficiently guiding the traffic evacuation is achieved.
The traffic emergency evacuation system and the traffic emergency evacuation method have the same advantages as compared with the prior art, and are not described in detail herein.
In one embodiment, a computer device is provided that includes a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the traffic emergency evacuation method described above when the computer program is executed.
FIG. 4 illustrates an internal block diagram of a computer device in one embodiment. The computer device may be specifically the terminal 110 (or the server 120) in fig. 1. As shown in fig. 4, the computer device includes a processor, a memory, a network interface, an input device, and a display screen connected by a system bus. The memory includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program which, when executed by a processor, causes the processor to implement a traffic emergency evacuation method. The internal memory may also store a computer program which, when executed by the processor, causes the processor to perform a traffic emergency evacuation method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, implements the steps of the traffic emergency evacuation method described above.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
Although the present disclosure is described above, the scope of protection of the present disclosure is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the disclosure, and these changes and modifications will fall within the scope of the invention.
Claims (8)
1. The traffic emergency evacuation method is characterized by comprising the following steps of:
acquiring real-time people stream monitoring data, regional data and activity data;
obtaining a people stream saturation index and a unit area people number index according to the real-time people stream monitoring data and the area data;
judging an early warning state according to the people stream saturation index, the unit area people number index and the activity data;
when the early warning state is an early warning state, issuing early warning information;
when the early warning state is a second early warning state, the early warning information is issued, and people flow slow evacuation is carried out through a people flow slow evacuation route;
when the early warning state is a three early warning state, the early warning information is issued, and the people stream slow evacuation and public transportation emergency dispatch are carried out through the people stream slow evacuation route;
the method for acquiring the people flow slow evacuation route comprises the steps of acquiring historical travel chain data, obtaining people flow travel time-space distribution and traffic mode proportion in specific activities and specific time according to the historical travel chain data, obtaining historical people flow travel distribution proportion according to the people flow travel time-space distribution, obtaining historical people flow time-space change according to the historical people flow travel distribution proportion and the traffic mode proportion, obtaining separated evacuation people flow according to the real-time people flow monitoring data, the historical people flow time-space change and activity ending time, and obtaining the people flow slow evacuation route according to the separated evacuation people flow and the real-time people flow monitoring data.
2. The traffic emergency evacuation method according to claim 1, wherein the real-time traffic monitoring data includes real-time people, the area data includes area and accommodation people, the activity data includes activity type and activity end time, the traffic saturation index and unit area people index are obtained according to the real-time traffic monitoring data and the area data, and the early warning state is judged according to the traffic saturation index, the unit area people index and the activity data, specifically including:
obtaining a people stream saturation index according to the real-time number of people and the accommodating number of people;
obtaining a unit area number index according to the real-time number of people and the area of the area;
and judging the early warning state according to the people stream saturation index, the unit area number index, the activity type and the activity ending time.
3. The traffic emergency evacuation method according to claim 2, wherein the real-time traffic monitoring data further includes congestion road section information and congestion site information, and wherein the issuing of the pre-warning information when the pre-warning state is an early-warning state specifically includes:
and when the early warning state is the early warning state, issuing the congestion road section information and/or the congestion site information.
4. The traffic emergency evacuation method according to claim 3, wherein the area data further comprises key area data and traffic cell data, and the acquiring the historical trip chain data specifically comprises:
and obtaining the historical trip chain data according to the historical key region data and the historical traffic cell data.
5. The traffic emergency evacuation method according to claim 2, wherein when the early-warning state is a three-early-warning state, public traffic emergency dispatch is performed, specifically comprising:
acquiring historical public transportation data and travel requirements of current public transportation;
and carrying out public transportation emergency dispatching according to the historical public transportation data and the travel demand of the current public transportation.
6. A traffic emergency evacuation system, comprising:
the acquisition unit is used for acquiring real-time people stream monitoring data, regional data and activity data;
the processing unit is used for obtaining a people stream saturation index and a unit area people number index according to the real-time people stream monitoring data and the area data;
the early warning unit is used for judging an early warning state according to the people stream saturation index, the unit area people number index and the activity data;
the processing unit is also used for issuing early warning information when the early warning state is an early warning state;
the processing unit is also used for issuing the early warning information when the early warning state is a second early warning state and carrying out people stream slow evacuation through a people stream slow evacuation route;
the processing unit is also used for issuing the early warning information when the early warning state is a three early warning state, and carrying out the people stream slow evacuation and public transportation emergency dispatch through the people stream slow evacuation route;
the processing unit is further used for obtaining the people flow travel space-time distribution and the traffic mode proportion in specific activities and specific time according to the historical travel chain data, obtaining the historical people flow travel distribution proportion according to the people flow travel space-time distribution, obtaining the historical people flow space-time variation according to the historical people flow travel distribution proportion and the traffic mode proportion, obtaining the separated evacuation people flow according to the real-time people flow monitoring data, the historical people flow space-time variation and the activity ending time, and obtaining the people flow slow evacuation route according to the separated evacuation people flow and the real-time people flow monitoring data.
7. The traffic emergency evacuation system of claim 6, wherein the processing unit comprises an optimization module and a release module, in particular comprising;
the optimizing module is also used for carrying out public transportation emergency dispatching according to the historical public transportation data and the travel demand of the current public transportation;
and the issuing module is used for issuing the early warning information according to the early warning state.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the traffic emergency evacuation method of any one of claims 1 to 5 when the computer program is executed.
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