A smart scenic area traffic optimization system

Abstract

The present invention discloses a smart scenic area traffic optimization system, belonging to the field of traffic optimization systems, comprising an image acquisition module, a sound acquisition module, a data analysis module, an early warning and emergency module, a pedestrian and vehicle diversion module, a route planning module, and a notification module; the image acquisition module is used to collect image information of scenic area roads through a camera and send the collected image information to the data analysis module; the sound acquisition module is used to collect sound information of scenic area roads through a sound sensor and send the collected sound information to the data analysis module; the data analysis module is used to receive and analyze the collected information, output the analysis results, and send them to the early warning and emergency module; the early warning and emergency module is used to issue risk warnings of corresponding levels based on the analysis results, and at the same time send corresponding emergency measures to the notification module based on the level of the risk warning. The present invention can optimize pedestrian flow management and ensure the safety and experience of tourists.

Description

Technical Field

[0001] The present invention relates to the field of traffic optimization systems, and in particular to a smart scenic area traffic optimization system. Background Art

[0002] As people's living standards improve, more and more people choose to visit scenic spots to relax and unwind. This leads to extremely congested traffic in popular scenic spots during holidays. To alleviate traffic pressure, scenic spots often optimize traffic during congestion. The scenic spot traffic optimization system is a comprehensive system that aims to intelligently upgrade and optimize traffic management within scenic spots through modern information technology and communication technologies, thereby improving traffic management efficiency, tourist travel experience, and the overall operation level of the scenic spot.

[0003] Existing scenic area traffic optimization systems typically simply collect pedestrian and vehicle flow information and use it to direct traffic to roads with high pedestrian and vehicle traffic. However, crowds in scenic areas present a double-edged sword for visitor experience and safety management. On the one hand, the bustling scene of crowds can create a rich tourism atmosphere, increasing visitor engagement and enjoyment. This lively atmosphere is particularly indispensable for scenic areas centered around culture, festivals, or special events. However, when a scenic area's visitor flow exceeds its capacity, it poses a series of safety hazards and management challenges. First, crowded conditions can easily lead to accidents such as pushing and trampling among visitors, increasing the risk of injury. Second, excessive visitor numbers can also place significant pressure on scenic area transportation, sanitation, and facilities, potentially causing traffic congestion, garbage accumulation, and damage to facilities, which in turn impacts the visitor experience. Therefore, balancing these contradictions, optimizing crowd management, and ensuring visitor safety and experience have become pressing challenges.

[0004] Therefore, those skilled in the art provide a smart scenic area traffic optimization system to solve the problems raised in the above background technology. Summary of the Invention

[0005] The purpose of the present invention is to provide a smart scenic area traffic optimization system that can optimize crowd flow management, ensure the safety and experience of tourists, and solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A smart scenic area traffic optimization system includes an image acquisition module, a sound acquisition module, a data analysis module, an early warning and emergency module, a pedestrian and vehicle diversion module, a route planning module, and a notification module;

[0008] The image acquisition module is used to collect image information of scenic area roads through a camera and send the collected image information to the data analysis module; the sound acquisition module is used to collect sound information of scenic area roads through a sound sensor and send the collected sound information to the data analysis module; the data analysis module is used to receive the collected information and analyze it, output the analysis results and send them to the early warning and emergency module; the early warning and emergency module is used to issue risk warnings of corresponding levels according to the analysis results, and send corresponding emergency measures to the notification module according to the level of the risk warning, and package the risk warning level together with the analysis results and send them to the pedestrian and vehicle diversion module and the route planning module; the pedestrian and vehicle diversion module is used to formulate a pedestrian and vehicle diversion plan based on the received data, and send the pedestrian and vehicle diversion plan to the notification module and the route planning module; the route planning module is used to formulate a route planning plan based on the received data, and send the route planning plan to the notification module; the notification module is used to notify pedestrians and drivers in the scenic area of ​​the pedestrian and vehicle diversion plan and the route planning plan, and at the same time notify the scenic area staff of the emergency measures.

[0009] As a further solution of the present invention: the specific process of the data analysis module analyzing the information collected by the image acquisition module is as follows:

[0010] Mark each road in the scenic area as Ai, i = 1···n, where n is a positive integer;

[0011] Perform image recognition on the image information collected from road Ai, count the number of pedestrians on road Ai and mark them as B, and then count the number of sightseeing vehicles on road Ai and mark them as C;

[0012] Calculate the real-time congestion weight value V = (B + 3 * C) of the current road Ai;

[0013] Compare the real-time congestion weight value V with the preset congestion weight value v. If V>v, plan the road Ai to the first sequence; if V≤v, plan the road Ai to the second sequence;

[0014] The number of roads Ai in the first sequence is counted and marked as D. If D>0, it means that there are congested roads in the current scenic area. If D=0, it means that there are no congested roads in the current scenic area.

[0015] As a further solution of the present invention: the specific process of the data analysis module analyzing the information collected by the sound collection module is as follows:

[0016] Perform speech recognition on the sound information collected from road AI, and then perform natural language processing to filter out the sources of tourists' dissatisfaction;

[0017] Count the number of tourist dissatisfaction sound sources corresponding to road Ai and mark it as E;

[0018] Sort each road Ai in the first sequence from largest to smallest according to its corresponding E to generate a priority list;

[0019] A priority list is output as a result of analyzing the sound information.

[0020] As a further solution of the present invention: the data analysis module can perform a comprehensive analysis on the information collected by the image acquisition module and the sound acquisition module to determine whether there is an emergency situation, specifically:

[0021] By performing image recognition on the image information collected from the road Ai, it is determined whether there is a fight on the current road Ai. If so, it indicates that there is an emergency on the current road Ai. If not, it proceeds to the next step;

[0022] By performing image recognition on the image information collected from the road Ai, it is determined whether there is a confrontation between the two parties on the current road Ai. If so, the process proceeds to the next step. If not, it indicates that there is no emergency situation on the current road Ai.

[0023] Sound information is collected from the area where the confrontation occurs on the road Ai for speech recognition to determine whether there are insulting words. If so, it means that there is an emergency situation on the current road Ai. If not, it means that there is no emergency situation on the current road Ai.

[0024] As a further solution of the present invention: the early warning and emergency response module issues risk warnings and corresponding emergency measures specifically as follows:

[0025] Compare the number D of roads Ai in the first sequence with a preset value d;

[0026] If 0<D≤d, a level 1 risk warning is issued, and the corresponding emergency measure is "dispatching at least one staff member to each road Ai in the first sequence to maintain order";

[0027] If d<D≤2*d, a level 2 risk warning is issued, and the corresponding emergency measures are "dispatching at least two staff members to each road Ai in the first sequence to maintain order and limit the number of people entering the scenic area";

[0028] If 2*d<D, a level 3 risk warning is issued, and the corresponding emergency measures are "dispatching at least three staff members to each road Ai in the first sequence to maintain order and closing the entrance to the scenic area";

[0029] If an emergency situation exists on the current road Ai, the early warning emergency module sends an emergency measure to the notification module, which is "dispatch at least five staff members to the road Ai where the emergency situation exists to maintain order and evacuate pedestrians on the road Ai at the same time."

[0030] As a further solution of the present invention: the specific process of the pedestrian and vehicle diversion module formulating the pedestrian and vehicle diversion plan is as follows:

[0031] Obtain the current location P1 of the sightseeing vehicle on the road Ai in the first sequence, and obtain the current location p1 of the pedestrian on the road Ai in the first sequence;

[0032] If the risk warning level is level one, then the destination P2 is planned for the sightseeing vehicle, and the straight-line distance between P2 and P1 is 500 meters. At the same time, the destination P2 is planned for the pedestrian, and the straight-line distance between P2 and P1 is 200 meters.

[0033] If the risk warning level is level 2, then the destinations P3 and P4 are planned for sightseeing vehicles, and the straight-line distance between P3 and P4 and P1 is one kilometer. At the same time, the destinations P3 and P4 are planned for pedestrians, and the straight-line distance between P3 and P4 and P1 is three hundred meters.

[0034] If the risk warning level is level three, the destinations P5, P6 and P7 are planned for sightseeing vehicles. The straight-line distance between P5, P6 and P7 and P1 is two kilometers. At the same time, the destinations p5, P6 and P7 are planned for pedestrians. The straight-line distance between P5, P6 and P7 and P1 is four hundred meters.

[0035] As a further solution of the present invention: the specific process of the route planning module formulating the route planning solution is as follows:

[0036] If the risk warning level is level 1, a vehicle driving route from P1 to P2 and a pedestrian driving route from P1 to P2 are generated;

[0037] If the risk warning level is level 2, the vehicle driving routes from P1 to P3 and P4, and the pedestrian driving routes from P1 to P3 and P4 are generated;

[0038] If the risk warning level is level three, vehicle driving routes from P1 to P5, P6 and P7, and pedestrian driving routes from P1 to P5, P6 and P7 are generated.

[0039] As a further solution of the present invention: when generating the vehicle driving routes and pedestrian driving routes, roads in the second sequence are preferably selected.

[0040] As a further solution of the present invention: the notification module includes a scenic area loudspeaker, a scenic area announcement display screen and a background terminal display screen, wherein the scenic area loudspeaker and the scenic area announcement display screen are used to broadcast the pedestrian and vehicle diversion plan and route planning plan to pedestrians and drivers in the scenic area, and the background terminal display screen is used to display the emergency measures corresponding to the current level of risk warning to the scenic area staff.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. This application first uses image recognition to determine which roads in the scenic area have excessive traffic and pedestrian flow, and then uniformly divides these roads that exceed the standard into the first sequence. Then, through voice recognition and natural language processing, it determines whether the pedestrians on these roads are dissatisfied with the scenic area or immersed in the lively atmosphere. Then, the roads with the most dissatisfaction with the crowded phenomenon are optimized first. This can not only ease the traffic in the scenic area, but also soothe the dissatisfaction of users, improve the user experience, and reduce accidents such as pushing and trampling among tourists. In addition, it can adopt different diversion plans according to different levels of risk warnings, and set diversion destinations of different distances for pedestrians and sightseeing vehicles on the scenic area roads, effectively alleviating the traffic pressure on the scenic area roads. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a structural diagram of a smart scenic area traffic optimization system. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0045] As mentioned in the background of this application, research has revealed that existing scenic area traffic optimization systems typically simply collect information on pedestrian and vehicle traffic flow, then use this information to direct traffic to roads with high pedestrian and vehicle traffic. However, high passenger volume in scenic areas presents a double-edged sword for both visitor experience and safety management. On the one hand, the bustling scene of crowds can create a vibrant tourist atmosphere, increasing visitors' sense of participation and enjoyment. This lively atmosphere is particularly indispensable for scenic areas themed around culture, festivals, or special events. However, when a scenic area's passenger volume exceeds its carrying capacity, it presents a series of safety hazards and management challenges. First, the crowded situation can easily lead to accidents such as pushing and trampling among tourists, increasing the risk of injury. Second, an excessive number of tourists can also place significant pressure on transportation, sanitation, and facilities in scenic areas, potentially causing traffic congestion, garbage accumulation, and damage to facilities, which in turn impacts the visitor experience and presents certain drawbacks.

[0046] In order to solve the above-mentioned defects, this application discloses a smart scenic area traffic optimization system that can optimize crowd flow management and ensure the safety and experience of tourists.

[0047] The following will describe in detail how the solution of this application solves the above technical problems with reference to the accompanying drawings.

[0048] See also Figure 1 In an embodiment of the present invention, a smart scenic area traffic optimization system includes an image acquisition module, a sound acquisition module, a data analysis module, an early warning and emergency module, a pedestrian and vehicle diversion module, a route planning module, and a notification module; the image acquisition module is used to collect image information of scenic area roads through a camera and send the collected image information to the data analysis module; the sound acquisition module is used to collect sound information of scenic area roads through a sound sensor and send the collected sound information to the data analysis module; the data analysis module is used to receive and analyze the collected information, output the analysis results and send them to the early warning and emergency module; the early warning and emergency module is used to issue a risk warning of a corresponding level based on the analysis results, and send corresponding emergency measures to the notification module based on the level of the risk warning, and package the risk warning level together with the analysis results and send them to the pedestrian and vehicle diversion module and the route planning module; the pedestrian and vehicle diversion module is used to formulate a pedestrian and vehicle diversion plan based on the received data and send the pedestrian and vehicle diversion plan to the notification module and the route planning module; the route planning module is used to formulate a route planning plan based on the received data and send the route planning plan to the notification module; the notification module is used to notify pedestrians and drivers in the scenic area of ​​the pedestrian and vehicle diversion plan and the route planning plan, and to notify scenic area staff of the emergency measures. This application first uses image recognition to determine which roads in the scenic area have excessive traffic and pedestrian flow, and then uniformly divides these roads that exceed the standard into a first sequence. Subsequently, through voice recognition and natural language processing, it is determined whether the pedestrians on these roads are dissatisfied with the scenic area or immersed in the lively atmosphere. Then, the roads with the most dissatisfaction with the crowded phenomenon are optimized first. This can not only ease the traffic in the scenic area, but also soothe the dissatisfaction of users, improve user experience, and reduce accidents such as pushing and trampling among tourists.

[0049] In this embodiment, the data analysis module analyzes the information collected by the image acquisition module as follows: Each road in the scenic area is labeled Ai, where i = 1...n, where n is a positive integer; image recognition is performed on the image information collected from road Ai, the number of pedestrians on road Ai is counted and labeled B, and the number of sightseeing vehicles on road Ai is counted and labeled C; the real-time congestion weight V = (B + 3*C) for the current road Ai is calculated; the real-time congestion weight V is compared with the preset congestion weight v. If V > v, road Ai is assigned to the first sequence; if V ≤ v, road Ai is assigned to the second sequence; the number of roads Ai in the first sequence is counted and labeled D. If D > 0, there is a congested road in the current scenic area; if D = 0, there is no congested road in the current scenic area. Image recognition is a conventional technology that uses computers to process, analyze, and understand images to identify various patterns of targets and objects. It is an important field in computer science and a practical application of artificial intelligence.

[0050] In this embodiment, the specific process of the data analysis module analyzing the information collected by the sound collection module is as follows: performing speech recognition on the sound information collected from the road Ai, and then performing natural language processing to filter out the sources of tourist dissatisfaction; counting the number of tourist dissatisfaction sources corresponding to the road Ai and marking them as E; sorting each road Ai in the first sequence from large to small according to the corresponding E to generate a priority list; and outputting the priority list as the analysis result of the sound information. Speech recognition is an existing well-known technology and includes the following steps: (1) Preprocessing, which preprocesses the collected speech signal, including noise suppression, endpoint detection, pre-emphasis, etc., to improve the accuracy of the speech recognition system. (2) Feature extraction, which extracts effective acoustic features from the preprocessed speech signal, such as Mel-frequency cepstral coefficients (MFCC), etc. These features will be used in the subsequent recognition process. (3) Decoding and recognition, which uses the trained speech recognition model to convert the extracted acoustic features into text. This process usually involves complex algorithms such as pattern matching and probability statistics. Natural language processing is also a well-known technology, including the following steps: (1) Word segmentation and part-of-speech tagging, which involves segmenting the identified text and tagging the part of speech of each word to facilitate subsequent analysis and understanding. (2) Sentiment analysis, which uses sentiment analysis technology in natural language processing to judge the emotional tendency of tourists' complaints. This usually involves methods such as matching sentiment dictionaries and predicting sentiment classification models. (3) Semantic understanding, which further understands the specific content of tourists' complaints and identifies key information such as the object, cause, and degree of the complaint. This may require combining multiple resources such as domain knowledge bases and contextual information.

[0051] In this embodiment, the data analysis module can perform a comprehensive analysis of the information collected by the image acquisition module and the sound acquisition module to determine whether an emergency situation exists. Specifically, the following steps are performed: image recognition is performed on the image information collected from road Ai to determine whether there is a fight on the current road Ai. If so, it indicates that an emergency situation exists on the current road Ai; if not, the process proceeds to the next step; image recognition is performed on the image information collected from road Ai to determine whether there is a confrontation between two parties on the current road Ai. If so, the process proceeds to the next step; if not, it indicates that there is no emergency situation on the current road Ai; sound information is collected from the area of ​​the road Ai where the confrontation occurs and voice recognition is performed to determine whether there is insulting language. If so, it indicates that an emergency situation exists on the current road Ai; if not, it indicates that there is no emergency situation on the current road Ai. This setting can quickly determine whether there is a fight or the possibility of a fight on the current road Ai.

[0052] In this embodiment, the early warning and emergency response module issues risk warnings and corresponding emergency measures as follows: The number D of roads Ai in the first sequence is compared with a preset value d. If 0 < D ≤ d, a level 1 risk warning is issued, with the corresponding emergency measure being "dispatching at least one staff member to each road Ai in the first sequence to maintain order." If d < D ≤ 2*d, a level 2 risk warning is issued, with the corresponding emergency measure being "dispatching at least two staff members to each road Ai in the first sequence to maintain order and restricting the number of people entering the scenic area." If 2*d < D, a level 3 risk warning is issued, with the corresponding emergency measure being "dispatching at least three staff members to each road Ai in the first sequence to maintain order and closing the entrance to the scenic area." If an emergency occurs on the current road Ai, the early warning and emergency response module sends an emergency measure to the notification module, stating "dispatching at least five staff members to maintain order on the road Ai where the emergency occurs and evacuating pedestrians on the road Ai." This configuration ensures that risk warnings of different levels are appropriately handled.

[0053] In this embodiment, the specific process of the pedestrian and vehicle diversion module formulating the pedestrian and vehicle diversion plan is as follows: obtaining the current location P1 of the sightseeing vehicle on the road Ai in the first sequence, and obtaining the current location p1 of the pedestrian on the road Ai in the first sequence; if the risk warning level is level one, then planning the destination P2 for the sightseeing vehicle, the straight-line distance between P2 and P1 is five hundred meters, and at the same time planning the destination p2 for the pedestrian, the straight-line distance between P2 and P1 is two hundred meters; if the risk warning level is level two, then planning the destinations P3 and P4 for the sightseeing vehicle, the straight-line distance between P3 and P4 and P1 is one kilometer, and at the same time planning the destinations p3 and p4 for the pedestrian, the straight-line distance between P3 and P4 and P1 is three hundred meters; if the risk warning level is level three, then planning the destinations P5, P6 and P7 for the sightseeing vehicle, the straight-line distance between P5, P6 and P7 and P1 is two kilometers, and at the same time planning the destinations p5, p6 and p7 for the pedestrian, the straight-line distance between P5, P6 and P7 and P1 is four hundred meters. This setting can adopt different diversion plans according to different levels of risk warnings, and set diversion destinations of different distances for pedestrians and sightseeing vehicles on scenic area roads, effectively alleviating traffic pressure on scenic area roads.

[0054] In this embodiment, the specific process of the route planning module formulating the route planning plan is: if the risk warning level is level one, the vehicle driving route from P1 to P2 and the pedestrian driving route from p1 to p2 are generated; if the risk warning level is level two, the vehicle driving route from P1 to P3 and P4 and the pedestrian driving route from p1 to p3 and p4 are generated; if the risk warning level is level three, the vehicle driving route from P1 to P5, P6 and P7 and the pedestrian driving route from p1 to p5, p6 and p7 are generated.

[0055] In this embodiment, when generating vehicle and pedestrian routes, roads in the second sequence are preferably selected. This setting ensures that the vehicle and pedestrian routes pass through fewer congested sections.

[0056] In this embodiment, the notification module includes a scenic area loudspeaker, a scenic area announcement display screen and a background terminal display screen. Among them, the scenic area loudspeaker and the scenic area announcement display screen are used to broadcast the pedestrian and vehicle diversion plan and route planning plan to pedestrians and drivers in the scenic area, and the background terminal display screen is used to display the emergency measures corresponding to the current level of risk warning to the scenic area staff.

[0057] The present invention first uses image recognition to determine which roads in a scenic area have excessive traffic and pedestrian flow, then uniformly groups these roads into a first sequence. Subsequently, through voice recognition and natural language processing, it determines whether pedestrians on these roads are dissatisfied with the scenic area or simply enjoying the bustling atmosphere. This system then prioritizes roads where pedestrians are most dissatisfied with the crowded environment. This not only eases traffic in the scenic area, but also alleviates user dissatisfaction, improves user experience, and reduces accidents such as pushing and trampling among tourists. Furthermore, the system can adopt different diversion plans based on different levels of risk warnings, establishing diversion destinations of varying distances for pedestrians and sightseeing vehicles on scenic area roads, effectively alleviating traffic pressure on scenic area roads.

[0058] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

[0059] The above is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solutions and inventive concepts of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A smart scenic area traffic optimization system, characterized by: It includes image acquisition module, sound acquisition module, data analysis module, early warning and emergency module, pedestrian and vehicle diversion module, route planning module and notification module; The image acquisition module is used to collect image information of the scenic area road through a camera and send the collected image information to the data analysis module; The sound collection module is used to collect sound information from scenic area roads through sound sensors and send the collected sound information to the data analysis module; the data analysis module is used to receive and analyze the collected information, output the analysis results and send them to the early warning and emergency response module; the early warning and emergency response module is used to issue risk warnings of corresponding levels based on the analysis results, and send corresponding emergency measures to the notification module based on the level of the risk warning, and package the risk warning level together with the analysis results and send them to the pedestrian and vehicle diversion module and the route planning module; The pedestrian and vehicle diversion module is used to formulate a pedestrian and vehicle diversion plan based on the received data and send the pedestrian and vehicle diversion plan to the notification module and the route planning module; The route planning module is used to formulate a route planning plan based on the received data and send the route planning plan to the notification module; The notification module is used to notify pedestrians and drivers in the scenic area of ​​the pedestrian and vehicle diversion plan and route planning plan, and to notify the scenic area staff of the emergency measures; The specific process of the data analysis module analyzing the information collected by the image acquisition module is as follows: Mark each road in the scenic area as Ai, i=1···n, where n is a positive integer; Perform image recognition on the image information collected from road Ai, count the number of pedestrians on road Ai and mark them as B, and then count the number of sightseeing vehicles on road Ai and mark them as C; Calculate the real-time congestion weight value V = (B + 3 * C) of the current road Ai; Compare the real-time congestion weight value V with the preset congestion weight value v. If V>v, plan the road Ai to the first sequence; if V≤v, plan the road Ai to the second sequence; Count the number of roads Ai in the first sequence, marked as D. If D>0, it means there are congested roads in the current scenic area. If D=0, it means there are no congested roads in the current scenic area. The specific process of the data analysis module analyzing the information collected by the sound collection module is as follows: Perform speech recognition on the sound information collected from road AI, and then perform natural language processing to filter out the sources of tourists' dissatisfaction; Count the number of tourist dissatisfaction sound sources corresponding to road Ai and mark it as E; Sort each road Ai in the first sequence from largest to smallest according to its corresponding E to generate a priority list; Outputting a priority list as a result of analyzing the sound information; The data analysis module can perform a comprehensive analysis on the information collected by the image acquisition module and the sound acquisition module to determine whether there is an emergency situation, specifically: By performing image recognition on the image information collected from the road Ai, it is determined whether there is a fight on the current road Ai. If so, it indicates that there is an emergency on the current road Ai. If not, it proceeds to the next step; By performing image recognition on the image information collected from the road Ai, it is determined whether there is a confrontation between the two parties on the current road Ai. If so, the process proceeds to the next step. If not, it indicates that there is no emergency situation on the current road Ai. Sound information is collected from the area where the confrontation occurs on the road Ai for speech recognition to determine whether there are insulting words. If so, it means that there is an emergency situation on the current road Ai. If not, it means that there is no emergency situation on the current road Ai.

2. A smart scenic area traffic optimization system according to claim 1, characterized in that: The early warning and emergency response module issues risk warnings and corresponding emergency measures as follows: Compare the number D of roads Ai in the first sequence with a preset value d; If 0<D≤d, a level 1 risk warning is issued, and the corresponding emergency measure is "dispatch at least one staff member to each road Ai in the first sequence to maintain order"; If d<D≤2*d, a level 2 risk warning is issued, and the corresponding emergency measures are "dispatching at least two staff members to each road Ai in the first sequence to maintain order and limit the number of people entering the scenic area"; If 2*d<D, a level 3 risk warning is issued, and the corresponding emergency measures are "dispatching at least three staff members to each road Ai in the first sequence to maintain order and closing the entrance to the scenic area"; If an emergency situation exists on the current road Ai, the early warning emergency module sends an emergency measure to the notification module, which is "dispatch at least five staff members to the road Ai where the emergency situation exists to maintain order and evacuate pedestrians on the road Ai at the same time." 3. A smart scenic area traffic optimization system according to claim 2, characterized in that: The specific process of the pedestrian and vehicle diversion module formulating the pedestrian and vehicle diversion plan is as follows: Obtain the current location P1 of the sightseeing vehicle on the road Ai in the first sequence, and obtain the current location p1 of the pedestrian on the road Ai in the first sequence; If the risk warning level is level one, then the destination P2 is planned for the sightseeing vehicle, and the straight-line distance between P2 and P1 is 500 meters. At the same time, the destination P2 is planned for the pedestrian, and the straight-line distance between P2 and P1 is 200 meters. If the risk warning level is level 2, then the destinations P3 and P4 are planned for sightseeing vehicles, and the straight-line distance between P3 and P4 and P1 is one kilometer. At the same time, the destinations P3 and P4 are planned for pedestrians, and the straight-line distance between P3 and P4 and P1 is three hundred meters. If the risk warning level is level three, the destinations P5, P6 and P7 are planned for sightseeing vehicles. The straight-line distance between P5, P6 and P7 and P1 is two kilometers. At the same time, the destinations p5, P6 and P7 are planned for pedestrians. The straight-line distance between P5, P6 and P7 and P1 is four hundred meters.

4. The intelligent scenic area traffic optimization system according to claim 3 is characterized in that: The specific process of the route planning module formulating the route planning solution is as follows: If the risk warning level is level 1, a vehicle driving route from P1 to P2 and a pedestrian driving route from P1 to P2 are generated; If the risk warning level is level 2, the vehicle driving routes from P1 to P3 and P4, and the pedestrian driving routes from P1 to P3 and P4 are generated; If the risk warning level is level three, vehicle driving routes from P1 to P5, P6 and P7, and pedestrian driving routes from P1 to P5, P6 and P7 are generated.

5. The intelligent scenic area traffic optimization system according to claim 4 is characterized in that: When generating the vehicle driving routes and pedestrian driving routes, roads in the second sequence are preferably selected.

6. The intelligent scenic area traffic optimization system according to claim 5, characterized in that: The notification module includes a scenic area loudspeaker, a scenic area announcement display screen and a background terminal display screen. Among them, the scenic area loudspeaker and the scenic area announcement display screen are used to broadcast the pedestrian and vehicle diversion plan and route planning plan to pedestrians and drivers in the scenic area, and the background terminal display screen is used to display the emergency measures corresponding to the current level of risk warning to the scenic area staff.

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